Stand-alone Administrative Social Science Data Assets

https://datahub.roadsafety.gov.au/

Data Custodian/Owner: ABS

Source of Metadata Extraction: https://www.abs.gov.au/census

21.05.2025

Archived on 04.12.2025: https://www.abs.gov.au/census

National Assessment Program — Literacy and Numeracy (NAPLAN)

Purpose: National Assessment Program — Literacy and Numeracy (NAPLAN) is the annual assessment of literacy and numeracy performance undertaken by all students in Years 3, 5, 7 and 9. The purpose of the NAPLAN dataset is to assess and monitor the literacy and numeracy skills of Australian students, and to support educational research, policy development, and school improvement initiatives. Specifically, the dataset serves the following key purposes: 1) monitor student achievements in reading, writing, language conventions and numeracy; 2) support schools and teachers; 3) inform system-level reporting and policy.

Main Topic: Childcare, education, and training

Other topics:

Demographics
Organisational characteristics

Subtopics:

Information about student and their parents
Information about school
Test results – reading, writing, language conventions (spelling, grammar and punctuation) and numeracy

Included into an integrated data asset:

Population scope: All students in Years 3, 5, 7, and 9 enrolled in government, catholic, independent and special schools

Geographic scope: Australia (national)

Temporal range: 2008 - ongoing

Temporal Unit/Frequency: Annually

Unit of Observation: Student; school; test event and test item presented to a student

Type of Unit of Observation: Individual; Organisation; Event/Process/Activity

Collection & Compilation Methods: NAPLAN test is administered to all students in Years 3,5,7 and 9 in Australia over three days annually in May. Paper-based versions were used until 2017. Online adaptive testing was first used in 2018 and fully implemented by 2022. Schools collect and submit data about each participating student, including name, year level, date of birth, gender, Indigenous status, language background, parental education and occupation, and participation status (e.g. exempt, absent). These data are sourced from school enrolment systems and standardised student background questionnaires (based on ACARA’s guidelines). Writing tests are marked centrally by trained human assessors using ACARA-developed rubrics. Other domains are marked automatically (online) or via scanning and automated systems (paper). Raw scores are compiled and verified through quality assurance processes. Raw scores are converted to NAPLAN scale scores using statistical methods. Results are mapped onto Proficiency Bands (Bands 1–10) to enable comparison over time. ACARA conducts: item analysis; differential item functioning (DIF) testing; and test reliability and validity checks. Statistical equating ensures results are comparable across years and jurisdictions. Individual-level data are stripped of direct identifiers.

Data Quality (Scope): High coverage: NAPLAN is a census-style assessment, intended to include all students in Years 3, 5, 7, and 9 in Australian schools (government, Catholic, and independent). It covers all states and territories and includes special schools. While the scope is comprehensive, certain groups may not be fully represented in practice such as students withdrawn by parents/carers; students with <1 year of English instruction; students with significant disabilities; absentees; homeschoolers. Additionally, there is no NAPLAN data available for 2020 due to the test cancellation because of the pandemic.

Data Quality (Other): Well-documented variables (see NAPLAN Online Data Extract Dictionary, NAPLAN Score Equivalence Tables). Scoring is done via automated systems (for multiple-choice) and trained human markers (for writing). Scaling and equating methods are statistically robust and validated annually. Some background variables (e.g. parental education) are collected via schools and often based on parent/carer self-report or school enrolment systems introducing potential bias. All states/territories follow national testing protocols, however, some variation in data collection methods may introduce minor inconsistencies in metadata or variable formatting. Change in delivery mode (paper to online from 2018–2022) may introduce mode effects in responses and adaptive test paths

Data Access: Student level data is available across several datasets: NAPLAN results, NAPLAN matched, NAP Information and Communication Literacy, NAP Science Literacy, NAP Civics and Citizenship, Student Background data. Some personal information of students who participated in the NAPLAN tests such as student ID, DOB, gender, Indigenous status, LBOTE status, information about their parents or guardians’ level of education and occupation is available. The NAPLAN Results Data Dictionary 2024 is available subject to completion of the application form. School level data is available. Generally, only deidentified data is available, however the following report has linked individual level NAPLAN data with the Longitudinal Surveys of Australian Youth: Lumsden, Marilyn & Semo, Ronnie & Blomberg, Davinia. (2015). Linking NAPLAN scores to the Longitudinal Surveys of Australian Youth. ACARA’s Data Access Protocols are intended to supplement the Principles and protocols for reporting on schooling in Australia, June 2009, and operate in conjunction with related legal agreements and procedures to ensure a rigorous and consistent process is in place for assessing applications and releasing data. No data will be provided that identifies, or could lead to the identification of, individual students. Data will only be released subject to an assessment of its compliance with the Data Access Protocols 2012 More information about ACARA data access is provided via the ACARA - Data Access Program page. Data request application form: https://acara.edu.au/contact-us/acara-data-access#:~:text=In%20the%20event%20of%20a%20data

Data is available across different geographical levels from state and territory, SA, LGA and postcodes.

More Information: NAPLAN online data extract dictionary naplan-online-data-extract-dictionary.pdf

NAPLAN Score Equivalence Tables http://www.acara.edu.au/assessment/naplan/naplan-score-equivalence-tables

ACARA Data Catalogue: Data_Catalogue.pdf

Email: info@acara.edu.au

Data Custodian/Owner: ACARA; Respective jurisdictions

Source of Metadata Extraction: https://www.acara.edu.au/assessment/naplan

04.06.2025

Archived on 05.12.2025: https://www.acara.edu.au/assessment/naplan

Australian Early Development Census (AEDC)

Purpose: The Australian Early Development Census (AEDC) is a nationwide census of early child development that shows how young children have developed as they start their first year of full-time school. The AEDC provides a population-level snapshot of how children are developing when they start full-time school, so that communities, schools and governments can identify strengths and developmental vulnerabilities, monitor trends over time, and use evidence to plan policies, services and supports that improve early childhood outcomes.

Main Topic: Health

Other topics:

Demographics
Childcare, education, and training

Subtopics:

Physical health and wellbeing
Social competence
Emotional maturity
Language and cognitive skills (school-based)
Communication skills and general knowledge

Included into an integrated data asset:

CWDA
PLIDA

Population scope: All children in their first year of full-time school across all Australia

Geographic scope: Australia (national)

Temporal range: 2009- ongoing (2024 – the most recent)

Temporal Unit/Frequency: Point-on-time/every three years

Unit of Observation: Individual child

Type of Unit of Observation: Individual

Collection & Compilation Methods: The AEDC is a nationwide data collection of early childhood development at the time children commence their first year of full-time school. AEDC data are collected every three years. The sixth collection took place in 2024. Around 300,000 children are included in each collection of the AEDC, totalling over 1.7 million children since the AEDC began. AEDC Data are collected using the AEDC Instrument, at the core of which is the Australian Version of the Early Development Instrument (AvEDI). The AvEDI adapts the Early Development Instrument (EDI) developed by the Offord Centre at McMaster University (Canada) to the Australian context. The AvEDI is completed by teachers based on their observations of the children in their class, and it collects data relating to five key domains of early childhood development: physical health and wellbeing; social competence; emotional maturity; language and cognitive skills (school-based); communication skills and general knowledge. The collected checklists are entered into a secure central database. Each record is linked to the child’s school, community and postcode of residence (but not to individual names). Data undergo validation and quality assurance checks before analysis.

Data Quality (Scope): High coverage: AEDC is a census-style data asset, intended to include all children in their first year of full-time school (typically aged 4-6) across Australia. High participation rate (more than 95%). Data quality is generally high due to its structured, population-based design, however certain groups may not be fully represented, e.g. absent children, home-schooled children, recently arrived immigrants.

Data Quality (Other): Well-documented variables (see AEDC Data Dictionary). Responses are converted into domain scores and vulnerability indicators using standardised scoring algorithms. The Early Development Instrument is completed by teachers. Subjective reporting which is based on teacher observations may introduce some potential bias.

Data Access: AEDC Data are available at both the aggregated or macro level and at the unit-record or micro level. Unit-record level data can be identified or de-identified Macrodata include derived summary data such as sums, proportions, and means, and are typically aggregated by geography, AEDC Cycle, and demographic characteristics. Deidentified AEDC microdata include unit-record level analytical variables obtained from the AvEDI and nonidentifying background and demographic variables. Deidentified AEDC microdata can be accessed either by application or via a data sharing agreement. Identified AEDC microdata include unit-record level demographic data that can be jointly utilised to identify the individuals they pertain to. Identified AEDC microdata are securely held by the DMA and are exclusively disclosed for data linkage purposes to authorised data linkage agencies. These include Approved Data Linkage Units (DLU)s, Commonwealth accredited integrated authorities, and AEDC Integrating Authorities. AEDC Approved DLUs and Commonwealth Accredited Integrating Authorities are able to undertake data linkage for Data Users requesting AEDC Data via the application process.

AEDC data is publicly available at various geographies including: national; state/territories; AEDC communities; AEDC local communities; various social geographies including SA2, SA3, SA4, LGA

More Information: AEDC data dictionary https://www.aedc.gov.au/resources/detail/aedc-2025-data-dictionary

2024 AEDC National Report https://www.aedc.gov.au/resources/detail/2024-aedc-national-report

Data by LGA: https://www.aedc.gov.au/data-hub/public-data/additional-data

User guides: http://www.aedc.gov.au/data-hub/interpreting-data/aedc-user-guides

Email: aedc@education.gov.au

Data Custodian/Owner: Australian Government Department of Education

Source of Metadata Extraction: https://www.aedc.gov.au/what-is-the-aedc/about-the-aedc

30.06.2025

Archived on 05.12.2025: https://www.aedc.gov.au/what-is-the-aedc/about-the-aedc

School Entry Health Assessment (SEHA)

Purpose: SEHA aims at monitoring and supporting child’ health and development at the time of school entry in Western Australia. It aims to promote the health and development of children by engaging with families and school staff and to identify children who may be at risk of health and developmental concerns, through use of age-appropriate surveillance activities

Main Topic: Health

Other topics:

Demographics

Subtopics:

Vision
Hearing
Growth
Oral health
General health
Healthy lifestyle
Child development

Included into an integrated data asset:

Population scope: All children enrolled in the Kindergarten or pre-primary in WA, including public, some catholic, private and independent schools in WA

Geographic scope: Western Australia

Temporal range: 2000-ongoing

Temporal Unit/Frequency: Annually

Unit of Observation: An individual child in the Kindergarten or pre-primary in WA

Type of Unit of Observation: Individual

Collection & Compilation Methods: The School Entry Health Assessment (SEHA) data set is collected and compiled using standardised clinical and administrative processes coordinated by Community Health Nurses under the Child and Adolescent Health Service (CAHS). Data from multiple regions and services are compiled centrally by CAHS. Data is collected through: 1) direct assessments including vision test (e.g., Snellen or LEA charts), hearing test (audiometer), and growth measurements (height, weight, BMI calculation); 2) parent questionnaire which collects information on developmental history, medical conditions, and behavioural concerns; 3) nurse observations and notes including general health, emotional wellbeing, and referrals. Information is documented during the nurse’s visit to the school. Most SEHA records are hard-copy, paper records. Information is collected from parents and documented by health service staff in the course of assessment and care. Much of the information collected is entered onto the Community Health Information System (CHIS). Data is cleaned and validated before central compilation. Data is standardised by using standard clinical guidelines and screening forms to ensure consistency across locations. Data fields are standardised to support comparability and linkage.

Data Quality (Scope): Completion is voluntary. Not all parents complete data for their children, however the completion rate is high. For example, in 2018, the SEHA program achieved a 96% completion rate among children enrolled in kindergarten within the metropolitan area. Children who are not assessed during their kindergarten year are offered the assessment in pre-primary.

Data Quality (Other): Data partially is self-reported by parents introducing potential bias. Format potential for transcription variation due to the use of paper and electronic formats. Data quality is maintained through: staff training, regular audits and electronic validation checks. The quality of variables varies depending on the type of variable and the method of data collection. It is high for clinically collected variables and lower for the self-reported ones. Completion may vary by region, school type (e.g. non-government schools), and demographic groups (e.g. Aboriginal children in remote areas may have lower coverage).

Data Access: SEHA is not publicly available as open data. It is a restricted administrative health dataset collected for operational and clinical purposes. Access requires formal approval.

More Information: School Entry Health Assessment Records Management Procedure: https://www.wacountry.health.wa.gov.au/~/media/WACHS/Documents/About-us/Policies/School-Entry-Health-Assessment-Records-Management-Procedure.pdf

Universal Contact School Entry Health Assessment: https://www.cahs.health.wa.gov.au/-/media/HSPs/CAHS/Documents/Community-Health/CHM/Universal-contact-School-Entry-Health-Assessment.pdf

Email: CAHS.ROI@health.wa.gov.au

Data Custodian/Owner: Child and Adolescent Health Services (CAHS)

Source of Metadata Extraction: https://www.cahs.health.wa.gov.au/Our-services/Community-Health/School-Health/Starting-school/School-Entry-Health-Assessment

02.07.2025

Archived on 05.12.2025: https://www.cahs.health.wa.gov.au/Our-services/Community-Health/School-Health/Starting-school/School-Entry-Health-Assessment

Australian Road Deaths Database (ARDD)

Purpose: The Australian Road Deaths Database (ARDD) provides basic details of road traffic crash fatalities in Australia as reported by the police each month to the State and Territory road safety authorities. It is published by the Bureau of Infrastructure and Transport Research Economics (BITRE).

Main Topic: Transport

Other topics:

Demographics

Subtopics:

Crash characteristics
Road user type
Fatality characteristics

Included into an integrated data asset:

Population scope: All people in Australia who die as a result of a police-reported road traffic crash, where the death occurs within 30 days of the crash.

Geographic scope: Australia (national)

Temporal range: 1989-ongoing

Temporal Unit/Frequency: Monthly

Unit of Observation: Persons killed in fatal road crashes; Fatal road crashes

Type of Unit of Observation: Individual; Event/Process/Activity

Collection & Compilation Methods: Each state and territory’s road safety authorities collect data from police reports on fatal road crashes. These authorities submit data monthly to BITRE. BITRE aggregates this data to form a national dataset. The ARDD includes details of individuals who die within 30 days of a road crash due to injuries sustained. Each fatal crash is recorded, with details such as date, time, location, and crash type. BITRE performs validation checks to ensure data accuracy and consistency.

Data Quality (Scope): High coverage: aims to include all fatal road crashes in Australia.

Data Quality (Other): The data are supplied by jurisdictional authorities and compiled by the BITRE. Accuracy depends on the initial police reports, which may be subject to human error or variability in reporting practices. Some fields (e.g. contributing factors or precise crash dynamics) may be missing, underreported, or inconsistently coded across jurisdictions.

Data Access: ARDD data is publicly available on the BITRE website and DITRDCSA Data Catalogue - Australian Road Deaths Database For individual level data researchers need to contact BITRE

More Information: Data files and dictionary catalogue.data.infrastructure.gov.au/dataset/australian-road-deaths-database

Email: roadsafetystatistics@infrastructure.gov.au

Data Custodian/Owner: Bureau of Infrastructure and Transport Research Economics (BITRE)

Source of Metadata Extraction: bitre.gov.au/statistics/safety/fatal_road_crash_database

01.07.2025

Archived on 05.12.2025: https://www.bitre.gov.au/statistics/safety/fatal_road_crash_database

Kindergarten Health Check (KHC)

Purpose: The purpose of the Kindergarten Health Check (KHC) dataset is to systematically monitor the health and development of children in their first year of formal schooling in the ACT. The KHC program is designed to: identify potential health, developmental, or behavioural concerns early in a child’s life, particularly in areas such as vision, hearing, oral health, nutrition, and general physical development; facilitate early referral to appropriate health or support services where issues are detected; support public health planning and service delivery.

Main Topic: Health

Other topics:

Demographics

Subtopics:

Vision Hearing Physical health Developmental concerns Behavioural wellbeing Lifestyle Family environment Healthcare services use

Included into an integrated data asset:

Population scope: All children enrolled in the Kindergarten in ACT public schools

Geographic scope: Australian Capital Territory

Temporal range: 2005-ongoing

Temporal Unit/Frequency: Annually

Unit of Observation: An individual child in the Kindergarten in ACT

Type of Unit of Observation: Individual

Collection & Compilation Methods: The Kindergarten Health Check (KHC) is a long running cross-sectional survey and universal health assessment of all children enrolled in their first year of fulltime primary education (Kindergarten) in the Australian Capital Territory. Validated standard tools are used to collect data covering chronic illness, population health issues and childhood development and emotional health in ACT children. Questionnaires are distributed in the beginning of the school year to parents. The completed questionnaires are returned to schools and then forwarded to the Academic Unit of General Practice (AUGP) for data entry and analysis. With parental consent, registered nurses from the School Health Team perform in April and October health checks at the child’s school, including: Vision Screening: Assessing visual acuity using standardized eye charts. Hearing Screening: Evaluating hearing capabilities through audiometric tests. Growth Measurements: Recording height and weight to calculate Body Mass Index (BMI). Responses from questionnaires and physical assessments are entered into a secure database managed by the AUGP. The data is geocoded and is enabled for record linkage (via Centre for Health Record Linkage CHeReL).

Data Quality (Scope): Participation rate is usually high with approximately 93% of parents completing the initial questionnaire, and over 85% of eligible children participating in both questionnaire and physical check. However, it is offered only in public schools – children in non-government schools are excluded.

Data Quality (Other): Health checks are conducted by trained nurses following standardised protocols, which helps ensure high consistency in data collection. Missing data may occur due to non-consent, child absence, or incomplete screening. Data entry is typically done electronically and checked by health staff, though occasional entry errors or inconsistencies are possible. Quality of variables may vary. Subjective inputs such as behavioural or emotional concerns may introduce inconsistency or bias.

Data Access: Aggregated data and summary reports from the KHC program are available to the public. These reports can be accessed through the ACT Government’s Open Government Information portal. Access to deidentified individual-level data is restricted. A formal application process is required. Enquiries about potential data linkage should be directed to: https://www.act.gov.au/directorates-and-agencies/act-health/data-statistics-and-surveys/healthstats-act/data-linkage

More Information: 37625-Kindergarten-Health-Check-Consent-and-Questionnaire_pg1-and-2.pdf

The Kindergarten Health Check. All Grown Up, An overview and summary data over 18 years, 2024 - Open Government Information

Email: KindyHealthAUGP@act.gov.au

Data Custodian/Owner: ACT Health Directorate

Source of Metadata Extraction: http://www.canberrahealthservices.act.gov.au/services-and-clinics/services/kindergarten-health-check

02.07.2025

Archived on 05.12.2025: https://www.canberrahealthservices.act.gov.au/services-and-clinics/services/kindergarten-health-check

Adult Migrant English Program (AMEP)

Purpose: To enable research and policy evaluation on the English language acquisition, integration, and long-term settlement outcomes of migrants and humanitarian entrants in Australia.

Main Topic: Childcare, education, and training

Other topics:

Demographics
Social support and welfare

Subtopics:

Enrolment and participation in AMEP
Hours of English tuition received
Course type and level
Completion status and learning progress
English proficiency (at entry and post-training)
Need for interpreter services
Highest level of education
Occupation
Number of years of schooling
Visa type
Visa grant and type expiry date
Geographic location at the moment of AMEP enrolment

Included into an integrated data asset:

PLIDA

Population scope: Adults (and some people aged 15-17) who were granted a permanent, eligible temporary visa or Australian citizens who held an eligible visa in the past

Geographic scope: Australia (national)

Temporal range: 2003-2019

Temporal Unit/Frequency: Not scheduled

Unit of Observation: A certain visa type holder enrolled into an AMEP program

Type of Unit of Observation: Individual

Collection & Compilation Methods: The data comes from administrative records maintained by the Department of Home Affairs, which oversees the AMEP. Data is collected from AMEP service providers (e.g., TAFE institutions and private education organisations) which deliver AMEP programs to eligible migrants.

Data Quality (Scope): The dataset includes records of immigrants who participated in the AMEP from 2003 to 2019. However, there may be underrepresentation in certain regions or among highly mobile populations. Data is sourced from administrative records, which are generally reliable.

Data Quality (Other): Variation in variable completeness across contributing datasets. Some delay in the inclusion of recent arrivals

Data Access: Access via ABS DataLab only. Project approval, data custodian agreement, and compliance with ABS microdata handling rules are required. Outputs subject to disclosure risk assessment.

More Information: About the program: https://immi.homeaffairs.gov.au/settling-in-australia/amep/about-the-program

https://www.abs.gov.au/about/data-services/data-integration/data-integration-project-register/data-assets?

Data Custodian/Owner: Department of Home Affairs

Source of Metadata Extraction: https://www.abs.gov.au/statistics/microdata-tablebuilder/available-microdata-tablebuilder/person-level-integrated-data-asset-plida/PLIDA%20Modular%20Product%20-https://www.abs.gov.au/statistics/microdata-tablebuilder/available-microdata-tablebuilder/person-level-integrated-data-asset-plida/PLIDA%20Modular%20Product%20-%20PLIDA%20Data%20Item%20List%20-%202025.02.20.xlsx (not working as of 02.12.2025)

30.04.2025

02.12.2025

Archived on 05.12.2025: https://www.canberrahealthservices.act.gov.au/services-and-clinics/services/kindergarten-health-check

Early Childhood Education and Care National Workforce Census (NWC)

Purpose: The NWC aims to improve the quality of information used in developing and measuring early childhood policy and programs. This data helps inform government policies and programs. 

Main Topic: Childcare, education, and training

Other topics:

Demographics
Organisational characteristics

Subtopics:

Service capacity
Service usage
Staff turnover
Workforce challenges
COVID-19 impacts
Workforce characteristics

Included into an integrated data asset:

Population scope: All approved early childhood education and care (ECEC) services in Australia

Geographic scope: Australia (national)

Temporal range: 2010-ongoing

Temporal Unit/Frequency: Every three years

Unit of Observation: Childcare service, educators and staff members

Type of Unit of Observation: Organisation; Individual

Collection & Compilation Methods: The Early Childhood Education and Care (ECEC) National Workforce Census (NWC) collects data using structured, government-administered processes designed to gather information from approved ECEC providers across Australia. Data collection is undertaken via a self-completion methodology, with the predominant mode being online. Collected information includes: service use, children with additional needs, access to preschool programs staff details, including staff demographics, types of work, roles, wages, professional development, qualifications, tenure, experience and current study.

Larger providers (of 40 or more services) are offered the option to provide consolidated data for their services via a spreadsheet, along with selected other providers whose circumstances made a group submission via spreadsheet their best option. These results are consolidated with the self-completion data, cleaned and weighted for analysis.

Responses are validated for internal consistency and logical coherence. Data are aggregated at service, provider, and national levels. Non-response follow-up is conducted to maximise participation. Data are weighted and adjusted for non-response to ensure representativeness across service types and jurisdictions.

Data Quality (Scope): The NWC is mandatory for all CCS approved providers and services which ensures a high participation rate. For example, the 2024 NWC achieved a 97.4% response rate across CCS approved services which includes Centre Based Day Care (CBDC), Outside School Hours Care (OSHC), Vacation Care (VAC), Family Day Care (FDC), and In Home Care (IHC) services.

Data Quality (Other): Data is collected through structured surveys. Data is weighted to account for non-response and to ensure that the results are representative of the national ECEC sector. The census includes various service types and geographic locations, enhancing the representativeness of the data.

Data Access: The Department of Education publishes aggregated data from the census in various formats, including national tables which provide data on service capacity, workforce demographics, and participation rates; regional tables and national reports. Access to individual-level data is restricted. Researchers need to contact the Department for more information on how to access the data at: contact.centre@education.gov.au

More Information: Report: https://www.education.gov.au/early-childhood/resources/2024-early-childhood-education-and-care-national-workforce-census-report

Previous census data: https://www.education.gov.au/early-childhood/about/data-and-reports/national-workforce-census/2021

https://www.education.gov.au/early-childhood/about/data-and-reports/national-workforce-census/2016

https://www.education.gov.au/early-childhood/about/data-and-reports/national-workforce-census/2013

https://www.education.gov.au/early-childhood/resources/2010-national-early-childhood-education-and-care-workforce-census

Email: ECEC-NWC@education.gov.au

Data Custodian/Owner: Australian Government Department of Education

Source of Metadata Extraction: https://www.education.gov.au/early-childhood/about/data-and-reports/national-workforce-census

03.07.2025

Archived on 05.12.2025: https://www.education.gov.au/early-childhood/about/data-and-reports/national-workforce-census

Healthy under 5 Kids (HU5K)

Purpose: The purpose of the Healthy under 5 Kids (HU5K) dataset is to systematically monitor is to support the monitoring, early identification, and ongoing care of the health, development, and wellbeing of children aged 0 to 5 years in the Northern Territory (NT), particularly in remote and First Nations communities.

Main Topic: Health

Other topics:

Demographics

Subtopics:

Age-specific health checks
Initial and risk assessments
Nutrition and feeding
Hearing and vision
Immunizations
Oral health
Psychological health
Parenting
Environmental and social risk factors

Included into an integrated data asset:

Population scope: Children aged 0 to 5 years residing in the Northen Territory

Geographic scope: Northern Territory

Temporal range: 2015-ongoing

Temporal Unit/Frequency: Annually

Unit of Observation: An individual child aged 0-5 in the NT

Type of Unit of Observation: Individual

Collection & Compilation Methods: The HU5K data are collected during standardised child health checks conducted by remote area nurses, Aboriginal health practitioners, and other child and family health professionals. These health checks are scheduled at key developmental milestones (e.g. at birth, 2 weeks, 6 weeks, 2, 4, 6, 12, 18 months, and at 2, 3, and 4.5 years). Data are entered directly into the HU5K module within the Communicare EHR system used by NT Health. This includes structured templates with fields covering physical growth (e.g. weight, height, head circumference), nutrition, immunisation, developmental screening (e.g. PEDS, ASQ-TRAK), hearing and vision checks, and social determinants of health. Some data are based on clinical observations, while others (e.g. child behaviour, feeding practices, household smoking) are reported by caregivers. Data fields are consistent across health services using the HU5K program, ensuring uniform data definitions and collection protocols. Data for all children are collated and analysed using the World Health Organisation (WHO) growth references. Clinical tools embedded in the system guide users in consistent data entry (e.g. drop-down options, mandatory fields, clinical prompts).

Data Quality (Scope): Participation rate is usually high for children who receive primary child health services through: Northern Territory Government health clinics, or Aboriginal Community Controlled Health Organisations (ACCHOs) using the Communicare clinical information system.

Data Quality (Other): Data is clinician-entered at the point of care using standardised templates, reducing free-text variation.

Data Access: Publicly available data is in the form of reports. Access to the individual-level data is governed by the NT Department of Health’s data access protocol: https://health.nt.gov.au/data-and-research/health-data/how-to-request-data-for-secondary-use

More Information: Health Under 5 Kids Program Growth and Nutrition Report - 2018: https://digitallibrary.health.nt.gov.au/nthealthserver/api/core/bitstreams/7b565ff4-4e1b-419a-9224-fba20689abbf/content

Email: child.health@nt.gov.au

Data Custodian/Owner: Northern Territory (NT) Department of Health

Source of Metadata Extraction: communicare-portal.telstrahealth.com/knowledge/V21.3/topics/hu5k_oview.html

04.07.2025

Archived on 05.12.2025: https://communicare-portal.telstrahealth.com/knowledge/V21.3/topics/hu5k_oview.html

Queensland Early Childhood Education and Care (ECEC) Services Census

Purpose: Queensland Early Childhood Education and Care (ECEC) Services Census is an annual data collection from the Queensland early childhood education and care services sector. The ECEC is used for planning and program development, monitoring outcomes of early childhood initiatives, such as kindergarten, the implementation of the National Quality Framework and reporting under the Preschool Reform Agreement.

Main Topic: Organisational characteristics

Other topics:

Demographics

Subtopics:

Service information
Kindergarten program details
Workforce information
Operational details

Included into an integrated data asset:

Population scope: All approved ECEC services operating within Queensland

Geographic scope: Queensland

Temporal range: 2013-ongoing

Temporal Unit/Frequency: Annually

Unit of Observation: ECEC service

Type of Unit of Observation: Organisation

Collection & Compilation Methods: All early childhood education and care services complete the Census, including long day care, kindergarten, family day care, outside school hours care (OSHC) and state and non-state schools that provide kindergarten programs. The reference period for 2025 is from 28 July 2025 to 3 August 2025. Services have until Sunday 17 August 2025 to complete the survey. Data collected is managed in accordance with the requirements imposed on the Department under the Education and Care Services National Law (Queensland) Act 2011 and the Information Privacy Act 2009. De-identified information obtained from the survey may be published publicly by the department, or shared with other Queensland Government agencies.

Data Quality (Scope): The census includes all approved ECEC services in Queensland (e.g. long day care, kindergarten, family day care, OSHC), ensuring comprehensive population coverage. The Census response rate generally exceeds 99%. In 2024, the census had a 100% response rate, as participation is compulsory for approved providers.

Data Quality (Other): Variables are clearly defined in official guidance documents (e.g. the Census Glossary and Data Collection Manual). Services are instructed to report data exactly as it was during the reference week. Pre-defined categories (e.g. service type, staff qualifications, child age groups) minimise reporting errors. The same variables are collected across all services each year, enabling time-series comparisons. Definitions align with national frameworks (e.g. National Quality Framework), ensuring compatibility with other datasets.

Data Access: Publicly available data is in the form of statistics: https://qed.qld.gov.au/publications/reports/statistics/early-years Detailed or unit-level data (e.g., individual child or staff records) is not publicly available due to privacy and confidentiality considerations. To access individual-level data, researchers need to contact the Department of Education and lodge a formal request.

More Information: Glossary: https://earlychildhood.qld.gov.au/sector-news-and-resources/reports-and-research/early-childhood-education-and-care-services-census/glossary

Email: census.ecec@qed.qld.gov.au

Data Custodian/Owner: Queensland Department of Education

Source of Metadata Extraction: https://earlychildhood.qld.gov.au/sector-news-and-resources/reports-and-research/early-childhood-education-and-care-services-census

07.07.2025

Archived on 05.12.2025: https://earlychildhood.qld.gov.au/sector-news-and-resources/reports-and-research/early-childhood-education-and-care-services-census

National Schools Statistics Collection (NSSC)

Purpose: The National Schools Statistics Collection (NSSC) is a census, conducted annually as a collaborative arrangement between State, Territory and Commonwealth education authorities and the ABS. Data is collected from the relevant authorities on a range of issues relating to schools, students and staff in primary and secondary schools throughout Australia, from both the government and non-government sectors.

The NNSSC exists to produce nationally consistent, annual statistics on Australian school education - counting schools, students and staff across government and non-government sectors - for policy, planning and public reporting.

Main Topic: Organisational characteristics

Other topics:

Demographics
Childcare, education, and training

Subtopics:

School types and characteristics
School workforce
Students characteristics

Included into an integrated data asset:

Population scope: Establishments which have, as their major activity, the administration and/or provision of full-time day primary, secondary or special education, or primary or secondary distance education.

Geographic scope: Australia (national)

Temporal range: 1960- onoging

Temporal Unit/Frequency: Annually

Unit of Observation: School

Type of Unit of Observation: Organisation

Collection & Compilation Methods: The NSSC is based on data collected from the national school census. The annual census is held on the first Friday in August by each state and territory education department and the non-government education systems. Data on government and non-government schools are collected from administrative school enrolment databases and collated by the ABS through the NSSC. The compilation of government sector data varies between the different state and territory departments of education. Data may be accessed from central administrative databases, sourced from education sectorial bodies or collected directly from education establishments. Data are provided to the ABS for the compilation of these statistics. Statistics for the government series include: all establishments administered by the departments of education under the director-general of education (or equivalent) in each state/territory; students attending those establishments, and all staff engaged in the administration or provision of school education at those establishments. The Australian Government Department of Education collects data for establishments in the non-government sector for all states and territories for administrative purposes. The non-government sector statistics in this publication are a summary of results from that collection. Statistics for the non-government series include: all in-scope establishments not administered by the state/territory departments of education; students attending those establishments, andall staff engaged in the administration or provision of school education at those establishments. Data for non-government establishments are reported by schools through the SchoolsHUB, which is managed by the Australian Government Department of Education. These data are then collated by the department and a subset is provided to the ABS for the NSSC. The NSSC is based on enrolment information from education administrative data systems at the time of the school census, collected in accordance with agreed national standards and definitions. For government data, each school provides and/or validates the information reflecting their enrolments to the relevant state education department. Each state and territory education department processes the data so that data forwarded to the ABS represents, or can be used to derive, student counts. Non-government data are co-ordinated through the Australian Government Department of Education. Most education authorities supply the ABS with unit record level data for students and schools, which are subsequently processed and output in aggregate format. The ABS undertakes validation of all received data prior to publication to ensure nationally comparable and historically consistent output.

Data Quality (Scope): Comprehensive coverage of all Australian schools. While schools who do not receive government funding are not obliged to report, evaluation of the 2024 NSSC identified that almost all schools are represented in the collection.

Data Quality (Other): Due to the different enrolment systems, the ability to manage multiple records of enrolment for a student may vary among jurisdictions. This may result in a small degree of over-reporting of student numbers in some jurisdictions. Some minor differences exist across jurisdictions in the interpretation of the standards applying to the collection and the ability of systems to collect data to the specifications of the collection. This may affect comparisons of school counts, student counts and student full-time equivalent values.

Data Access: Publicly available data (aggregated data): https://www.abs.gov.au/statistics/people/education/schools

To access individual-level data, researchers need to contact the ABS and lodge a formal request.

Geographic coverage: national, states and territories

More Information: https://www.abs.gov.au/methodologies/schools-methodology/2024

Data Custodian/Owner: ABS

Source of Metadata Extraction: https://www.abs.gov.au/ausstats/abs@.nsf/DOSSbyTopic/6F7111FCBD0121C0CA256BD00027255B

07.07.2025

Archived on 05.12.2025: https://www.abs.gov.au/ausstats/abs@.nsf/DOSSbyTopic/6F7111FCBD0121C0CA256BD00027255B

Criminal Courts, Australia (CCA)

Purpose: The Criminal Courts, Australia (CCA) dataset provides comprehensive national statistics on defendants whose cases were finalised in the criminal jurisdictions of the Higher (Supreme and District/County Courts), Magistrates’, and Children’s Courts across Australia’s states and territories. The data set includes information on the offences, outcomes, and sentences associated with these defendants during the reference period. The primary purpose of this data set is to offer a detailed overview of the criminal court system’s operations, facilitating analysis of trends and patterns in criminal proceedings.

Main Topic: Justice

Other topics:

Demographics

Subtopics:

Defendants
Sentences
Offence categories

Included into an integrated data asset:

Population scope: All defendants finalised in Australia’s criminal courts during the reference period

Geographic scope: Australia (national)

Temporal range: 2001- ongoing (the latest release is 2023-2024)

Temporal Unit/Frequency: Annually

Unit of Observation: Finalised defendant

Type of Unit of Observation: Individual; Organisation

Collection & Compilation Methods: The Criminal Courts, Australia (CCA) dataset is compiled by using administrative data sourced from court administration agencies across all Australian states and territories. In Queensland, data is supplied by the Office of the Government Statistician, and in New South Wales, by the Bureau of Crime Statistics and Research. Data is collected annually at the end of each financial year, covering the period from 1 July to 30 June. Offences are coded using the Australian and New Zealand Standard Offence Classification (ANZSOC) 2011. Court outcomes are coded to the Method of Finalisation classification, and penalties to the Sentence Type classification 2023. The primary counting unit is the finalised defendant. If a defendant is finalised for multiple cases on the same date and in the same court level, they are counted once. If finalised on separate dates or in different court levels, they are counted separately for each instance. Historical data may be revised due to changes in classifications or corrections in data reporting. For instance, rates have been revised from 2016–17 due to new population estimates and projections.

Data Quality (Scope): The dataset includes information on defendants (individuals or organisations) whose cases were finalised in the criminal jurisdictions of the Higher, Magistrates’, and Children’s Courts during the reference period. It excludes civil and coroners court cases, appeal cases, tribunal matters, cases not requiring adjudication of charges (e.g., bail reviews), pre-court diversionary programs, and cases finalised in specialist courts like Drug Courts.

Data Quality (Other): Variations in court processes and data systems between states and territories can affect how offences are classified; how cases are recorded and finalised; and whether certain offences or court types are included. Variables are based on standard definitions from the National Criminal Courts Data Dictionary, Version 1.0. This ensures a high level of comparability across states/territories and over time. However, some variables may not be fully consistent across jurisdictions due to local legal or administrative differences. Changes over time are noted in explanatory notes.

Data Access: Summary data is freely available on the ABS website: https://www.abs.gov.au/statistics/people/crime-and-justice/criminal-courts-australia Data downloads are available in Excel and CSV formats; interactive tables (Data Explorer); main features pages (narrative summaries); explanatory notes and technical information.

Data is available at national and state/territory levels, and sometimes by court level or offence type. Unit-level (individual defendant) microdata is not publicly available.

Researchers needing more detailed or customised data may be able to submit a request through the ABS Microdata and TableBuilder services (though Criminal Courts is not currently available as a microdata product) and/or apply for access via DataLab for restricted projects (subject to approval).

More Information: National Criminal Courts Data Dictionary: https://www.abs.gov.au/ausstats/abs@.nsf/latestproducts/AD5000DAB611D7EECA257274001726D7

Criminal Courts - latest release: https://www.abs.gov.au/statistics/people/crime-and-justice/criminal-courts-australia/latest-release

Data Custodian/Owner: ABS

Source of Metadata Extraction: https://www.abs.gov.au/statistics/people/crime-and-justice/criminal-courts-australia/latest-release

09.07.2025

Archived on 05.12.2025: https://www.abs.gov.au/statistics/people/crime-and-justice/criminal-courts-australia/latest-release

Early Childhood Education and Care National Minimum Data Set (ECEC NMDS)

Purpose: The Early Childhood Education and Care National Minimum Data Set (ECEC NMDS) has been developed to support the collection of data under the National Information Agreement on Early Childhood Education and Care (NIA ECEC). Data and information in scope of the NIA ECEC include: activity under the Preschool Reform Agreement (PRA); ECEC information required to support the information needs of other National Agreements and National Partnerships, including the National Agreement on Closing the Gap; other national reporting purposes, including but not limited to, the Report on Government Services (ROGS), Overcoming Indigenous Disadvantage, and Australia’s Children Monitoring, research and evaluation related to children, families and early childhood development services under the Early Childhood Development Strategy (ECDS).

Main Topic: Childcare, education, and training

Other topics:

Demographics
Organisational characteristics

Subtopics:

Early childhood care workforce
Enrolment and attendance
Preschool program details

Included into an integrated data asset:

Population scope: Children aged 3 to 6 years enrolled in and/or attending a preschool program

Geographic scope: Australia (national)

Temporal range: 2008- ongoing (2024 is the latest year)

Temporal Unit/Frequency: Annually

Unit of Observation: Individual child enrolled in a preschool program; service provider organisation; person employed

Type of Unit of Observation: Individual; Organisation

Collection & Compilation Methods: The NECECC is based on data collected from commonwealth and state preschool census collections. The collection date for the National Early Childhood Education and Care Collection (NECECC) is the first Friday in August of each year, with a reference period of one week in the same week as the collection date. Some jurisdictions prefer to incorporate a reference period of two weeks that includes the collection date, to better reflect their preschool program delivery model. In exceptional circumstances a different reference period may be used if agreed to by the Australian Department of Education, Skills and Employment, the jurisdiction and the Australian Bureau of Statistics. The ECEC NMDS uses two data collection methodologies: unit record level data collection and aggregate level data collection.

Data Quality (Scope): High coverage of the targeted population. However, children aged 3–6 who are not enrolled in any preschool program or only attending long day care without a preschool component and/or informal or unregulated care, as well as children outside the preschool delivery period are not included.

Data Quality (Other): Some jurisdictions, for example, WA, submit a mix of unit record and aggregate data. Annual census of all services ensures full coverage, not sampling Most variables are sourced from existing administrative systems (e.g., attendance, enrolment, qualifications). Quality relies on accurate local data systems mapped to NMDS specifications.

Data Access: The aggregated national data are published annually by the ABS as part of the National Early Childhood Education and Care Collection (NECECC) reports. These include: summmary statistics by state/territory Enrolment and attendance data; service provider types; workforce characteristics. Unit record-level data is not publicly available. Access is via ABS DataLab.

More Information: Early Childhood Education and Care DSS 2013 https://meteor.aihw.gov.au/content/494143

Email: info@mydata.abs.gov.au

Data Custodian/Owner: ABS; AIHW

Source of Metadata Extraction: https://meteor.aihw.gov.au/content/772443?operationalSpecification=True

11.07.2025

Data Over Multiple Individual Occurrences (DOMINO)

Purpose: DOMINO stands for Data Over Multiple Individual Occurrences. Established in 2017 as a data asset based on social security payments administrative data, DOMINO provides a very detailed and longitudinal view of individuals’ interactions with the welfare system to support a range of government and academic research. DOMINO captures information about people’s changing circumstances over time. Importantly, unlike the official payments data assets, the payments data in DOMINO is regularly updated and revised as further information becomes available. This makes DOMINO a highly reliable and up to date data asset.

Main Topic: Social support and welfare

Other topics:

Demographics

Subtopics:

Payment type (e.g. JobSeeker, Age Pension, Youth Allowance, Parenting Payment)
Payment start and end dates
Payment frequency and amount (where applicable)
Eligibility status and basis for entitlement
Suspension or cancellation reason
Transitions between payments
Housing assistance

Included into an integrated data asset:

NDDA
PLIDA

Population scope: All individuals who have received a Centrelink payment (e.g. JobSeeker, Age Pension, Parenting Payment); held a concession card (e.g. Health Care Card, Pensioner Concession Card); been assessed for eligibility, even if no payment was ultimately made; received Commonwealth Rent Assistance (CRA).

Geographic scope: Australia (national)

Temporal range: 2000-ongoing

Temporal Unit/Frequency: Monthly

Unit of Observation: Individual person

Type of Unit of Observation: Individual

Collection & Compilation Methods: The DOMINO (Data Over Multiple Individual Occurrences) dataset is a longitudinal, event-based administrative data asset capturing individuals’ interactions with the Australian social security system. Here’s a breakdown of its key data collection and compilation methods: DOMINO draws from Centrelink payment and service systems, tracking individuals’ payment events and eligibility changes over time. It also includes DSS-managed program and settlement data. Data is collected automatically through Services Australia’s administrative systems when individuals interact with the social security and welfare system, including: Centrelink systems (for payments and services) Department of Social Services (DSS) program databases Other supporting eligibility and concession card systems Every time an individual interacts with the welfare system (e.g. receives a payment, applies for a benefit, changes income or family status), an event record is created. These events are logged in operational systems and periodically extracted by DSS for use in the DOMINO dataset.

Data Quality (Scope): Full population coverage of people who interact with the Australian social security system, primarily through Centerlink

Data Quality (Other): Variables (e.g. payment type, start/end dates, concession card eligibility) are directly extracted from Centrelink’s transaction systems. Some variables (e.g. Indigenous status, country of birth) may be incompletely reported or based on self-declaration during Centrelink registration.

Data Access: Some data is available in the form of the research publications, for example: https://www.ahuri.edu.au/sites/default/files/migration/documents/AHURI-Final-Report-351-The-utility-of-new-data-in-understanding-housing-insecurity.pdf For individual level data access, applicants will need to submit all relevant documentation for review by the AIHW. Consideration will then be given by DSS to issuing a Public Interest Certificate that will enable researchers to access the data. Please note that access to the dataset is currently provided via the Sax Institute’s Secure Unified Research Environment (SURE). Locations provided: state and territory, ABS Statistical Areas (SA1), Local Government Areas (LGA)

More Information: Catalogue: https://dss.aristotlecloud.io/item/89008/datacatalog/domino-externally-available-data-catalogue https://dss.aristotlecloud.io/item/54038/datacatalog/domino-datasets-catalogue

Access via SHORE, variables list: https://www.aihw.gov.au/about-our-data/accessing-australian-government-data/dss-data

Email: domino.dataset@aihw.gov.au

Data Custodian/Owner: DSS

Source of Metadata Extraction: https://dss.aristotlecloud.io/item/1942/dataset/domino-external-analytical-version?#

14.07.2025

Archived on 05.12.2025: https://dss.aristotlecloud.io/item/1942/dataset/domino-external-analytical-version?#

Indigenous Community Housing data collection (ICH)

Purpose: The primary purpose of the Indigenous Community Housing data collection (ICH) is to capture information about ICH organisations (ICHOs), the dwellings they manage, and tenants assisted.

Main Topic: Housing and homelessness

Other topics:

Demographics

Subtopics:

Housing organisation
Dwellings managed by ICHOs
Tenants assisted

Included into an integrated data asset:

Population scope: All dwellings and associated households managed by Indigenous Community Housing Organisations (ICHOs) across Australia that: Receive government funding, or Report through state and territory housing authorities as part of the ICH data collection.

Geographic scope: Australia (national)

Temporal range: 2003-ongoing (2024 is the most recent one)

Temporal Unit/Frequency: Point-in-time/Annually

Unit of Observation: Dwelling, household, organisation

Type of Unit of Observation: Object; Household; Organisation

Collection & Compilation Methods: ICHOs include community organisations such as resource agencies and land councils, which may have a range of functions, however, are included in ICH provided that they manage housing for Indigenous people. ICHOs may either directly manage the dwellings they own or sublease tenancy management services to the relevant state/territory housing department or another organisation. Since 2003–04, the Australian Institute of Health and Welfare (AIHW) has compiled ICH data from state and territory housing departments on an annual basis. These data help to describe the performance of Indigenous housing programs. The data collection has evolved over time, including changes to the data collection scope, procedures, data items and underlying definitions and concepts.

Data Quality (Scope): Inclusions: dwellings that are targeted to Indigenous people and ICHOs that provide medium- to long-term housing tenure to tenants.

Excludes dwellings: managed under Community Housing, Public Housing, State Owned and Managed Indigenous Housing, or the Crisis Accommodation Program no longer under the administration of an ICHO at 30 June of the reference year (including dwellings demolished, sold or otherwise disposed of) not yet available to the ICHO at 30 June of the reference year (such as those still under construction or being purchased). Apart from the following, the data collection focuses on dwellings managed by funded ICHOs only (for NSW, this means excluding not actively registered ICHOs): Number of permanent dwellings managed by funded and unfunded organisations at 30 June Number of funded and unfunded ICHOs at 30 June.

Data Quality (Other): Variables to support reporting and linkage: age (date of birth), sex/gender, rent assistance. However, some of these variables may be incomplete or missing. Not all states and territories or organisations capture and report all data items, leading to incomplete data in some cases. Data for individual states and territories may not be comparable across reporting periods or with other social housing sectors due to changes in systems and processes The data collection focuses on dwellings managed by funded ICHOs, excluding those managed under Community Housing, Public Housing, State Owned and Managed Indigenous Housing, or the Crisis Accommodation Program There is no ICH program in the ACT.

Data Access: Publicly availabe data include summary tables published in electronic form; statistics. Client specified tables are provided on request which may be subject to data provider approval (charges apply).

Restricted unit record access subject to Ethics Committee approval and/or the agreement of all relevant data custodians in all states and territories (charges may apply).

There are restrictions and limitations governing the availability or use of other data in this holding.

Geographical coverage: national and state/territory.

More Information: Indigenous Community Housing DSS 2018: https://meteor.aihw.gov.au/content/711226

Housing assistance: https://www.aihw.gov.au/reports/housing-assistance/housing-assistance-in-australia/contents/overview https://www.aihw.gov.au/about-our-data/our-data-collections/national-social-housing-survey

Data Custodian/Owner: AIHW

Source of Metadata Extraction: https://www.aihw.gov.au/about-our-data/our-data-collections/indigenous-community-housing

11.06.2025

Public Housing and State-owned and Managed Indigenous Housing Data Collections (PH and SOMIH)

Purpose: The primary purposes of the PH and SOMIH data collections are to monitor and evaluate the performance and effectiveness of public housing and SOMIH programs; inform policy development and strategic planning at both national and state/territory levels; support research and analysis on housing assistance, particularly for Indigenous populations; provide data for reporting to stakeholders, including government agencies and the public.

Main Topic: Housing and homelessness

Other topics:

Demographics
Employment, income, taxation, wealth, and consumption

Subtopics:

Dwelling information
Tenant and household characteristics
Housing conditions
Tenancy details
Information about programs
Household income

Included into an integrated data asset:

Population scope: PH and SOMIH dwellings and households residing in PH and SOMIH dwelling where the dwelling is: owned by the housing authority; leased from the private sector or other housing program areas and used for provision of PH and SOMIH programs.

Geographic scope: Australia (national)

Temporal range: 1995-ongoing

Temporal Unit/Frequency: Annually

Unit of Observation: Household, dwelling, person

Type of Unit of Observation: Individual; Household; Dwelling

Collection & Compilation Methods: The data collection encompasses information on dwellings, such as information on the number, type, and location of dwellings managed under PH and SOMIH programs; tenants and households, including demographic details such as age, sex, Indigenous status, household composition, and income levels; and tenancy details such as tenancy commencements, durations, rent charged, and occupancy status. SOMIH programs operate in specific jurisdictions, including New South Wales, Queensland, South Australia, Tasmania, and the Northern Territory. State and territory housing authorities extract relevant data from their administrative systems based on the NMDS specifications. The extracted data undergo validation checks to ensure accuracy, consistency, and completeness. Validated data are then submitted to the AIHW through secure data transfer protocols. The AIHW standardises and compiles these submissions into national datasets, applying consistent coding and classification systems to facilitate comparability across jurisdictions.

Data Quality (Scope): Excludes dwelling leased to other programs (e.g., community housing, crisis accommodation); dwellings no longer under housing authority administration at 30 June (e.g., demolished, sold); dwellings not yet available to housing authorities at 30 June (e.g., under construction).

Data Quality (Other): Not all states and territories capture all data items. Indigenous status is self-identified and not reported under eligibility requirements in some jurisdictions. Variations in data collection and reporting practices among states and territories may affect the uniformity of the PH and SOMIH datasets. Each jurisdiction manages their own housing systems which may differ in platforms and protocols. Some jurisdictions may also update tenant income data more frequently than others. There could be some missing data, out-of-data data and data coding or recording errors. Coherence over time has also been affected by changes in methodology

Restricted unit record access subject to Ethics Committee approval and/or the agreement of all relevant data custodians in all states and territories (charges may apply).

There are restrictions and limitations governing the availability or use of other data in this holding.

Geographical coverage: national and state/territory.

More Information: Quality statement: https://meteor.aihw.gov.au/content/788968

Clearinghouse https://www.aihw.gov.au/about-our-data/our-data-collections/national-aged-care-data-clearinghouse https://www.aihw.gov.au/about-our-data/our-data-collections/extended-aged-care-at-home-each-census

Data Custodian/Owner: AIHW

Source of Metadata Extraction: https://www.aihw.gov.au/about-our-data/our-data-collections/ph-somih-data-collections

11.06.2025

Aged Care National Minimum Data Set (ACNMDS)

Purpose: The purpose of the Aged Care NMDS is to improve data quality, comparability and usefulness of data collected across the aged care sector. This means that data must be collected in accordance with the NMDS data specifications at the point of care, capture or record creation (as applicable). In scope is aged care - which includes both care and assessments - that is funded by the Australian Government.

Main Topic: Community services

Other topics:

Demographics
Health

Subtopics:

Primary health conditions
Comorbidities
Dementia
Functional status
Aged care service type
Service start and exit dates
Service provider information
Aged care assessments
Service utilisation and outcomes

Included into an integrated data asset:

NACDA (as a component of the National Aged Care Data Clearinghouse (NACDC))

Population scope: Persons registered in the aged care system – people going through an aged-care related assessment process or currently using government-funded aged care services

Geographic scope: Australia (national)

Temporal range: 2023-ongoing

Temporal Unit/Frequency: Annually

Unit of Observation: Individual person, aged care provider, aged care services, aged care assessments

Type of Unit of Observation: Individual; Organisation; Event

Collection & Compilation Methods: Aged care includes community-based (or in-home) aged care and residential aged care services. As of June 2023, this consists of the following programs: • Commonwealth Home Support Program; • Home Care Packages Program; • Residential aged care (permanent); • Residential aged care (respite); • Transition Care Program; • Short-Term Restorative Care Program; • National Flexible Aboriginal and Torres Strait Islander Flexible Aged Care Program; • Multi-Purpose Services. The Aged Care NMDS data specifications are applicable to all aged care-related data, whether it is administrative, census or survey. The Aged Care NMDS data are generally: collected by a provider, service/facility or assessor, reported to government and collated by government. The data are then forwarded to the AIHW National Aged Care Data Clearinghouse for public dissemination via the AIHW’s dedicated aged care data website GEN and other platforms, as well as made available for research, analysis and data integration. The Aged Care NMDS will be developed progressively, with content added over time. Items included in the first version (as at 30 June 2023) have been established through consultation with a range of stakeholders, including the aged care sector. They represent a minimum set of core data items (or, data elements) where consistent collection is needed and where standards can feasibly be progressed and implemented.

Data Quality (Scope): The dataset includes: All individuals who undergo an aged care assessment (via Aged Care Assessment Teams – ACATs); All individuals who receive Australian Government-subsidised aged care services, including: residential aged care; home care packages; flexible care (e.g. Transition Care Program, Multi-Purpose Services). It covers all Commonwealth-funded aged care services, excludes non-subsidised aged care services.

Data Quality (Other): Data are collected annually and reflect aged care services provided during each financial year. Most key data elements (e.g. assessment dates, service use, demographics) are routinely and comprehensively completed. However, some variables may have lower completeness, particularly optional fields or fields affected by changes in reporting practices. Jurisdictional differences in reporting may introduce inconsistencies. Recently introduced fields, e.g. gender identity may be incompletely reported.

Data Access: Summary statistics and reports are available on the About GEN website: https://www.gen-agedcaredata.gov.au/ Researchers can request customised data tables tailored to specific research needs. Access to de-identified individual-level data is available under strict conditions. Researchers will need to prepare a detailed proposal outlining research objectives, data requirements, and methodologies, obtain ethics approval and contact AIHW to initiate the data request process. Upon approval, access will be granted through a secure environment.

Geographical coverage: states, territories

More Information: https://www.gen-agedcaredata.gov.au/

Email: info@aihw.gov.au

Data Custodian/Owner: AIHW

Source of Metadata Extraction: https://meteor.aihw.gov.au/content/774715

06.06.2025

Australian Government housing data set (AGHDS)

Purpose: The primary purpose of the AGHDS is to support national reporting and policy development related to housing assistance, particularly Commonwealth Rent Assistance (CRA). The AGHDS includes information about the type of housing, amount of weekly income, payment type, and other characteristics of income units. This data is crucial for understanding the characteristics of households receiving government assistance and for informing housing policy and programs.

Main Topic: Housing and homelessness

Other topics:

Demographics
Employment, income, taxation, wealth, and consumption

Subtopics:

Housing assistance
Rent paid
Rent affordability
Type of income support payments
Family Tax Benefit (Part A)
Total government support received
Gross and assessable income
Income unit type

Included into an integrated data asset:

Population scope: The AGHDS encompasses: income units receiving Centrelink social security payments; families receiving Family Tax Benefit (FTB) Part A

Geographic scope: Australia (national)

Temporal range: 2006- ongoing (2024 – the most recent)

Temporal Unit/Frequency: Point-on-time/Annually

Unit of Observation: Income unit

Type of Unit of Observation: Group

Collection & Compilation Methods: The Australian Government housing data set (AGHDS) is a confidentialised unit record file that provides point in time data for income units in receipt of Centrelink social security payments and families receiving Family Tax Benefit (FTB) Part A. The AGHDS is derived from administrative data provided by the Department of Social Services (DSS) to the AIHW. It combines information from various Centrelink files to create records at the income unit level, which includes a person, their partner, and any children for whom the couple may receive FTB Part A. Data are compiled as point-in-time snapshots, with temporal coverage shown as 30 June each year.

Data Quality (Scope): Combines information from numerous Centrelink files to create records at an income unit level, rather than person or household level. An income unit consists of a person, the person’s partner, and any children for whom the couple may receive FTB Part A. Single social security recipients living together in the same household are regarded as separate income units. One person in each income unit is classified as the primary reference person based on sex and the type of payment received. Income sharing is assumed to take place within married (registered or de facto) couples, and between parents and dependent children. Includes information about type of housing, amount of weekly income, payment type and other characteristics of income units. Overall, high coverage of people receiving housing-related income support, however does not cover the general population, only people receiving Centrelink payments.

Data Quality (Other): Variable names/definitions align with AIHW metadata standards.

Data Access: Publications: Housing assistance Reports - Australian Institute of Health and Welfare Data tables: Housing assistance Data - Australian Institute of Health and Welfare Restricted unit record access subject to Ethics Committee approval and/or the agreement of all relevant data custodians in all states and territories (charges may apply). There are restrictions and limitations governing the availability or use of other data in this holding. Geographical coverage: states, territories, SA2

More Information: Housing assistance report https://www.aihw.gov.au/reports/housing-assistance/housing-assistance-in-australia/contents/about https://www.aihw.gov.au/reports-data/health-welfare-services/housing-assistance/overview https://www.aihw.gov.au/reports-data/health-welfare-services/housing-assistance/resources

A data dictionary is available upon request.

Glossary: https://www.aihw.gov.au/reports/alcohol-other-drug-treatment-services/alcohol-other-drug-treatment-services-glossary

Data Custodian/Owner: AIHW

Source of Metadata Extraction: https://www.aihw.gov.au/about-our-data/our-data-collections/australian-government-housing-data-set

16.06.2025

Alcohol and Other Drug Treatment Services National Minimum Data Set (AODTS NMDS)

Purpose: The AODTS NMDS, maintained by the Australian Institute of Health and Welfare (AIHW), is designed to collect nationally consistent information about alcohol and other drug (AOD) treatment services across Australia. Its primary purpose is to inform policy, planning, research, and service delivery related to alcohol and other drug treatment in Australia by providing comprehensive, standardised, and reliable data on: who receives AOD treatment; why they seek treatment, what types of treatment are provided, and where and by whom the services are delivered.

Main Topic: Health

Other topics:

Demographics

Subtopics:

Treatment episode details
Treatment type
Episode start and end dates
Reason for cessation
Substance use information
Service provider information

Included into an integrated data asset:

Population scope: Clients of publicly funded AOD treatment services in Australia aged 10 and older at the time of their first treatment episode

Geographic scope: Australia (national)

Temporal range: 2000-ongoing

Temporal Unit/Frequency: Annually

Unit of Observation: Individual, treatment episode, service provider

Type of Unit of Observation: Individual; Event/Process/Activity; Organisation

Collection & Compilation Methods: AODTS NMDS includes data from government-funded and some non-government AOD treatment services; services funded by state/territory governments, the Australian Government, or Primary Health Networks (PHNs). Agencies submit data in CSV format, with each row representing a single treatment episode. Submissions are made through the AIHW’s Validata™ tool, which performs automated data quality checks. Each client is assigned a Statistical Linkage Key (SLK-581) to enable de-identified tracking across services and over time.

Data Quality (Scope): High national coverage for government publicly funded alcohol and other drug treatment specialist services, uses standardised data elements. Although the AODTS NMDS collection covers the majority of publicly funded AOD treatment services, including government and non-government organisations, it is difficult to fully quantify the scope of AOD services in Australia and quantification does not provide a complete picture.

Data Quality (Other): The dataset does not not include private treatment services or services not funded by government. Some optional fields (e.g. method of drug use, referral source) may have incomplete reporting. Needle and syringe programs (NSPs) and prison-based programs often excluded. Clients with age missing are excluded. Clients receiving treatment for others’ AOD use excluded. Episodes where alcohol was at any point reported were included, split into two categories: alcohol only and alcohol as well as other principal drugs of concern (amphetamines, cannabis, heroin, pharmaceuticals).

Data Access: Publicly available data includes publications, data cubes (cover the period 2003-04 to 2023-24), summary tables published in electronic form and statistics.

Publication: https://www.aihw.gov.au/reports/alcohol-other-drug-treatment-services/alcohol-treatment-2013-23/contents/about Data cubes on closed treatmet episodes and profile of drug treatment agencies can be found here: https://www.aihw.gov.au/reports/alcohol-other-drug-treatment-services/alcohol-other-drug-treatment-services-aus/contents/data-cubes

Client specified tables on request which may be subject to data provider approval.

Restricted unit record access subject to Ethics Committee approval and/or the agreement of all relevant data custodians in all states and territories (charges may apply).

Geographical coverage: national, state and territory, SA4, SA3, SA2, postcode

More Information: AODTS cube metadata: https://meteor.aihw.gov.au/content/756056

About Validata (AIHW tool which ensures that receipt and storage of data meets appropriate data quality standards: https://www.aihw.gov.au/our-services/validata

Clients are identified using a statistical linkage key (SLK-581). https://www.aihw.gov.au/getmedia/875673aa-2eba-48f2-a9d6-6a9ffebdcffc/aihw-aodts-nmds-slk-581-guide-for-use-2023-24_2.pdf

Email: aod@aihw.gov.au

Data Custodian/Owner: AIHW

Source of Metadata Extraction: https://www.aihw.gov.au/about-our-data/our-data-collections/alcohol-other-drug-treatment-services

09.06.2025

Community Housing data collection (CH)

Purpose: The Community Housing (CH) data collection captures information about CH organisations, the dwellings they manage and the tenants assisted. It is complied to provide a single, comparable national view of the community housing program for planning, performance reporting and public statistics (e.g., AIHW’s Housing assistance in Australia).

Main Topic: Housing and homelessness

Other topics:

Demographics
Organisational characteristics

Subtopics:

Dwelling types
Dwelling ownership type
Ownership/leasing
Subsidy models
Jurisdictional participation of CHs

Included into an integrated data asset:

Population scope: Tenants and Households including individuals or households living in community housing dwellings, typically low- to moderate-income people or those with special needs; people assisted by registered community housing providers, excluding public housing and crisis accommodation. Rental housing owned or managed by community-based, not-for-profit organisations.

Geographic scope: Australia (national)

Temporal range: 1996- ongoing (the latest is 2024)

Temporal Unit/Frequency: Annually

Unit of Observation: Tenancy unit; household; community housing organisation

Type of Unit of Observation: Group; Household; Organisation

Collection & Compilation Methods: The data are supplied by state and territory housing departments on an annual basis. Data is collected via a survey of community housing providers and forwarded to state or territory housing authorities. Data is also sourced from administrative records held by state/territory housing authorities.

The data collection has evolved over time. Changes have occurred to data collection scope, procedures, data items and underlying definitions and concepts.

All states and territories provide the AIHW with community housing data from their administrative systems. Additionally, unit record community housing data are collected from CHOs via an Excel tool managed by the AIHW.

In New South Wales, data are collected from CHOs quarterly via a cloud-based tool managed by the Department of Communities and Justice. The Northern Territory does not use the AIHW-managed tool and does not provide any unit record household data. New South Wales, Victoria, Western Australia, South Australia, Tasmania, and the Australian Capital Territory supply unit record level data, including details on individuals, organisations, dwellings, and associated tenancies. Queensland provides aggregate data supplemented by unit record administrative data for funded organisations, properties, and current waitlist applications.

Care is required when comparing outputs across states and territories. Differences in the data collected, including which records are included or excluded from a calculation can affect the coherence of the outputs.

Data Quality (Scope): CH includes tenancy (rental) units under management of a CH organisation, excluding Indigenous CH organisations. CH excludes dwellings: where the tenancy is managed under: Public Housing; State and Territory Owned and Managed Indigenous Housing; Indigenous CH; or the Crisis Accommodation Program; no longer administered by a CH organisation at 30 June of the reference financial year (including dwellings demolished, sold or otherwise disposed of); not yet available to CH organisations at 30 June of the reference financial year (e.g. under construction or being purchased).

Data Quality (Other): Variables to support reporting and linkage include: age (date of birth, sex/gender, Indigenous status). Additional jurisdiction-specific inclusions and exclusions reflect: different definitions of CH in legislation; difficulties in identifying some organisations e.g. those not registered or funded by the state/ territory housing authority; inconsistencies in reporting e.g. inclusion of transitional housing and National Rental Affordability Scheme dwellings owned or managed by CH organisations. Coherence over time has been affected by changes in methodology. Data are incomplete for some jurisdictions due to non/under-reporting by CH organisations.

Data Access: • Publications • Summary tables published in electronic form • Statistics Client specified tables on request which may be subject to data provider approval (charges apply). Restricted unit record access subject to Ethics Committee approval and/or the agreement of all relevant data custodians in all states and territories (charges may apply). There are restrictions and limitations governing the availability or use of other data in this holding.

More Information: Community housing is rental housing for low- to moderate-income or special-needs households. It is managed by community-based organisations that lease properties from government or have received a capital or a recurrent subsidy from government. CH models vary across states and territories, and the housing stock may be owned by a variety of groups including government.

Community Housing DSS 2018- https://meteor.aihw.gov.au/content/710899

Community Housing Data Collection, 2023–24; Quality Statement: https://meteor.aihw.gov.au/content/788964

Housing assistance: https://www.aihw.gov.au/reports-data/health-welfare-services/housing-assistance/overview

Report on government services (housing): https://www.pc.gov.au/ongoing/report-on-government-services/2025/housing-and-homelessness/housing

Resources: https://www.aihw.gov.au/about-our-data/our-data-collections/home-purchase-assistance https://www.aihw.gov.au/reports/housing-assistance/housing-assistance-in-australia/contents/overview https://www.aihw.gov.au/reports/australias-welfare/australias-welfare-overview

Data Custodian/Owner: AIHW

Source of Metadata Extraction: https://www.aihw.gov.au/about-our-data/our-data-collections/community-housing

18.06.2025

Child Protection National Minimum Data Set (CPNMDS)

Purpose: The purpose of the Child Protection National Minimum Data Set (CP NMDS) is to provide a nationally consistent framework for collecting, reporting, and analysing data on children and young people who come into contact with child protection systems across Australia.

Main Topic: Justice

Other topics:

Demographics

Subtopics:

Care and protection orders
Out-of-home care
Child’s living arrangements
Type of abuse or neglect
Investigations
Interventions

Included into an integrated data asset:

CWDA

Population scope: Children and young people aged 0–17 years who are the subject of a child protection notification (report of suspected abuse, neglect, or harm); are the subject of a substantiated investigation; are placed on a care and protection order; are placed in out-of-home care as part of child protection intervention.

Geographic scope: Australia (national)

Temporal range: 2012-ongoing (2021-2022 is the latest)

Temporal Unit/Frequency: Annually

Unit of Observation: Child, notification, investigation, protection order, out-of-home care episode

Type of Unit of Observation: Individual; Organisation; Event/Process/Activity

Collection & Compilation Methods: The Child Protection National Minimum Data Set (CP NMDS) is an annual collection of information on child protection in Australia. The collection is a part of the child welfare series of reporting. It contains data on children who come into contact with State and Territory departments responsible for child protection. The data for this collection are collected from each of the eight state and territory departments responsible for child protection.

The CP NMDS consists of the following data files: client demographics, notifications, investigations and substantiations, care and protection orders, living arrangements, including children in funded out-of-home care, carer households, data for reporting on National Out-of-Home Care Standards measures, and safety in care.

The CP NMDS collection was implemented in 2012–13. Prior to that a national aggregate child protection data collection was used for national child protection reporting (data for this collection began in 1990–91).

The AIHW compiles data for the CP NMDS each year using data extracted from the administrative systems of the state and territory departments responsible for child protection. These state and territory departments are the: Department of Families, Fairness and Housing, Victoria; Department of Children, Youth Justice and Multicultural Affairs, Queensland; Department of Communities, Western Australia; Department for Child Protection, South Australia; Department of Communities, Tasmania; Community Services Directorate, Australian Capital Territory; Department of Territory Families, Housing and Communities, Northern Territory.

These data are then supplied to the AIHW as unit record (event-level and child-level) files and forms the basis of the CP NMDS. Data represent a ‘snapshot’ of the data at the time of extraction and may not include retrospective updates made to data held by state/territory departments.

Data produced from the CP NMDS are based on nationally agreed specifications and may not match state and territory figures published elsewhere and may not be comparable with data for previous years.

Data Quality (Scope): Child protection notifications, investigations and substantiations; care and protection orders; living arrangements, including children in funded out-of-home care; carer households; national out-of-home care standards; sibling relationships; safety in care. The dataset excludes children reported to non-statutory family support services without subsequent formal child protection involvement. The dataset excludes informal support services and voluntary referrals that are not subject to statutory child protection processes.

Data Quality (Other): The dataset contains both individual-level data and event-level data across several domains: Demographic characteristics; Types and sources of abuse/neglect reported; Legal and procedural outcomes (e.g. orders); Placement settings for out-of-home care; Service and care timelines (entry/exit dates).

Variables to support reporting and linkage: age (date of birth); sex/gender; Indigenous status; Statistical Linkage Key.

Data Access: Data available in the following formats: publications – these data include national and jurisdictional counts of notifications, substantiations, care and protection orders, out-of-home care placements; summary tables published in electronic form; client specified tables on request which may be subject to data provider approval (charges may apply).

Restricted unit record access subject to Ethics Committee approval and/or the agreement of all relevant data custodians in all states and territories (charges may apply).

Geographical coverage: national and states and territories

More Information: Child protection: https://www.aihw.gov.au/reports-data/health-welfare-services/child-protection/overview

Child protection NMDS 2021-22 – metadata information https://meteor.aihw.gov.au/content/773440

Child protection – glossary: https://www.aihw.gov.au/reports-data/health-welfare-services/child-protection/glossary

Email: child.protection@aihw.gov.au

Data Custodian/Owner: AIHW

Source of Metadata Extraction: https://www.aihw.gov.au/about-our-data/our-data-collections/child-protection-national-minimum-data-set

06.06.2025

Home Purchase Assistance data collection (HPA)

Purpose: The primary purpose of the HPA data collection is to capture information about the recipients of HPA and instances of HPA assistance.The data help to describe the performance of the current National Housing and Homelessness Agreement and the former National Affordable Housing Agreement and Commonwealth-State Housing Agreement.

Main Topic: Housing and homelessness

Other topics:

Demographics
Employment, income, taxation, wealth, and consumption

Subtopics:

Gross weekly income Number of households assisted Value of assistance Outstanding repayments Arrears and bad debts HPA program performance and outcomes

Included into an integrated data asset:

Population scope: Households that received financial assistance under HPA programs administered by state and territory housing authorities.

Geographic scope: Australia (national)

Temporal range: 1997-ongoing (30.06.2024- the most recent)

Temporal Unit/Frequency: Annually

Unit of Observation: Household

Type of Unit of Observation: Household

Collection & Compilation Methods: HPA is administered by each state/territory housing authority and provides a range of financial assistance to eligible households to improve their access to, and maintain, home ownership.

Since 1997–98, the Australian Institute of Health and Welfare (AIHW) has compiled HPA data from states and territories on an annual basis. The data collection has evolved over time, with changes to the data collection scope, procedures, data items collected and underlying definitions and concepts.

State and territory housing authorities provide the data to the AIHW for national collection, on an annual basis. The reference period starts on 1 July and ends on 30 June each financial year. Data collection for each HPA data set specification reference period includes records of assistance to households that: commenced receiving assistance in the current reference period; commenced receiving an ongoing form of assistance in a previous financial year and continued to receive this assistance in the current reference period; received a repayable form of assistance in a previous financial year for which repayable monies remained outstanding at the commencement of the current reference period.

Data qualifications: A separate record should be reported for each type of assistance provided to a household. A single record should be reported for each type of ongoing assistance provided to a household in the reference period, regardless of which financial year assistance commenced. For households that had monies outstanding on repayable assistance provided in a previous financial year and received no new assistance in the current reference period, the amount of assistance should be left blank, but the type of assistance received, payment type, and date assistance received should be reported.

Data Quality (Scope): Data scope includes: direct lending (including government loans, shared equity loans and bridging loans); deposit assistance; interest rate assistance; mortgage relief; other assistance grants. Excludes: non-financial assistance, for example home purchase advisory and counselling services; home renovation and/or maintenance services; relocation or start up assistance; sale to tenant programs; provision of housing or any share of it; expense incurred in providing assistance to a household that is not the value of financial assistance directly received by the household; any aspect of a shared equity loan that is not direct lending, deposit assistance, interest rate assistance or mortgage relief; any assistance not provided expressly for purchasing a home.

Data Quality (Other): Limited demographic detail. Variables to support reporting and linkage include age (date of birth); sex/gender; Indigenous status of primary applicant only.

While data collected from state/territory housing authorities are typically accurate for financial transactions and program eligibility, they are not nationally uniform because each jurisdiction runs their own HPA programs.

Data Access: Publicly available data include publications, summary tables published in electronic form, statistics.

Client specified tables on request which may be subject to data provider approval (charges apply).

Restricted unit record access subject to Ethics Committee approval and/or the agreement of all relevant data custodians in all states and territories (charges may apply). There are restrictions and limitations governing the availability or use of other data in this holding.

Geographical coverage: states, territories

More Information: Home purchase assistance DSS 2013- https://meteor.aihw.gov.au/content/596710

Data Custodian/Owner: AIHW

Source of Metadata Extraction: https://www.aihw.gov.au/about-our-data/our-data-collections/home-purchase-assistance

16.06.2025

National Hospitals Data Collection (NHDC)

Purpose: The National Hospitals Data Collection (NHDC) serves to compile comprehensive, standardised data on hospital services across Australia. Its primary purpose is to support national health reporting, policy development, service planning, and research by providing detailed information on hospital activities and resources.

Main Topic: Health

Other topics:

Demographics

Subtopics:

Hospital activity Clinical information Hospital resources and infrastructure Elective surgery Health system performance

Included into an integrated data asset:

COVID-19 Register
NACDA
NDDA
NHDH

Population scope: All admitted patient episodes from public and private hospitals across Australia. Individuals admitted to hospitals for inpatient care, including day admissions.

Geographic scope: Australia (national)

Temporal range: 1993-ongoing

Temporal Unit/Frequency: Annually

Unit of Observation: Individual, admitted patient episode, ED presentation, waiting list entry, non-admitted service event, hospital establishment

Type of Unit of Observation: Individual; Event/Process/Activity; Organisation

Collection & Compilation Methods: The National Hospitals data collection includes the major national hospitals databases held by the Australian Institute of Health and Welfare (AIHW), including: The National Hospital Morbidity Database (NHMD), a compilation of episode-level records from admitted patient morbidity data collection systems in Australian public and private hospitals; The National Public Hospital Establishments Database (NPHED), which holds information on public hospital resources and includes information reported for public hospitals, Local hospital networks (LHNs) and state and territory health authorities; The National Non-Admitted Patient Emergency Department Care Database (NNAPEDCD), a compilation of episode-level records (including waiting times for care) for non-admitted patients registered for care in emergency departments in selected public hospitals; The National Elective Surgery Waiting Times Data Collection (NESWTDC), which holds episode-level information on patients added to or removed from elective surgery waiting lists managed by public hospitals; The National Non-Admitted Patient Care (aggregate) Database (NNAP(agg)D), which holds clinic-level information on non-admitted patient care provided by public hospitals, LHNs and selected other public hospital services managed by state and territory health authorities; The National Non-admitted Patient (episode-level) Database (NNAP(el)D), which holds episode-level information on non-admitted patient care provided by public hospitals, LHNs and selected other public hospital services managed by state and territory health authorities; 1/1/2011–30/6/2013: The National Emergency Access Target Database (NEATD) is a compilation of electronic records of non-admitted patient service episodes for the purposes of reporting the National Emergency Access Targets as part of the National Partnership Agreement on Improving Public Hospital Services; 1/1/2011–30/6/2015: The National Elective Surgery Targets Database (NESTD) is census and removal elective surgery waiting list entries for the purposes of reporting the National Elective Surgery Targets as part of the National Partnership Agreement on Improving Public Hospital Services; 2005–2013: National collection of occasions of service provided in outpatient clinics of public hospitals that are classified as either principal referral and specialist women’s and children’s hospitals and large hospitals (Peer Group A or B) as reported in the Australian Institute of Health and Welfare’s Australian Hospital Statistics publication from the preceding financial year.

Hospitals (both public and private) collect data on patient care episodes, including demographics, diagnoses, procedures, and service details. State and territory health authorities aggregate data from their respective hospitals, ensuring adherence to national data standards. The complied data is submitted to the AIHW, where it is integrated into national databases.

Data Quality (Scope): The NHDC encompasses a broad range of hospital-related data, with the scope varying by dataset.

Data Quality (Other): Differences in data collection and reporting practices across jurisdictions may affect data comparability. Some variables, e.g. Indigenous status, can be under-reported and misclassified. Variability in clinical coding practices and the use of different editions of the International Classification of Diseases (ICD) can affect the consistency of diagnosis and procedure data. Variations in emergency department admission practices and the types of services provided can lead to inconsistencies in non-admitted patient data. Differences in the recording and reporting of non-admitted patient services, including outpatient care, can result in data inconsistencies. Inconsistencies in recording the funding source for hospital separations, particularly in private hospitals.

Data Access: Data is available in the form of publications, summary tables published in electronic form and statistics.

Data cubes have been archived and no longer available.

Restricted unit record access subject to Ethics Committee approval and/or the agreement of all relevant data custodians in all states and territories (charges may apply).

Individual level data can be requested by using the Data on request form: https://www.aihw.gov.au/about-our-data/accessing-data-through-the-aihw/data-on-request

Geographical coverage: national, state and territory, SA1, SA2

More Information: Data for this collection are published regularly in the Australian hospital statistics suite of publications and related products. While the temporal range for this dataset is 1993-201, the most recent updates on patient and non-patient care are dated 2023-2024: https://www.aihw.gov.au/reports-data/myhospitals

Each dataset in this collection has specific inclusion criteria and data elements, detailed in the respective National Minimum Data Set (NMDS) specifications available through METEOR. https://meteor.aihw.gov.au/content/344846

Data Custodian/Owner: AIHW

Source of Metadata Extraction: https://www.aihw.gov.au/about-our-data/our-data-collections/national-hospitals-data-collection

10.06.2025

Private Rent Assistance Data Collection (PRA)

Purpose: The Private Rent Assistance (PRA) data collection captures information about the recipients of PRA and instances of PRA assistance. The Private Rent Assistance (PRA) data collection exists to produce nationally comparable statistics on state/territory programs that help low-income households access or keep accommodation in the private rental market. The purpose is to inform monitoring, reporting and policy about this type of financial assistance across Australia.

Main Topic: Housing and homelessness

Other topics:

Demographics
Organisational characteristics

Subtopics:

Assistance type
Assistance date
Number of episodes per financial year
Housing situation prior seeking assistance
Primary reason for seeking assistance
Risk types

Included into an integrated data asset:

Population scope: People who received financial private rental support from state or territory governments in a given financial year.

Geographic scope: Australia (national)

Temporal range: 1997- ongoing (the latest is 2024)

Temporal Unit/Frequency: Annually

Unit of Observation: A private rent assistance instance provided to an individual or household within a financial year

Type of Unit of Observation: Event/Process/Activity

Collection & Compilation Methods: State and territory housing authorities provide the data to the Australian Institute of Health and Welfare (AIHW) for national collection, on an annual basis.

The reference period starts on 1 July and ends on 30 June each financial year. Data collection for each PRA DSS reference period includes records of assistance to households that: commenced receiving assistance in the reference period; commenced receiving an ongoing form of assistance in a previous financial year and continued to receive this assistance in the current reference period; received a repayable form of assistance in a previous financial year for which repayable monies remained outstanding at the commencement of the current reference period.

Data Quality (Scope): The PRA defines information relating to the provision of financial assistance to enable households to access and maintain accommodation in the private rental market and includes: bond loans, rental grants, rental subsidies, relocation expenses, and other assistance grants. The PRA excludes: non-financial assistance, for example, tenancy support services and tenancy guarantees, and any expense incurred in providing assistance to a household that is not the value of financial assistance received directly by the household (e.g. related administrative and operational costs associated with providing the private rent assistance).

Data Quality (Other): Variables to support reporting and linkage include age (date of birth), sex/gender, Indigenous status.

If a person receives assistance in two categories (e.g., rent arrears and relocation), they may appear more than once.

The administrative data sets from which this collection is drawn have inaccuracies to varying degrees including missing data and data coding or recording errors.

Not all states and territories collect data items as per data specifications.

Information about the Indigenous status of the household is not collected for some programs within the PRA collection.

Data Access: Publicly available data includes publications, summary tables published in electronic form, and statistics.

Client specified tables on request which may be subject to data provider approval (charges apply).

Restricted unit record access subject to Ethics Committee approval and/or the agreement of all relevant data custodians in all states and territories (charges may apply).

There are restrictions and limitations governing the availability or use of other data in this holding.

More Information: Private rent assistance DSS 2013- https://meteor.aihw.gov.au/content/596529

Glossary: https://www.aihw.gov.au/reports/youth-justice/youth-justice-in-australia-2023-24/contents/glossary

Data Custodian/Owner: AIHW

Source of Metadata Extraction: https://www.aihw.gov.au/about-our-data/our-data-collections/private-rent-assistance-data-collection

18.06.2025

Australian Business Register (ABR)

Purpose: The primary purpose of the Australian Business Register (ABR) is to record and manage information about all businesses and organisations in Australia that have been issued an Australian Business Number (ABN). The ABR serves as a central mechanism for identifying and verifying businesses, enabling government agencies, businesses, and the public to confirm the legitimacy of trading entities. It supports the administration of the taxation system by facilitating the management of GST, PAYG withholding, company tax, and other obligations. It provides a foundation for analysing the structure, dynamics, and performance of the Australian business population.

Main Topic: Employment, income, taxation, wealth, and consumption

Other topics:

Organisational characteristics

Subtopics:

Tax-related information such as registrations for Goods and Services Tax (GST), Pay AS You GO (PAYG) withholding, Fringe Benefits Tax (FBT)
Source and reason for registration
Charity or non-for-profit status
ABN information
Legal and trading names
Entity type
Main business activity
Government entity flag

Included into an integrated data asset:

BLADE
LEED

Population scope: All entities operating in Australia that are required or entitled to register for an Australian Business Number (ABN) under the A New Tax System (Australian Business Number) Act 1999

Geographic scope: Australia (national)

Temporal range: 1999 – ongoing (the latest update - August 2025)

Temporal Unit/Frequency: Event-based/weekly

Unit of Observation: Business entity (ABN holder)

Type of Unit of Observation: Organisation

Collection & Compilation Methods: The Australian Business Register (ABR) is a continuously updated administrative dataset maintained by the ATO. Data collection for the ABR begins when an entity applies for an Australian Business Number (ABN). This application process is mandatory for businesses intending to register for goods and services tax (GST), claim fuel tax credits, or participate in other areas of the tax and regulatory system. During registration, the business is required to provide key identifying and operational information, including legal and trading names, business structure, main business activities, contact details, locations, and relevant tax registrations (such as PAYG or GST). The ATO validates this information using internal records and external sources such as ASIC, the Department of Home Affairs, and the Department of Employment and Workplace Relations, depending on the nature of the entity and its registration.

Once registered, businesses are legally required to maintain accurate information in the ABR. They must notify the Registrar of any relevant changes within 28 days. Changes may include changes in business activity, structure, contact details, or status. The ATO performs ongoing integrity checks to ensure the information remains current and accurate. This includes cross-matching with other government systems, undertaking bulk update programs, and deactivating ABNs that are no longer active or valid.

Data compilation is continuous. The ABR is a live register, meaning that new records are added as ABNs are issued and existing records are updated or cancelled in real time. The ABR system is designed to integrate with other government platforms and databases, the ABR data underpins the ABS Business Register (ABSBR) which serves as the core linkage spine for BLADE.

Data Quality (Scope): The dataset aims to capture all entities operating in Australia that are required or entitled to register for an Australian Business Number (ABN) under the A New Tax System (Australian Business Number) Act 1999. This includes sole traders, companies, partnerships, trusts, superannuation funds, government entities, and not-for-profit organisations, regardless of size, activity level, or sector. As such, the ABR serves as a comprehensive administrative register of legal and operating entities within Australia.

This inclusiveness results in high completeness in terms of legal business identity coverage. However, it also means that not all entities in the ABR are economically active or currently trading. The register includes inactive or dormant entities, and does not provide a direct statistical indicator of economic significance, such as turnover or employment. While an ABN’s status (active or cancelled) is maintained, there is no definitive measure of whether an entity is operational or economically productive at any given time.

Data Quality (Other): Because registration details are self-reported by applicants, the accuracy of some variables, such as business location or industry classification (based on the ANZSIC code), can vary. Although the Australian Taxation Office (ATO) applies validation and integrity checks, the precision and currency of information depend on the compliance and update behaviour of registrants. Businesses may fail to update their details or cancel ABNs when no longer trading, leading to potential data quality issues such as outdated or duplicate records.

Data Access: When an ABN is registered the business identity information is stored in the ABR as public and non-public data. Only eligible government agencies can access and use the non-public data to provide improved community services.

Public data includes: ABN Lookup: https://abr.business.gov.au/ is the public view of the ABR. Using ABN Lookup, agencies can download public data into their applications and databases, and: search for single or multiple ABNs; quickly and easily identify cancelled ABNs and changes to public data items; pre-fill agency online forms and validate ABNs; confirm ABNs without navigating away from payment and procurement applications.

Non-public data: Access to non-public data is available only to eligible government agencies.

The following information explains different methods of accessing public and non-public ABR data: Check if your agency has access to non-public data: https://www.abr.gov.au/government-agencies/accessing-abr-data/agencies-access-non-public-data

If you do not have access, read how your agency can get access to non-public data: https://www.abr.gov.au/government-agencies/accessing-abr-data/abr-data

Once your agency has been granted access to non-public data, the following products and services are available.

The ABR Identifier Search service is not currently accepting new registrations. If you already have an account, you can still access the service as usual.

ABR Explorer: https://www.abr.gov.au/government-agencies/accessing-abr-data/abr-data-products-and-services/abr-explorer

ABR Explorer is an online reporting tool providing eligible government agencies with access to ABR information. ABR bulk data files can also be downloaded using this access channel. ABR bulk data file download: https://www.abr.gov.au/government-agencies/accessing-abr-data/abr-data-products-and-services/abr-bulk-data-file-download

Government agencies with current ABR Partnership Agreement in place can download large volumes of data using ABR Explorer.

More Information: ABR Data Dictionary https://www.abr.gov.au/government-agencies/accessing-abr-data/abr-data-dictionary

About ABR Registrar https://www.abr.gov.au/who-we-are

Email: GovernmentAgencySupport@ato.gov.au

Data Custodian/Owner: ATO Registrar of the Australian Business Register (ABR) The sharing and release of SHSC data where South Australian data can be separately identified is subject to approval from the South Australian government, as they are the data suppliers.

Source of Metadata Extraction: https://abr.business.gov.au/ABR-Data (not working)

08.08.2025

Link added on 05.12.2025: https://www.abr.gov.au/government-agencies/accessing-abr-data/abr-data-products-and-services?utm

Archived on 05.12.2025: https://www.abr.gov.au/government-agencies/accessing-abr-data/abr-data-products-and-services?utm

Youth Justice National Minimum Data Set (YJNMDS)

Purpose: The Youth Justice National Minimum Data Set (YJ NMDS) is an annual collection of information on young people under youth justice supervision in Australia. It contains data on all supervised orders (both community based and detention) relating to young people under youth justice supervision. This dataset is pivotal for informing policy, research, and service delivery in the youth justice sector.

Main Topic: Justice

Other topics:

Demographics
Childcare, education, and training
Health

Subtopics:

Supervision details
Order types
Completion status
Child protection
Interactions with health services

Included into an integrated data asset:

CWDA

Population scope: All young people under youth justice supervision throughout Australia from July 2000

Geographic scope: Australia (national)

Temporal range: 2000-ongoing

Temporal Unit/Frequency: Annually

Unit of Observation: Individual young person (client), period of supervision, order

Type of Unit of Observation: Individual; Event/Process/Activity

Collection & Compilation Methods: The Youth Justice National Minimum Data Set (YJ NMDS), managed by the Australian Institute of Health and Welfare (AIHW), is a comprehensive, longitudinal dataset that captures information on young people under youth justice supervision across Australia. The data for the YJ NMDS are provided to the AIHW by the state and territory departments responsible for youth justice. These departments include: Department of Communities and Justice, New South Wales; Department of Justice and Community Safety, Victoria; Department of Youth Justice and Victim Support, Queensland; Department of Justice, Western Australia; Department of Human Services, South Australia; Department for Education, Children and Young People, Tasmani; Community Services Directorate, Australian Capital Territor; Department of Corrections, Northern Territoy.

To ensure national consistency, the AIHW collaborates with jurisdictions to standardise data definitions and coding practices.

Data Quality (Scope): The YJ NMDS is comprehensive, nationally standardised, and includes both community-based and detention supervision episodes for young people aged 10-17. Overall, the levels of missing data in the YJ NMDS are low. For the majority of variables the proportion of missing data is 1% or less. Not all participating states and territories were able to provide YJ NMDS data in the current format for all years of the YJ NMDS (2000–01 to 2023–24).

Data Quality (Other): The 2023–24 YJ NMDS submission is the seventh to include data for the Northern Territory. Data were supplied in YJ NMDS format for the period 2012–13 to 2023–24. The following Northern Territory data was unavailable in 2023–24: average day, completed supervision periods and average length of time under supervision during the year (all supervision and community-based supervision), and orders (all supervision types).

The 2015–16 reporting period was the first year to include YJ NMDS standard data from Western Australia since 2007–08. In Tasmania, data are available from 2006–07 onwards only. In the ACT, data prior to 2003–04 are not available, and data for 2003–04 to 2007–08 are only available in YJ NMDS 2007 format. In 2023–24, young people aged 12–17 in the ACT and NT were included in the YJ NMDS, as 10 and 11-year-olds cannot be held criminally responsible for their actions following the increase to the minimum age of criminal responsibility from 10 to 12 years old in these jurisdictions.

Each year, most jurisdictions supply data from 2000–01 to the most recent financial year, incorporating updates to data as required. Trend data may therefore differ from those published in previous Youth justice in Australia reports due to data revisions. The most recent data are the most accurate.

The YJ NMDS maintains low levels of missing data. For the majority of variables, the proportion of missing or unknown data is 1% or less. Key Variables with Higher Missing Data: Indigenous Status: Approximately 5.3% of all young people in the YJ NMDS since 2000–01 have an unknown Indigenous status. In 2023–24, this figure was 2.2%, with variation across jurisdictions—for instance, 6.1% in the Australian Capital Territory and 0% in Western Australia.

Geographic Information: Around 5% of records in the order files and 4% in the detention files have unknown or missing information for the postcode, suburb, and state of the young person’s last known address

Data Access: Data derived from the YJ NMDS are publicly available. https://www.aihw.gov.au/reports-data/health-welfare-services/youth-justice/overview https://www.aihw.gov.au/reports/youth-justice/youth-justice-in-australia-2023-24/data

However, access to unit record data is restricted and subject to ethical approvals and agreements with data custodians to protect individual privacy

Geographical coverage: national and states and territories

More Information: Youth Justice Dataset 2020-2023 specification: https://meteor.aihw.gov.au/content/743989 https://www.aihw.gov.au/reports/youth-justice/youth-justice-in-australia-2023-24/contents/summary

Data quality and technical information: https://www.aihw.gov.au/reports/youth-justice/youth-justice-in-australia-2020-21/contents/appendixes

Report: https://www.aihw.gov.au/reports/youth-justice/youth-detention-population-in-australia-2024/contents/understanding-youth-detention-in-australia/age-limits

Email: Youth.justice@aihw.gov.au

Data Custodian/Owner: AIHW

Source of Metadata Extraction: https://www.aihw.gov.au/about-our-data/our-data-collections/youth-justice

09.06.2025

ATO Longitudinal Information Files (ALife)

Purpose: The ATO Longitudinal Information Files (ALife) is a de-identified tax and super dataset. The Australian Taxation Office Longitudinal Information Files: Individuals (ALife: Individuals), is one of the most comprehensive tax administrative datasets in the world. The ALife: Individuals dataset, which currently covers the period 1990-91 to 2017-18, is based on a 10 per cent longitudinal sample of administrative unit-record personal income tax data.

The purpose of ALife is to enable the availability of tax data to researchers. The data asset has built on previous endeavours of producing publicly available tax statistics and producing confidentialised datasets. In addition, its purpose is also to enhance the understanding of public policy and administration in Australia as well as expand research value of administrative data, with approval provided to projects with a benefit to the community for research purposes only.

Main Topic: Employment, income, taxation, wealth, and consumption

Other topics:

Demographics

Subtopics:

Wages and salary
Investment income
Tax
Superannuation

Included into an integrated data asset:

Population scope: All individuals who have interacted with the Australian tax and superannuation systems from 2000–01 onwards.

Geographic scope: Australia (national)

Temporal range: 2000- ongoing (the latest release is 2022-2023)

Temporal Unit/Frequency: Annually

Unit of Observation: Individual person

Type of Unit of Observation: Individual

Collection & Compilation Methods: ALife follows individuals over time, using their unique client identification number. The initial ALife file, ALife 2016, was based on a random 10 percent sample of the total population of individuals on the ATO’s 2016 client register. The client register, which is actively maintained since at least 1980, includes all individuals who are, or have been, registered by the ATO. The most common reason an individual appears on the client register is when they first apply for a tax file number (TFN).

ALife includes a sample of: income tax return data since the 1999–00 financial year; super data drawn from member contribution statements and self-managed super fund annual returns since 2007–08; Higher Education Contribution Scheme (HECS), Higher Education Loan Program (HELP) and Student Financial Supplement Scheme (SFSS) data, and data collected from the ATO client register.

Some direct identifiers are removed while other indirect identifiers are derived into new variables (e.g., date of birth converted to age at 30 June of the tax year or home address converted into Statistical Area Level 4) or removed due to being outliers.

Data are updated annually with the latest year of data, adjustments to location boundaries, tax return amendments, adding tax records of late lodgements.

There is information on a preliminary version of a household-level of tax and superannuation data which links spouses, children, parents, and siblings. Users are instructed to contact the ALife team for more information.

A 10% random sample of individuals is selected based on tax and super interactions from a base year onward (e.g. 2000–01). All personally identifying information is removed. Individuals are assigned a synthetic ID.

Records are linked across years using synthetic IDs, creating a panel dataset (person-year format). Raw tax/super values are cleaned, recoded, and formatted into usable variables for research (e.g., income, deductions, benefits).

Data is perturbed or suppressed in cases where individuals may be re-identifiables. Fine-grained data (e.g. postcode or employer ID) may be aggregated to SA4 or industry code levels.

Data Quality (Scope): Data quality is generally high. It is based on official ATO records — tax, superannuation, and third-party data. The ALife is based on a random 10 per cent sample of tax returns that have been stripped of identifiers and subjected to a range of other techniques to preserve privacy. Limited to individuals who interact with ATO systems. Data lag is 2-3 years.

Data Quality (Other): Sampling is stratified and anchored in a base year (e.g., 2001 or later), and individuals are tracked over time, even if they become inactive.

Alife has a high level of retention. On average, around 96.5% of tax filers who lodge in a given year also lodge in the subsequent income year.

There are more than 400 variables (around 300 from the personal income tax return and over 100 superannuation variables) with clear naming conventions. The data is available in ‘csv’ and ‘dta’ formats. Some of the variables, e.g. occupation, are self-reported.

Policy and administrative changes such as changes to superannuation may have implications for this dataset.

Data Access: Access to the ALife is limited to researchers from approved organisations. Researchers need to meet certain requirements and obtain ethics approval. Detailed information on access for different types of researchers is available at: https://alife-research.app/info/gaining-access#Applying%20for%20access

Approved researchers generally access ALife through a secure connection to a remote-access data research lab operated by an approved independent provider (currently SURE operated by the Sax Institute).

Data is available at national, state/territory and SA4 levels

More Information: ALife Manual (contains variables, glossary, forms)

https://alife-research.app/research/search/list https://alife-research.app/info/overview#ALife-Family https://openresearch-repository.anu.edu.au/server/api/core/bitstreams/ff2c457f-62c3-4d84-a280-542eccf196fe/content

Email : alife@ato.gov.au

Data Custodian/Owner: ATO

Source of Metadata Extraction: https://alife-research.app/

16.07.2025

Archived on 05.12.2025: https://alife-research.app/

Data Exchange (DEX)

Purpose: The DEX is the program performance reporting solution developed by the DSS. It was developed to improve the way administrative data are collected and used to improve the wellbeing of people and families. Organisations funded under the National Disability Advocacy Program (NDAP) are required under their agreement with the Commonwealth to enter data into the DSS DEX in accordance with the data exchange protocols.

Main Topic: Social support and welfare

Other topics:

Demographics

Subtopics:

Support services for families
Parenting programs
Children’s wellbeing
Family relationship services.

Emergency relief

Financial counselling
Support to improve financial literacy and resilience
Housing and Homelessness services
.

Settlement Services

Community based mental health support programs
Disability and Carers
Employment and Skills programs
Other Social Services

Included into an integrated data asset:

PLIDA

Population scope: Individuals and families who receive services funded by the Department of Social Services (DSS) or participating agencies.

Geographic scope: Australia (national)

Temporal range: 2014-ongoing

Temporal Unit/Frequency: Biannually

Unit of Observation: Individual person, service session

Type of Unit of Observation: Individual; Event/Process/Activity

Collection & Compilation Methods: Service providers (e.g., NGOs, state/territory agencies) funded under DSS grant programs must routinely report client-level and service delivery information. The minimum Priority Requirements are mandatory, while the enhanced Partnership Approach (SCORE outcomes) is optional but incentivised. Organisations can upload data in three ways: direct entry via the web portal; bulk XML file uploads, and system-to-system transfers using web services from their internal case-management systems.

All reporting adheres to the Data Exchange Protocols, a comprehensive manual guiding data definitions, formats, technical requirements, and quality expectations.

Organisation-submitted data feeds into automated reporting tools (e.g. Qlik-based dashboards, “Stories”) accessible via the web portal.

Each biannual reporting period (Jul–Dec, Jan–Jun) enables near-real-time access to insights on clients, service sessions, and outcome metrics

Data Quality (Scope): While it intends to cover all people accessing or requesting DSS-funded services, not service providers consistently report all the clients. Clients who do not consent to provide a Statistical Linkage Key (SLK) or identifying info may be counted incompletely or excluded.

Data Quality (Other): DEX only includes services funded through specific DSS programs. If a service is co-funded by another department or jurisdiction, data may not be included. Variables: high level of completeness for mandatory variables such as session date, session type, program activity and some demographics. Voluntary or optional fields such as income or living arrangements can be incomplete. No standard measure of service time; session counts may not reflect actual time or effort.

Data Access: Publicly available data in the form of reports. https://dex.dss.gov.au/document/746

Organisations funded by DSS that have an active DEX portal account can access their own client-level data, including cases and sessions. Access occurs via: web portal (view, search, filter data); bulk XML upload/download; system to system API connections.

Under the Partnership Approach, additional data elements such as outcome metrics (SCORE) and the Statistical Linkage Key (SLK) are included for participating providers.

DSS staff, and potentially accredited external researchers, may access de-identified unit data under strict governance.

More Information: Community Outcomes (SCORE) Fact Sheet: https://dex.dss.gov.au/document/796

DEX Framework: https://dex.dss.gov.au/sites/default/files/documents/2022-07/1066-data-exchange-framework.pdf

DEX protocols: https://dex.dss.gov.au/data-exchange-protocols?utm

Email: dssdataexchange.helpdesk@dss.gov.au

Data Custodian/Owner: DSS

Source of Metadata Extraction: https://dex.dss.gov.au/

14.07.2025

Archived on 05.12.2025: https://dex.dss.gov.au/

Single Touch Payroll (STP)

Purpose: Single Touch Payroll (STP) is an Australian Government initiative to streamline employers’ reporting to government agencies. The purpose of the Single Touch Payroll (STP) dataset is to provide a real-time, administrative data source on payroll and employment information for Australian employees.

Main Topic: Employment, income, taxation, wealth, and consumption

Other topics:

Organisational characteristics

Subtopics:

Employment
Income and wages
Taxation
Superannuation
Payroll reporting activity

Included into an integrated data asset:

BLADE
LEED
PLIDA

Population scope: All employees paid by employers operating in Australia who report through STP

Geographic scope: Australia (national)

Temporal range: 2018-ongoing

Temporal Unit/Frequency: Weekly/fortnightly/monthly

Unit of Observation: Employee-pay event

Type of Unit of Observation: Individual; Event/Process/Activity; Organisation

Collection & Compilation Methods: The Australian Taxation Office (ATO) receives payroll information from employers through STP enabled payroll and accounting software each time the employer runs its payroll. The ATO provides selected employer and job level data items from the STP system to the ABS to produce official statistics. With STP employees’ payroll information is reported to ATO each time an employer pays them through STP-enabled software. Payroll information includes: ssalaries and wages; pay as you go (PAYG) withholding; superannuation liability information.

From 1 January 2022, the data collected through STP was expanded to collect additional payroll information. Validated data is stored in ATO systems and used for: compliance monitoring; pre-filling tax returns; super guarantee monitoring; historical data is compiled continuously for each financial year.

The ATO provides STP transactions to the ABS on a weekly basis. Transactions reported each week are generally for payments of wages and salaries for a defined pay cycle period. Weekly data can include other forms of payments or corrections to previously reported transactions.

Submissions of STP data vary from employer to employer based on pay cycle frequency and reporting arrangements of individual employers, however most report at the time the payroll is run. There can be reporting lags and other events that can affect regular employer reporting, which can result in revisions.

A payroll job exists when a payment has been received in a reference period. The following subsections describe the transformations used to produce the data for statistical purposes.

The STP data is enhanced through combining other administrative data held by the ABS (also sourced from the Australian taxation system).

Age and residential state/territory variables are primarily sourced from Client Register data (supplied by the ATO to the ABS as part of the transfer of Personal Income Tax data). When age and residential state/territory are not available from Client Register data, they are sourced from STP data. Up until March 2021, annual snapshots of Client Register data were used to refresh job holder variables. The payroll job system and processes can no longer support further updates from the Client Register.

Industry of activity and employment size variables of the employing business are sourced from the ABS Business Register (ABSBR). Variables from the ABSBR are updated periodically.

Data Quality (Scope): High coverage, mandatory for all Australian employers since July 2019. Persons reported via STP must hold either a Tax File Number (TFN) or an Australian Business Number (ABN). Not all jobholders in the Australian labour market are included in these estimates. Payroll jobs reported via STP exclude owner managers of unincorporated enterprises (OMUEs), which are more prevalent in the Construction and Agriculture, forestry and fishing industries. All payroll jobs are included, regardless of age or Australian residency status. Employers with 20 or more employees (large employers) commenced the transition to STP reporting on 1 July 2018. Employers with less than 20 employees (small employers) began transitioning to STP reporting on 1 July 2019. Small employer reporting concessions ended on 30 June 2021. From 1 July 2021 almost all large employers and eligible small employers are reporting through STP.

Data Quality (Other): Core variables such as employer ABN, pay date, pay period, gross income, tax withheld are of high quality. Optional fields such as employment basis are of moderate quality. Payroll job estimates are derived from data collected via the STP system, which effectively supports employer reporting obligations and ATO operational requirements through STP enabled software. STP was not primarily designed to support the production of statistics, hence some inherent characteristics contribute to variability in the estimates and revisions between releases. STP data originates from a wide range of payroll software used by employers. While standardised by ATO specifications, implementation differences can lead to: variations in field population and i nconsistent use of income types or codes.

Data Access: Aggregated statistics is available in a form of publications : https://www.ato.gov.au/businesses-and-organisations/hiring-and-paying-your-workers/single-touch-payroll/stp-and-activity-statements

https://www.ato.gov.au/about-ato/research-and-statistics/in-detail/taxation-statistics/taxation-statistics-2022-23/statistics/pay-as-you-go-statistics

Access to a unit-level data is via the DataLab.

More Information: STP started on 1 July 2018 for employers with 20 or more employees and 1 July 2019 for employers with 19 or fewer employees and is a mandatory obligation.

Payroll jobs methodology https://www.abs.gov.au/methodologies/payroll-jobs-methodology/week-ending-15-march-2025

STP payroll records are integrated within PLIDA alongside Census, tax, government payments, health, and more.

News https://www.ato.gov.au/businesses-and-organisations/hiring-and-paying-your-workers/single-touch-payroll/news-events-and-resources

STP employer reporting guidelines https://www.ato.gov.au/businesses-and-organisations/hiring-and-paying-your-workers/single-touch-payroll/in-detail

Items included: BMS ID; payer ABN/WPN; branch code; payer name; payer contact details; payer postcode; payer country of main business location; pay date; update date; run timestamp; submission ID; full-file replacement indicator; period total PAYG withholding; period total gross; intermediary details; intermediary declaration; child support garnishee total; child support deduction total; payee TFN; contractor ABN; payroll ID; previous payroll ID; family name; given name; other name; date of birth; residential address line 1; residential address line 2; suburb; postcode; country code; contact email; contact phone; employment basis; commencement date; cessation date; cessation type code; tax treatment code; tax offset amount; study and training loan indicators; pay period start date; pay period end date; final event indicator; income type; income stream collection; ordinary time earnings amount; disaggregated gross amount; overtime amount; bonuses and commissions amount; directors’ fees amount; paid leave type; paid leave amount; allowance type code; allowance description; allowance amount; lump sum type; lump sum amount; lump sum relevant financial year; ETP code; ETP payment date; ETP tax-free component; ETP taxable component; ETP PAYG withholding; foreign employment income amount; foreign tax paid; exempt foreign income; JPDA indicator/amount; PAYG withholding amount; deduction type; deduction amount; salary sacrifice type; salary sacrifice amount; superannuation entitlement type; superannuation liability/amount; OTE for super; RESC; RFBA taxable amount; RFBA exempt amount; RFBA type code

Email: singletouchpayroll@ato.gov.au

Data Custodian/Owner: ATO

Source of Metadata Extraction: https://www.ato.gov.au/businesses-and-organisations/hiring-and-paying-your-workers/single-touch-payroll

18.07.2025

Archived on 05.12.2025: https://www.ato.gov.au/businesses-and-organisations/hiring-and-paying-your-workers/single-touch-payroll

Admitted Patient Care National Minimum Data Set (APC NMDS)

Purpose: The purpose of the Admitted Patient Care National Minimum Data Set (APC NMDS) is to support national monitoring, analysis, planning, and policy development for hospital-based care across Australia. It captures detailed, standardised information about every episode of care for patients admitted to public and private hospitals.

Main Topic: Health

Other topics:

Demographics

Subtopics:

Diagnoses
Procedures and interventions
Details about admission and discharge
Private/public hospital
Funding source
Care type (acute, rehabilitation, palliative)

Included into an integrated data asset:

In NDDA for SA/ACT

Population scope: All patients admitted to public and private hospitals in Australia for an episode of care.

Geographic scope: Australia (national)

Temporal range: 1993- ongoing (latest data 2023-2924)

Temporal Unit/Frequency: Annually

Unit of Observation: Individual episode of admitted patient care

Type of Unit of Observation: Event/Process/Activity

Collection & Compilation Methods: Public and private hospitals in all states and territories collect patient-level data during each episode of admitted care (same day or overnight). Information includes demographics, diagnoses, procedures, admission/discharge dates, care type and funding source. Clinical information is coded using ICD-10-AM, ACHI, ACS. Hospitals use jurisdiction-specific health information systems to collect and validate data. Hospitals submit records to their respective state or territory health departments regularly (e.g. monthly, quarterly). Jurisdictions validate and standardise the data using AIHW-specified protocols. Each jurisdiction compiles its data into a nationally agreed format conforming to the APC NMDS specifications and submits to AIHW.

Data Quality (Scope): Coverage is close to 100% of admitted episodes in public hospitals. Private hospital data is not always complete, depending on voluntary participation and submission quality.

Data Quality (Other): Some variables such as Indigenous status, country of birth may be incomplete or non-accurate, especially in earlier years. While data is collected consistently over time and across jurisdictions with common metadata and coding standards, there have been changes in coding systems and care classification which may impact data quality.

Data Access: AIHW provides regular summary statistics, data cubes, and interactive dashboards, for example Principal diagnosis data cubes: https://www.aihw.gov.au/reports/hospitals/principal-diagnosis-data-cubes/contents/summary

For individual-level data researchers need to submit request to AIHW under the National Health Data Agreement.

Geographical coverage: national, state/territory, LHN (Local Hospital Network)

More Information: The National Hospital Morbidity Database (NHMD)is an output of the Admitted Patient Care NMDS – which is a collation of data based on an agreed data specification which AIHW then does some processing and QA to ensure national consistency. NHMD and APC often seem to get used interchangeably.

The NHMD listing on the AIHW’s website links to the APC data set. https://www.aihw.gov.au/about-our-data/our-data-collections/national-hospitals-data-collection

APC NMDC National Health Data dictionary https://www.aihw.gov.au/getmedia/a80cbfd4-2601-472f-942b-9bd2c90bca1d/apc.pdf Hospitals https://www.aihw.gov.au/hospitals/latest-updates-and-downloads/data

Reports: https://www.health.nsw.gov.au/aod/summit/publications/monitoring-and-reporting.pdf

Data Custodian/Owner: AIHW and each state and territory’s health authorities

Source of Metadata Extraction: https://www.aihw.gov.au/reports/hospitals/admitted-patient-care-nmds/summary

22.07.2025

NSW Controlled Drugs Data Collection (CoDDaC)

Purpose: The NSW Controlled Drugs Data Collection (CoDDaC) records details of authorities from the NSW Ministry of Health to prescribe or supply a Schedule 8 drug, including methadone and buprenorphine under the NSW Opioid Treatment Program (OTP), psychostimulants for the treatment of Attention Deficient Hyperactivity Disorder in children and adults, and Schedule 8 opioids for the ongoing management of chronic pain. The CoDDaC includes data relating to patients and prescribers.

Main Topic: Health

Other topics:

Demographics

Subtopics:

Treatment episode details Controlled drug user and authorisation Provider information Health system utilisation

Included into an integrated data asset:

Population scope: All individuals in New South Wales who are authorised to be prescribed Schedule 8 (S8) controlled substances under the NSW regulatory framework

Geographic scope: NSW

Temporal range: 1985- ongoing (latest data 2023)

Temporal Unit/Frequency: Irregular

Unit of Observation: Prescribed treatment authorisation record for a controlled (Schedule 8) drug; individual

Type of Unit of Observation: Event/Process/Activity; Individual

Collection & Compilation Methods: CoDDaC consists of three subcollections: Subcollection 1: Opioid Treatment Program (OTP) Relates to opioid substitution pharmacotherapy provided under the NSW OTP. Records are sourced from SafeScript NSW.

Subcollection 2: Other Schedule 8 (S8) medicines Relates to approvals for the prescribing of S8 medicines to individual patients other than those prescribed under the NSW OTP. These include: opioids for the ongoing management of pain; psychostimulants for the treatment of attention deficit hyperactivity disorder (ADHD) and hypersomnolence disorders such as narcolepsy; the benzodiazepines alprazolam and flunitrazepam for anxiety and insomnia respectively; and cannabis medicines. An approval is required in only some circumstances, so the data do not reflect all prescribing. Records are sourced from SafeScript NSW.

Subcollection 3: Notified Psychostimulant Prescriptions Relates to prescriptions for psychostimulant medicines for the treatment for ADHD in children and adults that were notified as a condition of general authorisation to prescribe psychostimulants for ADHD. The subcollection spans the period June 1996 to May 2016. Records were maintained in the (decommissioned) ERRCD system and have otherwise been archived.

The data collection system for the CoDDaC is the NSW Electronic Recording and Reporting of Controlled Drugs (ERRCD) system. ERRCD was implemented in September 2016 to replace the legacy Pharmaceutical Drugs of Addiction System (PHDAS).

Data Quality (Scope): Near-complete coverage of all S8 drug authorisations issued in NSW since 1985.

Data Quality (Other): High accuracy for core variables such as patient-related and provider-related variables, as well as drug-related variables, e.g. patient’s primary opioid drug of dependence On 22 May 2023, SafeScript NSW was adopted as the management system for applications and approvals to prescribe S8 medicines, replacing the ERRCD system which was subsequently decommissioned. The switch to SafeScript NSW resulted in changes to some data in the subcollections. The changes included transformation of some data to align with new classifications adopted in SafeScript NSW and to support implementation of new approval management procedures. The collection of some information was discontinued, and some information was not migrated from ERRCD and is no longer part of the CoDDaC. Details of changes are provided in the variable list. Strong for current ERRCD data; legacy PHDAS data (pre-2016) may have some gaps due to variability in metadata structure between the current and previous systems

Data Access: Publicly available resources offer aggregated data.

To access unit-level (person-level) CoDDaC data, researchers must follow strict procedures: Access Pathway via CHeReL. As part of the Master Linkage Key (MLK), CoDDaC is linkable to other NSW health datasets. Researchers must apply through the Centre for Health Record Linkage (CHeReL): submit an Expression of Interest via CHeReL’s CheckApp system, and provide a detailed project plan, ethics approval, and data custodian approval (incl. NSW Ministry of Health).

CoDDaC data is accessed only within approved secure environments (e.g. NSW Health Secure Access Environment - SAE or SURE lab).

Geographical coverage: NSW, LHD region codes

More Information: Data dictionary coddac-data-dictionary-mar-2025.docx

Variables list coddac-otp-mar-2025.xlsx

Other S8 authorisations coddac-other-s8-mar-2025.xlsx

Email: MOH-PharmaceuticalServices@health.nsw.gov.au

Data Custodian/Owner: NSW Department of Communities and Justice Pharmaceutical Regulatory Unit, NSW Ministry of Health

Source of Metadata Extraction: https://www.metadata.nsw.gov.au/item/4786/distribution/nsw-controlled-drugs-data-collection-otp_auth_all_

21.07.2025

Archived on 05.12.2025: https://www.metadata.nsw.gov.au/item/4786/distribution/nsw-controlled-drugs-data-collection-otp_auth_all_

Australian Curriculum, Assessment and Reporting Authority Student Attendance Data Collection (ACARA SAC)

Purpose: The ACARA Student Attendance Data Collection is used to monitor school attendance rates for students in Years 1–10 across all Australian school sectors. Its primary purpose is to support national reporting on student engagement, educational equity, and policy development. The dataset informs key national reports such as the National Report on Schooling in Australia, the Closing the Gap initiative, the Report on Government Services, and the My School website. It enables consistent, comparable attendance reporting by applying national standards for data collection and aggregation, ensuring that attendance metrics are calculated uniformly across jurisdictions and school types.

Main Topic: Childcare, education, and training

Other topics:

Demographics

Subtopics:

Student attendance School engagement Educational equity Indigenous education School type and sector

Included into an integrated data asset:

Population scope: All full-time students enrolled in Years 1 to 10 across all Australian states and territories and all school types.

Geographic scope: Australia (national)

Temporal range: 2008-ongoing

Temporal Unit/Frequency: Annually

Unit of Observation: School

Type of Unit of Observation: Organisation

Collection & Compilation Methods: ACARA collects, manages, evaluates and reports information on a range of educational outcomes. Student attendance data is one of the measurements of schooling in Australia, agreed by all state, territory and the Commonwealth Ministers of Education. The ACARA Student Attendance Data Collection uses administrative data reported by states, territories, and non-government education authorities. Each jurisdiction collects attendance records from schools in their sector. Student attendance has 2 reporting periods: Semester 1 (usually, terms 1 and 2): The period between the first school day of the year and the last school day of semester 1. Term 3: The period between the first school day of term 3 and the last school day of term 3.

Student attendance data is collected through the Student Attendance (STATS) collection, which covers full-time students in Years 1 to 10 across primary, secondary, and special schools. This includes ungraded students (labelled 11MINUS or 12PLUS) who are within the typical age range for Years 1 to 10. The dataset captures both the number of days each student was present and the total number of possible school days, disaggregated by variables such as year level, gender, Indigenous status, geographic location, and socioeconomic background.

All schools are required to complete the STATS submission for each of their campuses or locations.

The collected data is supplied to ACARA for a variety of reporting purposes. These include publishing student attendance rates on the My School website and reporting attendance at the national, state/territory, and school sector levels in national education performance reports.

Data Quality (Scope): Some students must not be included in the submission to the collection. These are: students in foundation year (year 1 minus 1) and earlier programs, students in years 11 and 12, part-time students (who are not full-time at state level), distance education students, home-schooled students, students no longer enrolled at the school for the entirety of the reference period. This includes expulsion or similar.

For more information about data quality and scope issues, see explanatory notes..

Data Quality (Other): National standardisation is the strength of this dataset. The National Standards for Student Attendance Data Reporting (Third Edition) were co-developed with all jurisdictions and sectors to ensure consistency in attendance calculations; standardised reference periods, definitions for enrolment status, part-day absences, mobility issues. However, there are some historical inconsistencies. Pre-2013 data were not fully compatible across jurisdictions and sectors.

Data Access: General users can access statistics for Years 1-10 published annually on: https://schools.education.gov.au/SchoolsHub/articlehelp/?subjectid=735f2bde-0

De-identified unit record data is available by request: datarequest@acara.edu.au

When submitting a data request, the signatory listed must be authorised to sign a legal document on behalf of your organisation.

The intended purpose of the Data Access Program as per the Data Access Protocols is to facilitate quality research to maximise benefits to students, schools and the Australian community.

More Information: MySchool publishes student attendance caveats for each state and territory on an annual basis: https://myschool.edu.au/technical-and-statistical-information/attendance-caveats

National Standards for Student Attendance Data Reporting https://dataandreporting.blob.core.windows.net/anrdataportal/ANR-Documents/National%20standards%20for%20student%20attendance%20reporting%20-%20third%20edition.pdf

STATS data https://schools.education.gov.au/SchoolsHub/articlehelp/?subjectid=735f2bde-0efc-e811-9158-02720401ef44

Email: info@acara.edu.au

Data Custodian/Owner: ACARA

Source of Metadata Extraction: https://www.acara.edu.au/reporting/national-standards-for-student-attendance-data-reporting

22.07.2025

Archived on 05.12.2025: https://www.acara.edu.au/reporting/national-standards-for-student-attendance-data-reporting

Recorded Crime - Offenders (RCO)

Purpose: The purpose of the Recorded Crime – Offenders (RCO) dataset is to provide nationally consistent statistics on individuals aged 10 years and over who have been proceeded against by police across Australia. It supports analysis of offender demographics, offence types, and trends over time, enabling comparisons across jurisdictions. The dataset is used by governments, justice agencies, and researchers to inform criminal justice policy, monitor police activity, and better understand patterns of offending behaviour.

Main Topic: Justice

Other topics:

Demographics

Subtopics:

Offender counts
Offender types
Principle offence
Repeat offending
Proceeding

Included into an integrated data asset:

Population scope: Alleged offenders aged 10 and over who have been proceeded against by police during the reference period. Criminal offences where police agencies have the authority to take legal action against an individual are included, with some exclusions.

Geographic scope: Australia (national)

Temporal range: 2007-ongoing

Temporal Unit/Frequency: Annually

Unit of Observation: The individual offender proceeded against by police

Type of Unit of Observation: Individual

Collection & Compilation Methods: RCO presents statistics about alleged offenders who were proceeded against by police during the 12-month reference period, for all states and territories. This includes information about the most serious offence, referred to as the principal offence, associated with an alleged offender (after this referred to as an offender). Statistics are also presented on the number of proceedings that police initiated for all states and territories except Western Australia.

Data is compiled based on the date that police-initiated action, or proceeded against, an offender (e.g., the date the offender was charged, the date the offender was cautioned, etc.). The date the offender was proceeded against by police may not be the date when the offence occurred, or the date when the offender came to the attention of police. In some jurisdictions the data may reflect the date of record creation rather than date of action; however, this does not have a significant impact on the comparability of data across jurisdictions for offenders as there are no major lags between the two dates.

For the offender population, an offender is only counted once, irrespective of how many offences they may have committed within the same incident or how many times they were dealt with by police during the reference period.

For the police proceeding population, an offender may be counted more than once if proceeded against on separate occasions by police during the reference period. Data is presented for both court and non-court proceedings where available.

Offence information presented in this publication relates to the principal offence allegedly committed by an individual offender during the reference period. These statistics are not designed to provide a count of the total number of individual offences that come to the attention of police.

For the offender counts, where a single offence is processed by police during the reference period, the offender is assigned that offence as their principal offence. Where multiple offences are committed by an offender, they are assigned a principal offence using the ABS National Offence Index (NOI). For the police proceeding counts, offenders who are proceeded against more than once in the reference period are assigned a principal offence for each separate date of police action.

Data Quality (Scope): The scope includes all persons aged 10 years and over who have been proceeded against by police during the reference financial year in each state and territory. It covers both court and non-court proceedings for criminal offences as recorded in police administrative systems. The dataset excludes offenders younger than 10 (below the age of criminal responsibility), people dealt with by other means outside of formal police proceedings (e.g. informal diversion not recorded), and offences handled by non-police agencies. It also excludes breaches of custodial orders where the breach itself does not constitute a new offence. The dataset is limited to offences that were finalised by police during the reporting period and may not include all offences committed in that time if they were still under investigation.

Data Quality (Other): The use of an offender-based counting rule means each offender is only counted once per year per principal offence type, potentially underestimating the total volume of offences. Only the most serious offence per proceeding is recorded as the principal offence, which may obscure other concurrent offences. Incomplete or inconsistent recording of Indigenous status limits the reliability of disaggregated analysis for Aboriginal and Torres Strait Islander peoples.

The dataset includes only proceedings finalised by police within the reference year, excluding ongoing investigations or delayed matters. Additionally, changes in police data systems and processing methods over time may affect consistency, and the dataset excludes offenders under 10 years of age or matters dealt with entirely outside the formal police process.

Some data inconsistencies for Western Australia which did not report number of times proceeded against or police proceedings in earlier years, and still faces ongoing reporting issues related to dual crime-recording systems.

The Indigenous status is not recorded consistently across all jurisdictions and its quality caried over time. The ABS includes Indigenous status data only for jurisdictions where it meets quality standards. For example, in 2023–24, reliable Indigenous data were available only for NSW, QLD, NT, SA, and ACT, while VIC, WA, and TAS were excluded due to insufficient quality.

Offenders proceeded against by penalty notice often lack Indigenous identification, leading to substantial “unknown” values. These records are excluded from Indigenous offender count.

There are also some inconsistencies in coding for COVID-19 related offences

Data Access: Data can be accessed via: TableBuilder under the Crime and Justice Theme. ABS offers securely downloadable basic microdata (unit records), stripped of direct identifiers and classified into broad categories to protect confidentiality which is available to Australian organisations via subscription.

Detailed microdata can be accessed via DataLab by application only.

More Information: Methodology: https://www.abs.gov.au/methodologies/recorded-crime-offenders-methodology

Previous annual release: https://www.abs.gov.au/statistics/people/crime-and-justice/recorded-crime-offenders/2022-23

Archive: https://www.abs.gov.au/statistics/people/crime-and-justice/recorded-crime-offenders

Data Custodian/Owner: ABS

Source of Metadata Extraction: https://www.abs.gov.au/statistics/people/crime-and-justice/recorded-crime-offenders/latest-release

23.07.2025

Archived on 05.12.2025: https://www.abs.gov.au/statistics/people/crime-and-justice/recorded-crime-offenders/latest-release

Recorded Crime - Victims (RCV)

Purpose: The purpose of the Recorded Crime – Victims (RCV) dataset is to provide data about victims of selected offences that came to the attention of, and were recorded by police during a reference period. Selected characteristics about the victim (including sex and age) or incident (including weapon use and location) are also presented, as well as the outcome of the police investigation at 30 days from the time of report. Information about the relationship of the offender to the victim and the Aboriginal and Torres Strait Islander status of the victim is also presented for selected states and territories.

Main Topic: Justice

Other topics:

Demographics

Subtopics:

Type of offence
Case and incident characteristics
Victim type

Included into an integrated data asset:

Population scope: Victims of crime for a selected range of offences as recorded by police

Geographic scope: Australia (national)

Temporal range: 1993-ongoing

Temporal Unit/Frequency: Annually

Unit of Observation: A recorded victim of a selected offence

Type of Unit of Observation: Individual

Collection & Compilation Methods: Data is compiled based on the date an offence is reported to police and recorded within the reference period. This corresponds to either the date the offence was reported to police by a member of the public or when it was detected by police and was recorded on police systems. The report date may not necessarily be the date when the offence occurred. This is particularly the case for sexual assault, where in some instances there may be a large time difference between when the offence occurred and the report/detection date. Statistics are: created from data held in administrative systems which is collected and maintained by police agencies within each state and territory; collected by the ABS and compiled according to the National Crime Recording Standard in order to maximise consistency between states and territories, and produced annually on a calendar year basis.

Data Quality (Scope): The scope of this collection includes victims of offences. A victim can be a person, premises, organisation, or motor vehicle depending on the type of offence. Selected offence categories are: homicide and related offences (including murder, attempted murder and manslaughter, but excluding driving causing death and conspiracy to murder), assault, sexual assault, abduction and kidnapping, robbery, blackmail and extortion, unlawful entry with intent/burglary, break and enter, motor vehicle theft, other theft. Statistics in this data set relate to both completed and attempted offences, i.e. those where the intent is not fulfilled. The scope excludes the following: conspiracy offences, threats to commit an offence (an exception to this exclusion is assault where there is an apprehension that the direct threat of force, injury, or violence could be enacted, which is in-scope of the collection. This also applies to offences like robbery, kidnapping/abduction and blackmail/extortion where an element of threat is implicit in the nature of the crime); aid, abet and accessory offences, deprivation of liberty offences, where an outcome of investigation determines ‘no crime’ was committed i.e. the offence was reported to police but later deemed to be unfounded, false, or baseless; counts are excluded from the data. Victims of crime as recorded by the Australian Federal Police (AFP). As such, victims of crime in Australia’s ‘other territories’ such as Christmas Island, the Cocos (Keeling) Islands and Jervis Bay Territory are out of scope as these territories are under AFP jurisdiction.

Data Quality (Other): The use of the Australian and New Zealand Standard Offence Classification (ANZSOC) enhances the quality of the data collection by providing consistent and rigorous framework. However, transition from ASOC to ANZSOC, updates to ANZSOC and changes in police recording practices can affect data continuity. Granular variables and disaggregation is another strength of this data set.

However, the data set only includes crimes reported to and recorded by police. It does not capture unreported incidents.

The use of the FDV flag as a measure of victims of FDV related offences varies across the states and territories.

Indigenous status is based on self-identification by the individual who comes into contact with police. Some offence data was not available for 1993 and 1994 as a staged approach was used to set up the original data collection. Data was collected from 1995 for: assault, further detail for unlawful entry with intent with subcategories of ‘property – stolen’ and ‘property – other’, other theft.

Detailed microdata can be accessed via DataLab by application only.

More Information: Recorded Crime- Victims: https://www.abs.gov.au/statistics/people/crime-and-justice/recorded-crime-victims

Data downloads 2023: https://www.abs.gov.au/statistics/people/crime-and-justice/recorded-crime-victims/2023#data-downloads

Data Custodian/Owner: ABS

Source of Metadata Extraction: https://www.abs.gov.au/statistics/people/crime-and-justice/recorded-crime-victims/latest-release

23.07.2025

Archived on 05.12.2025: https://www.abs.gov.au/statistics/people/crime-and-justice/recorded-crime-victims/latest-release

Medicare Benefits Schedule (MBS)

Purpose: The Medicare Benefits Schedule (MBS) data collection contains information on services that qualify for a benefit under the Health Insurance Act 1973 and for which a claim has been processed. The database comprises information about MBS claims (including benefits paid), patients and service providers.

It supports health policy development, service planning, funding decisions, monitoring of healthcare utilisation, and population health research. It also enables analysis of healthcare access, equity, costs, and outcomes across different demographic and geographic groups.

Main Topic: Health

Other topics:

Demographics

Subtopics:

Referral details
Type of claim
Type of medical services
Service delivery details
Provider type

Included into an integrated data asset:

COVID-19 Register
CWDA
NACDA
NDDA
NHDH
PLIDA

Population scope: All individuals who are enrolled in Medicare and who have accessed at least one Medicare-subsidised service during the reference period.

Geographic scope: Australia (national)

Temporal range: 1984-ongoing

Temporal Unit/Frequency: Monthly/quarterly/annually

Unit of Observation: MBS service claim

Type of Unit of Observation: Event/Process/Activity

Collection & Compilation Methods: The Medicare Benefits Schedule (MBS) data are collected through administrative processes managed by Services Australia on behalf of the Department of Health and Aged Care. Each time a Medicare-eligible medical service is provided and a claim is lodged, either through bulk billing by the service provider or by the patient submitting a claim, the details of that transaction are recorded. This includes the MBS item number, date of service, benefit paid, and information about the provider and patient. Healthcare providers and patients submit claims to Services Australia using multiple ways including electronic claiming systems (e.g. Medicare Easycliam), manual claims submitted directly by patients via Medicare offices, mail, or MyGov, and bulk billing arrangements. Services Australia comply transaction records into an administrative database that captures all Medicare-subsidised services across Australia. The data are then de-identified and securely transferred to the Department of Health and Aged Care, and for research and integration purposes, to authorised agencies. Before release or integration, the data are subject to quality assurance processes, including cleaning, classification by item codes, and validation checks.

Data Quality (Scope): The data set captures a complete census of Medicare claims covering all eligible patients and services providers across Australia. Includes: • all Australian residents who hold a current Medicare card and overseas visitors from countries with which Australia has a Reciprocal Health Care Agreement (RHCA) • All age groups, from infants to older adults • Services provided under the MBS, including general practitioner visits, specialist consultations, diagnostic tests, imaging, surgeries, etc. The dataset does not include individuals who: • Are not enrolled in Medicare (e.g. newly arrived migrants not yet eligible) • Received medical services that are not claimed under Medicare (e.g. fully private services without a rebate)

Data Quality (Other): Limited demographic detail. Variables to support reporting and linkage include agee (date of birth), sex (gender).

Variability in provider billing practices. Providers may differ in how they apply certain MBS item numbers, especially for complex consultations or procedures, which can introduce inconsistencies in how services are classified

Data Access: Publicly available data includes publications, summary tables published in electronic form, and statistics.

MBS Group Reports are interactive reports grouped by MBS categories, subgroups, or Broad Type of Service (BTOS), with demographic drills and downloadable output. https://medicarestatistics.humanservices.gov.au/VEA0032/SAS.Web/statistics/mbs_group.ht

MBS Item Reports Online tool can be used to generate item-level statistics for specified MBS items. Includes demographic breakdowns, time-series charts, and custom reporting by item number. https://medicarestatistics.humanservices.gov.au/statistics/mbs_item.html

Medicare Benefits Schedule Statistics is available at data.gov.au https://data.gov.au/data/dataset/medicare-benefits-schedule-statistics

Restricted unit record access, requires ethics approval and secure access.

Geographical coverage: states, territories, PHN, LGA

More Information: MBS Online: https://www.mbsonline.gov.au/

Medicare Benefits Scheme funded services: monthly data

A live dashboard showing monthly metrics—including the MBS subsidy proportion and services per person—presented by state/territory and LGA. Includes downloadable data and technical noteshttps: //www.aihw.gov.au/reports/medicare/mbs-funded-services-data

Medicare Benefits Scheme funded services over time Offers trend analysis from the MBS’s start in 1984 through mid 2023, with deep dives on rates per person and subsidy levels. https://www.aihw.gov.au/reports/medicare/mbs-funded-services-over-time Medicare funding of General Practitioner services over time. Focused review of GP attendances, subsidy rates, out-of-pocket costs, and attendance patterns by remoteness and socio-economic status. https://www.aihw.gov.au/reports/medicare/medicare-funding-of-gp-services-over-time

Geography and time specific health data for environment & health dashboards

Weekly MBS item use by geographic areas (SA4s) from 2002–03 to 2021–22, for environmental and demographic analysis. Includes technical notes. https://www.aihw.gov.au/reports/environment-and-health/geography-time-specific-data-environment

Email: mbs.pbs@aihw.gov.au

Data Custodian/Owner: AIHW Australian Government Department of Health and Aged Care

Source of Metadata Extraction: https://www.aihw.gov.au/about-our-data/our-data-collections/medicare-benefits-schedule-mbs

28.07.2025

Pharmaceutical Benefits Schema Data Collection (PBS)

Purpose: The Pharmaceutical Benefits Scheme (PBS) data collection contains information on prescription medicines that qualify for a benefit under the National Health Act 1953 and for which a claim has been processed. The database comprises information about PBS scripts and payments, patients, prescribers and dispensing pharmacies. Its primary purpose is to track medicines dispensed under the PBS, including details about the types of medicines provided, the demographics of patients receiving them, the prescribers involved, and the locations of service. This data enables comprehensive monitoring of pharmaceutical service delivery throughout the country.

Main Topic: Health

Other topics:

Demographics

Subtopics:

Medicine dispensing details
Dispensing pharmacy details
Prescriber details
Service utilisation
Financial transactions
PBS Safety Net thresholds
Use of concessional entitlements
Bulk billing
Medication safety

Included into an integrated data asset:

COVID-19 Register
CWDA
NACDA
NDDA
NHDH
PLIDA

Population scope: All individuals in Australia who have been dispensed medicines subsidised under the PBS or the Repatriation Pharmaceutical Benefits Scheme (RPBS). This includes both general and concessional patients, as well as veterans and eligible dependants who access medications through the RPBS.

Geographic scope: Australia (national)

Temporal range: 1984-ongoing

Temporal Unit/Frequency: Monthly/quarterly/annually

Unit of Observation: PBS dispensing event

Type of Unit of Observation: Event/Process/Activity

Collection & Compilation Methods: The Pharmaceutical Benefits Scheme (PBS) data set is compiled from administrative claims data that are generated when approved pharmaceutical items are dispensed to patients under the PBS and Repatriation Pharmaceutical Benefits Scheme (RPBS). The process begins when a medical practitioner prescribes a PBS-listed medicine, and the prescription is subsequently filled at a pharmacy. The pharmacist submits a claim to Services Australia, in order to receive reimbursement for the subsidised portion of the medicine. Each claim record includes detailed transactional information such as the PBS item code, prescription date, dispensing date, patient category (general or concessional), prescriber details, and the amount paid by the government and the patient. Once collected by Services Australia, this transactional data is stored in a central database and processed according to quality control protocols. The raw claim data are cleaned, validated, and standardised to ensure consistency across providers, pharmacies, and jurisdictions. Services Australia is responsible for the initial compilation and maintenance of the dataset. The data are then securely transferred to the Department of Health and Aged Care, which oversees policy and program delivery relating to the PBS. Additionally, the AIHW receives curated extracts of the PBS dataset for statistical analysis and public reporting. AIHW processes the data further to generate indicators on medicine use, trends, and expenditure patterns at the population level. The dataset covers both PBS and RPBS claims, and includes prescriptions filled at community pharmacies and eligible private hospitals. However, it excludes medicines supplied in public hospitals to inpatients, as these are not generally subsidised under the PBS. The PBS dataset may also include under co-payment prescriptions—that is, prescriptions where the patient pays the full amount because the cost is below the PBS co-payment threshold—although the comprehensiveness of these records depends on the reporting arrangements in place and the time period of the data. Data compilation is performed with strict privacy and confidentiality protocols in place. Identifiers such as Medicare numbers are removed or encrypted before release to authorised data users.

Data Quality (Scope): The dataset includes nearly all prescription medicines dispensed in community settings and private hospitals under the PBS or RPBS for all Medicare-eligible Australians. It includes information on the medicine type, quantity, patient category, prescriber and pharmacy details, and cost components (such as government subsidy and patient co-payment). However, the dataset does not include medicines dispensed to public hospital inpatients, as these are funded directly by state and territory governments. It also excludes private non-PBS prescriptions, such as medications not listed on the PBS, prescriptions paid entirely out-of-pocket without any claim and medications purchased over the counter without a prescription.

Data Quality (Other): Historically, PBS data collection focused exclusively on subsidised prescriptions—that is, prescriptions where the price of the medicine exceeded the patient’s co-payment threshold, meaning the government paid a subsidy. This meant that a substantial portion of dispensed medicines, especially low-cost medications, were not included in the dataset because they were fully paid by patients and not claimed under the PBS. These are referred to as “under co-payment prescriptions.” As a result, earlier versions of the dataset underreported the total volume of medicines dispensed. After the reforms that took place in 2012 a more systematic collection of under co-payment prescription data has started. From this point onward, pharmacies began submitting information to Services Australia for all PBS-listed medicines dispensed, regardless of whether a subsidy was claimed. This significantly improved the completeness and representativeness of the dataset, particularly for analyses of medicine use patterns across the entire population. Improvements in electronic prescribing, dispensing software, and claims processing systems have reduced data entry errors and improved the consistency of coding for medicines, prescribers, and patient demographic details. Geographic and demographic variables have become more detailed over time, allowing for more refined analysis of medicine use by age group, sex, remoteness, and socio-economic status. The linkage infrastructure supporting the PBS dataset has improved, enabling integration with other national datasets such as hospital admissions, cancer registries, and mortality data.

Data Access: Publicly available data is in the electronic form and statistics.

PBS statistics: https://medicarestatistics.humanservices.gov.au/VEA0032/SAS.Web/statistics/pbs_item.html

PBS item reports: https://medicarestatistics.humanservices.gov.au/VEA0032/SAS.Web/statistics/pbs_item.html

PBS group reports https://medicarestatistics.humanservices.gov.au/VEA0032/SAS.Web/statistics/pbs_group.html

Quarterly and annual datasets for MBS and PBS expenditure and volume statistics in downloadable CSV or Excel format are available on data.gov.au. https://data.gov.au/data/dataset/pharmaceutical-benefits-scheme-pbs-statistics

AIHW reports and dashboards: Interactive tools and trend reports presenting national and regional-level PBS data by medicine class, demographic group, or expenditure. https://www.aihw.gov.au/reports-data/medicines/pharmaceutical-benefits-scheme

Geographical coverage: national, state and territory, SA4, PHN, LGA

More Information: PBS online: https://www.pbs.gov.au/pbs/home PBS downloads: https://www.pbs.gov.au/browse/downloads PBS publications: https://www.pbs.gov.au/browse/publications

Email: mbs.pbs@aihw.gov.au

Data Custodian/Owner: AIHW Australian Government Department of Health and Aged Care

Source of Metadata Extraction: https://www.aihw.gov.au/about-our-data/our-data-collections/pharmaceutical-benefits-scheme

28.07.2025

Net Overseas Migration Traveller Data (NOM)

Purpose: The purpose of the Net Overseas Migration (NOM) Traveller dataset is to support the accurate estimation of Net Overseas Migration. The dataset enables the Australian Bureau of Statistics (ABS) to classify travellers as migrants or non-migrants based on their actual behaviour—specifically, whether they spent 12 months or more in or out of Australia within a 16-month period. The dataset is essential for informing immigration and labour market policies, planning for health, education, and infrastructure, and conducting demographic research.

Main Topic: Demographics

Other topics:

Subtopics:

Arrivals to Australia
Departures from Australia
Net migration
Travel and Border movements
Information about travellers
Visa and migration type

Included into an integrated data asset:

PLIDA

Population scope: All people who cross Australia’s international borders, regardless of citizenship, residency status, or purpose of travel and who meet the 12/16-month rule

Geographic scope: Australia (national)

Temporal range: 2006-ongoing

Temporal Unit/Frequency: Quarterly

Unit of Observation: Individuals categorised as immigrants or emigrants based on the 12/16 months rule

Type of Unit of Observation: Individual; Event/Process/Activity

Collection & Compilation Methods: Administrative information about persons arriving in, or departing from, Australia is collected via various processing systems, passport documents, visa information, and incoming passenger cards. Aside from persons travelling as Australian or New Zealand citizens, persons travelling to Australia are required to provide information in visa applications. These administrative data are collected by the Department of Home Affairs under the authority of the Migration Regulations 1994 made under the Migration Act 1958. ABS statistics on overseas migration are mainly compiled using information from Home Affairs sources. All overseas movement records are stored in Home Affairs’ Travel and Immigration Processing System (TRIPS). Each month all overseas arrivals and departures (OAD) movement records and related information, including those matched to an incoming passenger card, are supplied to the ABS and then processed. This OAD data is then the main input to produce quarterly overseas migration estimates.

From July 2017, due to the removal of the outgoing passenger card, the ABS has also used Medicare enrolment data. This is a secondary source of state or territory of residence information for Australian residents and is used for a small proportion of records.

After linking records and applying the migration classification algorithm, the ABS compiles and aggregates the data to produce quarterly and annual estimates of NOM. These estimates are disaggregated by age, sex, visa type, and geographic location to support detailed demographic analysis. Throughout the process, the ABS performs data cleaning, validation, and confidentiality checks to ensure the accuracy and privacy of the data. NOM forms part of the ABS’s Person-Level Integrated Data Asset (PLIDA).

Data Quality (Scope): Net overseas migration is the net gain or loss of population through international migration to and from Australia. The NOM Traveller data set is built from a record of all international border movements into and out of Australia, provided by the Department of Home Affairs. However, Net Overseas Migration estimates only include a small proportion of these travellers, specifically, those who meet the 12/16-month rule for being classified as overseas migrant arrivals (added to the population) or departures (subtracted from the population). Most people who travel to and from Australia (such as undertaking short trips as holidays) are not included in NOM, as they do not meet the criteria for changing usual residence. The effective scope of NOM estimates is limited to long-term population-affecting travellers.

Data Quality (Other): The core movement data such as arrival and departure dates, ports, and identifiers are highly accurate because they are recorded via electronic border processing systems. However, classification of travellers into migrants or non-migrants is derived using the 12/16-month rule. This introduces a lag: migration status cannot be definitively assigned until the person’s travel history over the reference period is known. A major change in NOM estimation methodology occurred in July 2006, when the ABS replaced the former “intended length of stay” approach with the 12/16-month rule, based on actual movement behaviour. As a result, data prior to 2006 are not directly comparable with post-2006 data. Discontinuation of passenger cards in 2017, which affected the collection of self-reported data and shifted reliance fully onto administrative records.

Data Access: Publicly available statistics: https://www.abs.gov.au/statistics/people/population/overseas-migration/latest-release

TableBuilder: https://www.abs.gov.au/statistics/microdata-tablebuilder/available-microdata-tablebuilder/net-overseas-migration

Individual-level from the NOM Traveller dataset is can be accessed through the ABS DataLab, subject to strict application and approval processes

Geographical coverage: state and territories, SA4 or SA3

More Information: Measuring Net Overseas Migration in Australia https://www.abs.gov.au/articles/measuring-net-overseas-migration-australia Overseas Migration methodology: https://www.abs.gov.au/methodologies/overseas-migration-methodology

OAD statistics and related data quality issues are published on a monthly basis in Overseas Arrivals and Departures, Australia: https://www.abs.gov.au/statistics/industry/tourism-and-transport/overseas-arrivals-and-departures-australia/latest-release The following variables for overseas migration data may be made available on request: age, country of birth, country of citizenship, country of previous residence, direction of migration, category of travel (permanent departures not available from Sep quarter 2011), main reason for journey (not available for permanent movements, residents departing or visitors departing), marital status (not available from Sep quarter 2011 or for Australian and New Zealand citizens), reference quarter/year (available from Dec quarter 2003), sex, state or territory of residence, status (preliminary or final), visa applicant type (primary or secondary applicant - available from Sep quarter 2011), visa subclass (includes separate groups for Australian citizens and NZ citizens).

Data Custodian/Owner: ABS

Source of Metadata Extraction: https://data.gov.au/data/dataset/net-overseas-migration-financial-years/resource/0e5d0901-ebb4-4739-b1af-c74fde7089a4

29.07.2025

Archived on 08.12.2025: https://data.gov.au/data/dataset/net-overseas-migration-financial-years/resource/0e5d0901-ebb4-4739-b1af-c74fde7089a4

Australian Immunisation Register (AIR)

Purpose: The key objective of the Australian Immunisation Register (AIR) data set is to provide a national, de identified record of vaccinations administered in Australia. It supports surveillance and monitoring of vaccine coverage across the population, including specific age milestones, geographic areas, and demographic groups (e.g. Indigenous status); public health research and program evaluation, especially in relation to coverage trends, immunisation equity, and the effectiveness of vaccination strategies.

Main Topic: Health

Other topics:

Demographics

Subtopics:

Vaccination events
Vaccination provided under the National Immunisation Program (NIP) or outside it School-based program indicator (e.g. HPV vaccine)
Program-specific vaccinations (e.g. COVID-19, Japanese encephalitis
Vaccination setting

Included into an integrated data asset:

COVID-19 Register
NHDH
PLIDA

Population scope: Originally established as the Australian Childhood Immunisation Register in 1996, to record data on vaccinations provided to children aged up to 7 years, the register was expanded in 2016 to include data for people of all ages.

Geographic scope: Australia (national)

Temporal range: 1996-ongoing

Temporal Unit/Frequency: Date of vaccination/weekly

Unit of Observation: A single vaccine dose given to an individual

Type of Unit of Observation: Event/Process/Activity

Collection & Compilation Methods: The Australian Immunisation Register (AIR) collects and compiles detailed information on vaccinations administered to individuals of all ages in Australia. The register is maintained by Services Australia and serves as the national source of immunisation records, initially established for childhood vaccinations in 1996 and expanded to include all age groups from 2016. Data collection occurs at the point of vaccination, where immunisation providers record each immunisation event. The recorded details typically include the vaccine brand and type, dose number, date of administration, and demographic information such as the individual’s name, date of birth, sex, and Medicare number (if available). Vaccination records are submitted to the AIR primarily through electronic channels. Most providers use integrated clinical software that transmits data automatically to the AIR via secure electronic interfaces. Providers without integrated systems may enter data directly through the AIR secure web portal or upload files in bulk, especially in the case of school-based or public health programs. Each vaccination event is linked to a unique individual AIR record, which is created or matched using identifiers such as Medicare number, name, and date of birth.

Once submitted, vaccination data are centrally stored by Services Australia in the AIR system. The system applies automated validation processes to check for completeness, logical consistency, and duplication. For example, it ensures that vaccine products match expected schedule requirements and that duplicate entries are flagged or resolved. Where records cannot be fully verified or matched, follow-up or manual correction may be required.

The AIR updates on an ongoing basis, with vaccination events being processed and stored in near real-time. For secondary use, such as research and public health analysis, the AIHW receives de-identified extracts from the AIR on a periodic basis, such as quarterly or annually. These extracts are then used to compile immunisation coverage statistics, inform policy evaluations, and, where permitted, are linked with other national health datasets including hospital admissions, mortality records, and Medicare claims.

The AIR is included in AIHW Data Collections and PLIDA.

Data Quality (Scope): It is a national, whole-of-population register which aims to capture all vaccinations given to Australians, regardless of age. Reporting to the AIR became mandatory for all vaccines under the NIP in 2021. Prior to this, coverage for some non-NIP vaccines was lower due to voluntary reporting. The childhood schedule (0–5 years) has near-complete reporting due to long-standing program incentives and policy links (e.g. “No Jab, No Pay”)

Data Quality (Other): Core vaccination data—such as vaccine type, date of administration, dose number, and age—is generally highly accurate, as it is submitted directly by healthcare providers via electronic medical records or web portals. Demographic fields (e.g. Indigenous status, Medicare status, postcode) may be missing or outdated for some records, particularly for adults and those not enrolled in Medicare

Data Access: Data is available for research purposes at detailed aggregate and unit record levels under terms and conditions that ensure compliance with the relevant legislation under which the collection has been made. A range of aggregate data has been made available on the Internet for public use.

Tables published on the internet. Data available includes: national historical conscientious objection by calendar year - 1999 to current; state and territory historical conscientious objection by calendar year - 2012 to current, current coverage data (for all children and for Aboriginal and Torres Strait Islander children only), and historical coverage data (for all children and for Aboriginal and Torres Strait Islander children only).

For individual-level data, researchers can request data under the DATA Scheme via Dataplace. However, not all AIHW data holdings are eligible to be shared under the DATA Scheme.

More information about the DATA Scheme is available here: https://www.datacommissioner.gov.au/

More Information: As of 2018 the HPV vaccination register was transferred to the AIR along with records of other school-based immunisation programs. Reporting of adult vaccinations to the AIR was mandated in July 2021 for vaccinations provided under the National Immunisation Program, for influenza and for covid-19, and in December 2022 for Japanese encephalitis virus vaccines. Reporting of other vaccinations is not mandatory.

Immunisation https://www.health.gov.au/topics/immunisation/when-to-get-vaccinated/national-immunisation-program-schedule

Childhood immunisation https://www.health.gov.au/node/38782/childhood-immunisation-coverage

Email: immunisation@aihw.gov.au

Data Custodian/Owner: AIHW Department of Health and Aged Care

Source of Metadata Extraction: https://www.aihw.gov.au/about-our-data/our-data-collections/australian-immunisation-register-de-identified-dat

29.07.2025

National Health Survey (NHS)

Purpose: The National Health Survey (NHS) is usually collected every three years and is designed to provide a range of information about the health of Australians. It provides data such as prevalence of chronic and long-term health conditions, self-reported health status and health risk factors. This information can be cross classified by selected demographic and socioeconomic characteristics.

Main Topic: Health

Other topics:

Demographics

Subtopics:

Self-rated overall health
Long-term conditions
Tobacco
Alcohol consumption
Diet
Physical activity
Medication use
Psychological distress
Healthcare needs

Included into an integrated data asset:

PLIDA

Population scope: All usual residents in Australia aged 0+ years living in private dwellings

Geographic scope: Australia (national)

Temporal range: 1989- ongoing (the latest release is 2022-2023)

Temporal Unit/Frequency: Irregular, 3-4 years cycle

Unit of Observation: Individual person

Type of Unit of Observation: Individual

Collection & Compilation Methods: Data collection methods include: face-to-face interviews with ABS interviewers who are using a Computer Assisted Interview (CAI) system. Households can complete the first part of the survey, which collected basic demographic information about all usual residents of the household via an online form, telephone interview or face-to-face interview with an ABS Interviewer. The individual questionnaires were completed via face-to-face interview only. Some modules are self-completed, especially those related to sensitive topics (e.g. mental health, sexual health, drug use).

Stratified multistage random sampling ensures national and regional representation.

Since 1995, and more systematically from 2011–12, nurses or trained staff collected: height and weight (for BMI); waist circumference; blood pressure.

Self-reported data include: diagnosed conditions, lifestyle behaviours, mental health and general wellbeing.

With consent, ABS links NHS data to: Medicare Benefits Scheme (MBS); Pharmaceutical Benefits Scheme (PBS) and provides validation and richer datasets for analysis.

As only a sample of people in Australia are surveyed, results need to be converted into estimates for the whole population. This is done through a process called weighting. Each person or household is given a number (known as a weight) to reflect how many people or households they represent in the whole population. A person or household’s initial weight is based on their probability of being selected in the sample. For example, if the probability of being selected in the survey was one in 45, then the person would have an initial weight of 45 (that is, they would represent 45 people). The person and household level weights are then calibrated to align with independent estimates of the in-scope population, referred to as ‘benchmarks’. The benchmarks use additional information about the population to ensure that: people or households in the sample represent people or households that are similar to them; the survey estimates reflect the distribution of the whole population, not the sample.

Data Quality (Scope): The scope of the survey included: all usual residents in Australia aged 0 years and over living in private dwellings; both urban and rural areas in all states and territories, except for very remote parts of Australia and discrete Aboriginal and Torres Strait Islander communities; members of the Australian permanent defence forces living in private dwellings and any overseas visitors who have been working or studying in Australia for the last 12 months or more, or intend to do so.

The following people were excluded: visitors to private dwellings; overseas visitors who have not been working or studying in Australia for 12 months or more, or do not intend to do so; members of non-Australian defence forces stationed in Australia and their dependants; non-Australian diplomats, diplomatic staff and members of their households; people who usually live in non-private dwellings, such as hotels, motels, hostels, hospitals, nursing homes and short-stay caravan parks (people in long-stay caravan parks, manufactured home estates and marinas are in scope); people in Very Remote areas; discrete Aboriginal and Torres Strait Islander communitie; households where all Usual Residents are less than 18 years of age.

Data Quality (Other): Changes in data collection may reduce comparability with earlier data. Specifically, COVID019 forced a shift to telephone interviews and reduced sample size in 2021-2022 The 2022 NHS is considered to be comparable with the 2017–18 NHS and previous cycles. Consequently, the 2022 NHS cannot be compared to the 2020-2021 survey.

Additionally, topic changes over the years may also have implications for this data set. For example, health service use, carer identification, food security, stressors were not collected in 2022.

Data Access: Microdata access via ABS TableBuilder, Microdata Download, or DataLab, including NHS cycles from 2011–12 through 2022 https://www.abs.gov.au/statistics/microdata-tablebuilder/available-microdata-tablebuilder/national-health-survey

Basic microdata – approved users can download and analyse unit record data in their own environment. This product is available for NHS cycles from 1977-78 to 2017-18. For more information, see the MicrodataDownload page.

Detailed microdata - approved users can access DataLab for in-depth and interactive data analysis using a range of statistical software packages. This product is available for NHS cycles 2001 to 2022

Data is available at SA1, SA2, SA3 and SA4 levels

More Information: File structure: Datasets from the NHS are hierarchical in nature. A hierarchical data file is an efficient means of storing and retrieving information which describes one to many, or many to many, relationships. For example, a person may report multiple days on which alcohol was consumed and multiple types of alcoholic beverages on each of these days.

Data about households and families are contained as individual characteristics on person records. While estimates are also available at the household level, estimates at the family level are not available from this survey. The data items and related output categories are described in Excel spreadsheets from the Data Item Lists section: https://www.abs.gov.au/statistics/microdata-tablebuilder/available-microdata-tablebuilder/national-health-survey#data-item-lists

Summary of the earlier results: https://www.abs.gov.au/statistics/health/health-services/national-health-survey-summary-results NHS : State and Territory Findings, 2022 https://www.abs.gov.au/statistics/health/health-conditions-and-risks/national-health-survey-state-and-territory-findings/latest-release

Integration of the 2017-2018 NHS and the Personal Linkage Spine : https://www.abs.gov.au/articles/integration-2017-18-national-health-survey-and-personal-linkage-spine

Email : client.services@abs.gov.au

Data Custodian/Owner: ABS

Source of Metadata Extraction: https://www.abs.gov.au/statistics/health/health-conditions-and-risks/national-health-survey/latest-release

30.07.2025

Archived on 08.12.2025: https://www.abs.gov.au/statistics/health/health-conditions-and-risks/national-health-survey/latest-release

Death Registrations

Purpose: The purpose of the Death Registrations data set in the Person-Level Integrated Data Asset (PLIDA) is to enable population-level analysis of mortality outcomes by linking individual death records to a wide range of administrative and demographic data. This data set provides detailed information on deaths registered in Australia, including the date and cause of death, and is integrated with other modules within PLIDA. By linking death registrations to socio-economic, health, and service data, the Death Registry module supports research and evaluation into the social determinants of mortality, the impact of health and welfare policies, and patterns of premature death in specific populations.

Main Topic: Demographics

Other topics:

Subtopics:

Age at death
Sex
Indigenous status
State and territory of usual residence and registration
Mortality statistics
Cause of death

Included into an integrated data asset:

NDDA
PLIDA

Population scope: The ABS Death Registrations collection includes all deaths that occurred and were registered in Australia, including deaths of persons whose place of usual residence was overseas.

Geographic scope: Australia (national)

Temporal range: 1912-ongoing (2023 is the most recent one)

Temporal Unit/Frequency: Annually

Unit of Observation: A single registered death

Type of Unit of Observation: Event/Process/Activity

Collection & Compilation Methods: The registration of deaths is the responsibility of the Australian states and territories Registries of Births, Deaths and Marriages (RBDMs). Deaths occurring in “other territories” of Australia are registered by RBDMs in one of the eight states and territories. The exception to this is deaths occurring on Norfolk Island which are registered by the Norfolk Island Registry of Births, Deaths and Marriages which sits within the Norfolk Island Regional Council. Deaths for “other territories” are included in the death statistics for Australia.

As part of the registration process, information about the cause of death is supplied by the certifying medical practitioner or by a coroner. Other information about the deceased is supplied by a relative or other person acquainted with the deceased, or by an official of the institution where the death occurred. The information is provided to the ABS by individual registries for coding and compilation into the National Mortality dataset. In addition, the ABS supplements this data with information made available via the National Coronial Information System (NCIS).

Information is collected using a death registration form, which includes: personal details of the deceased (e.g. name, sex, age, usual residence); cause of death (completed by a medical practitioner or coroner); additional demographic variables (e.g. Indigenous status, birthplace), and informant relationship and details.

The ABS complies the data obtained from the RBDMs and codes the causes of death to an international standard, called the International Statistical Classification of Diseases and Related Health Problems (ICD).

The Death Registrations data set is included in PLIDA.

Data Quality (Scope): The current scope includes: all deaths being registered for the first time; deaths in Australia of temporary visitors to Australia; deaths occurring within Australian Territorial waters; deaths occurring in Australian Antarctic Territories or other external territories (including Norfolk Island); deaths occurring in transit (i.e. on ships or planes) if registered in the Australian state or territory of ‘next port of call’; deaths of Australian Nationals overseas who were employed at Australian legations and consular offices (i.e. deaths of Australian diplomats while overseas) where able to be identified; deaths that occurred in earlier reference periods that have not been previously registered (late registrations).

The scope of the statistics excludes: repatriation of human remains where the death occurred overseas; deaths of foreign diplomatic staff in Australia (where these can be identified); stillbirths/fetal deaths.

Data Quality (Other): In compiling death statistics, the ABS implements quality control measures to ensure the accuracy of the Death Registrations collection. However, some known issues remain. Due to system-related delays at the Victorian Registry, 2,812 death registrations from 2017–2019 were not previously provided to the ABS. These are now included in the 2019 reference year, as they fall within scope. Additionally, 1,864 deaths registered in Victoria from 2013–2016 were only supplied in 2021. Because they fall outside the five-year reporting window, they are excluded from 2021 totals but are included in occurrence-based tables. Death statistics are generally based on the year of registration, not the year of occurrence. Delays between a death and its registration mean some deaths, especially those in November and December, are registered in the following year.

The number of registered deaths of Aboriginal and Torres Strait Islander people are included for all jurisdictions. However, detailed disaggregation’s of deaths of Aboriginal and Torres Strait Islander people are provided only for New South Wales, Queensland, South Australia, Western Australia and the Northern Territory. These five states and territories have evidence of a sufficient level of Indigenous identification and numbers of deaths of Aboriginal and Torres Strait Islander people to support mortality analysis. There are several data collection forms on which people are asked to state whether they or the persons for whom they are reporting are Aboriginal and/or Torres Strait Islander. However, the results are not always consistent, the main reason being the changes in identification. Identification levels vary across datasets, jurisdictions and time.

Data Access: Published annually through the Deaths, Australia statistical release, which includes mortality statistics up to the most recent completed calendar year (2023) https://www.abs.gov.au/statistics/people/population/deaths-australia

Some data are also accessible through data cubes (in Microsoft Excel spreadsheet format) via the ABS website, e.g. Deaths, Country of Birth, Australia, 2023; Median age at death, Year of occurrence, States and territories, 2013 to 2023; Deaths, Summary, Statistical Area Level 4, 2011 to 2023

ABS microdata products: The Mortality, Enhanced Characteristics microdata file is available via ABS MicrodataDownload or within ABS DataLab to approved users. It contains linked unit-record information such as age at death, sex, Indigenous status, cause of death, and key demographics based on the 2011 Census https://www.abs.gov.au/statistics/microdata-tablebuilder/available-microdata-tablebuilder/mortality-enhanced-characteristics-australia

The Death Registrations module in PLIDA can be accessed through ABS DataLab for approved research projects https://www.abs.gov.au/about/data-services/data-integration/integrated-data/person-level-integrated-data-asset-plida. Approved users can apply for microdata. More information is available here: Microdata and TableBuilder | Australian Bureau of Statistics

Data on deaths are available by the following geographies: Australia, states and territories, SA2, SA4, LGA, Remoteness Areas, Indigenous Remoteness Areas.

More Information: Deaths, Australia methodology: https://www.abs.gov.au/methodologies/deaths-australia-methodology/2023

Causes of death, Australia methodology: https://www.abs.gov.au/methodologies/causes-death-australia-methodology/2023

The National Mortality Database (NMD) maintained by AIHW is directly derived from the Death Registrations data collected by the ABS. https://www.aihw.gov.au/about-our-data/our-data-collections/national-mortality-database

Data Custodian/Owner: ABS State and Territory Registrars of Births, Deaths and Marriages (RBDMs)

Source of Metadata Extraction: https://www.abs.gov.au/statistics/people/population/deaths-australia/latest-release

31.07.2025

Archived on 08.12.2025: https://www.abs.gov.au/statistics/people/population/deaths-australia/latest-release

Tertiary Collection of Student Information (TCSI)

Purpose: Tertiary Collection of Student Information (TCSI) (former the Higher Education Information Management System (HEIMS)) data set is compiled by the Australian Government Department of Education through mandatory electronic submissions from approved higher education providers. All higher education providers that are approved under the Higher Education Support Act 2003 (HESA) are required to report data for the Higher Education Data Collection.

Main Topic: Childcare, education, and training

Other topics:

Demographics

Subtopics:

Student field of education and course level
Enrolment status
Campus location
Course completion
Commonwealth assistance and HELP loans
Staff information

Included into an integrated data asset:

PLIDA

Population scope: All students and staff affiliated with approved Australian higher education providers who are required to report under the Higher Education Support Act 2003

Geographic scope: Australia (national)

Temporal range: 2005-2020 (before 2021, HEIMS)

Temporal Unit/Frequency: Annually

Unit of Observation: Individual student; interaction with the higher education system

Type of Unit of Observation: Individual; Event

Collection & Compilation Methods: Tertiary Collection of Student Information (TCSI) data set is compiled by the Australian Government Department of Education through mandatory electronic submissions from approved higher education providers. All higher education providers that are approved under the Higher Education Support Act 2003 (HESA) are required to report data for the Higher Education Data Collection.

Submissions are made several times annually and include detailed student-level data on enrolments, course structures, completions, Commonwealth-supported places, and financial assistance such as HELP loans. Once submitted, the data undergoes further automated and manual quality assurance checks by the Department to ensure accuracy and compliance with national data standards. After validation, data is compiled and aggregated for use in public statistical releases, government accountability reporting, and research.

The Higher Education Information Management System (HEIMS) data set is maintained by the Australian Government Department of Education and its primary purpose is to collect, manage, and report comprehensive data about students, courses, staff, and completions in the Australian higher education sector.

HEIMS data is integrated in PLIDA.

Data Quality (Scope): The data quality scope is generally high, as it is a comprehensive, mandatory administrative collection managed by the Australian Government Department of Education. All approved higher education providers are legally required to submit standardised data under the Higher Education Support Act 2003. The scope covers full-time, part-time, domestic, international, Commonwealth-supported, and fee-paying students across all recognised higher education providers in Australia. The data set covers only students enrolled in, which means that informal learning, unaccredited courses, and some private sector activity are excluded.

Data Quality (Other): Some data items (e.g. course classification codes, citizenship status categories, or study load definitions) have evolved over time. While TCSI has robust validation mechanisms at the point of submission, errors may still occur, particularly in the classification of students (e.g. domestic vs. international), courses, or units of study. These may reflect provider-level variations in interpretation or administrative practices. While most core fields are mandatory, certain optional data items (e.g. disability status or language spoken at home) may suffer from underreporting or missingness due to non-response or inconsistent collection practices at the provider level. TCSI data are compiled and verified after the end of each calendar year, meaning there is typically a 6–12 month delay before the finalised dataset is released. This affects the timeliness of trend analyses.

Data Access: Data is available in the form of Statistics publications; Datasets; Tabulations; Analyses prepared for clients; Reports.

Individual-level data is available, but only within a secure research environment.

De-identified unit record data from TCSI is included in the PLIDA (Person-Level Integrated Data Asset) Modular Product and can be accessed through the Australian Bureau of Statistics (ABS) DataLab. This access is granted to approved researchers who are affiliated with authorised institutions.

To use the DataLab, researchers must submit a detailed project proposal, complete Safe Researcher training, and receive approval for access to specific PLIDA modules. All work must be conducted within the secure DataLab environment, and any outputs require clearance by ABS before release.

More Information: Prior 2021 data was submitted via the Higher Education Provider Client Assistance Tool (HEPCAT). Prior 2021, the Higher Education Information Management System (HEIMS) was in place.

Higher Education Statistics https://www.education.gov.au/higher-education-statistics

Data reported from the student collection include: course information including level, field of education and special course flag; age (date of birth); gender; citizenship; Aboriginal and Torres Strait Islander indicator;location of term residence; location of permanent home residence; basis for admission to course; type of attendance (full-time / part-time); mode of attendance (internal, external, multi-modal); country of birth; language spoken at home; year of arrival in Australia; tertiary entrance score; equity data (Disability, Low-SES, NESB, Women in non-traditional areas, Regional/Remote); highest educational attainment prior to commencement; and award course completions.

Data element dictionary: https://www.tcsisupport.gov.au/element

Email: microdata.access@abs.gov.au University-Statistics@education.gov.au

Data Custodian/Owner: Australian Government Department of Education

Source of Metadata Extraction: https://www.education.gov.au/higher-education-statistics/student-data

01.08.2025

Archived on 08.12.2025: https://www.education.gov.au/higher-education-statistics/student-data

National Study of Mental Health and Wellbeing (NSMHW)

Purpose: The National Study of Mental Health and Wellbeing (NSMHW) is a component of the wider Intergenerational Health and Mental Health Study. The main aims of the NSMHW are to provide information in five key areas: How many Australians have mental disorders?; What is the impact of these disorders?; How many people have used services and what are the key factors affecting this?; Are services making a difference to the lives of people experiencing problems with their mental health?; How many Australians have a lived experience of suicide and what services have they used?

Main Topic: Health

Other topics:

Demographics

Subtopics:

Lifetime and 12-month prevalence of selected mental disorders
Level of impairment for these disorders
Health services used for mental health problems, such as consultations with health practitioners or visits to hospital
Suicidality and self-harm behaviours
Disordered eating

Included into an integrated data asset:

PLIDA

Population scope: All usual residents in Australia aged 16–85 years living in private dwellings Urban and rural areas in all states and territories, excluding Very Remote parts of Australia and discrete Aboriginal and Torres Strait Islander communities.

Geographic scope: Australia (national)

Temporal range: 1997-2022

Temporal Unit/Frequency: Irregular

Unit of Observation: Individual person

Type of Unit of Observation: Individual

Collection & Compilation Methods: Data for the NSMHW was collected in the Survey of Health and Wellbeing (SHWB) which was conducted by the Australian Bureau of Statistics (ABS). The first cohort was conducted between December 2020 and July 2021. The second cohort was conducted between December 2021 and October 2022.

Cohort 1 of the study was collected over an 8-month period from 5 December 2020 to 31 July 2021. Cohort 2 of the study was collected over an 11-month period from 4 December 2021 to 31 October 2022. The majority of households were required to complete a survey face-to-face with an ABS Interviewer. Interviews were conducted during periods when circumstances in individual jurisdictions permitted face-to-face interviewing according to relevant jurisdictional public health orders and restrictions. During the collection of Cohort 2, 446 households (4.3% of Cohort 2 fully responding households) completed the survey via a video call with an ABS Interviewer.

Information collected in the study includes:

Household Information, which was completed by any responsible adult in the household aged 18 years or over. The Household Information component of the study collected basic demographic information about all usual residents of the household, including those aged under 15 years, as well as information about the dwelling and household income.

Individual Questionnaire, which was completed by one randomly selected person in the household aged 16–85 years. The random selection was automatically performed upon completion of the Household Form.

The study was designed to provide lifetime prevalence estimates for mental disorders by asking respondents about experiences throughout their lifetime. 12-month diagnoses were derived based on lifetime diagnosis and the presence of symptoms of that disorder in the 12 months prior to the survey interview. The full diagnostic criteria were not assessed within the 12-month timeframe.

The study included mental disorders that: were expected to affect more than 1% of the population; were able to be diagnosed through the WMH-CIDI 3.0; were likely to be identified through a household survey.

The WMH-CIDI 3.0 was also used to collect information on: the onset of symptoms and mental disorders; the recency of symptoms and mental disorders; the persistence or duration of symptoms and mental disorders; the impact of mental disorders on home management, work life, relationships, and social life; treatment-seeking and access to helpful treatment.

Due to the sensitivity of some content, the mental health component of the study was conducted on a voluntary basis.

The Cohort 1 and Cohort 2 sample have been combined to create a 2020–2022 dataset.

Data Quality (Scope): The scope of the study included: all usual residents in Australia aged 16–85 years living in private dwellings; both urban and rural areas in all states and territories, except for Very Remote parts of Australia and discrete Aboriginal and Torres Strait Islander communities.

The study excluded the following people: visitors to private dwellings, overseas visitors who have not been working or studying in Australia for 12 months or more, or do not intend to do so, members of non-Australian defence forces stationed in Australia and their dependants, non-Australian diplomats, diplomatic staff, and members of their households, people who usually live in non-private dwellings, such as hotels, motels, hostels, hospitals, nursing homes and short-stay caravan parks (people in long-stay caravan parks, manufactured home estates and marinas are in scope). people in Very Remote areas, discrete Aboriginal and Torres Strait Islander communities.

The exclusion of people living in Very Remote areas and discrete Aboriginal and Torres Strait Islander communities is unlikely to impact national estimates. It will only have a minor impact on any aggregate estimates produced for individual states and territories, except the Northern Territory where the excluded population accounts for around 21% of people.

The exclusion of residents in special dwellings (e.g., hotels, boarding houses, and institutions) and homeless people means the results are likely to underestimate the prevalence of mental disorders in the Australian population.

Data Quality (Other): For the 2020–22 wave, some variables (e.g. medication use) were sourced from PBS administrative data, improving objectivity and reducing reporting bias. Questionnaire and procedures were extensively tested with input from clinical, academic, and statistical experts. Potential underreporting of symptoms, substance use or suicidal intentions due to stigma. People with severe mental illness, or cognitive impairment, may be underrepresented if they are less able or willing to participate.

Data Access: Microdata access via ABS TableBuilder https://www.abs.gov.au/statistics/microdata-tablebuilder/available-microdata-tablebuilder/national-study-mental-health-and-wellbeing Available downloads: NSMHW and Follow up Study 2020-2023 Detailed Microdata (DataLab) data item list; NSMHW 2020-2022 and 2021-22 Detailed Microdata (DataLab) data item list; NSMHW 2020-2022 TableBuilder data item list; NSMHW 2020-21 Detailed Microdata (DataLab) data item list; 2007 SMHWB Detailed Microdata (DataLab) data item list; 2007 SMHWB Basic and Expanded Microdata (DataLab) data item list.

Basic CURF available only for the 1997 and 2007 survey waves Detailed microdata - approved users can access DataLab for in-depth and interactive data analysis using a range of statistical software packages.

Data is available at state and territory, SA4.

More Information: The study used the World Mental Health Survey Initiative version of the World Health Organization’s (WHO) Composite International Diagnostic Interview, version 3.0 (WMH-CIDI 3.0).

A group of ABS officers were trained in the use of the WMH-CIDI 3.0 by WHO accredited trainers. These officers then provided training to experienced ABS interviewers, as part of a comprehensive four-day training program, which also included sensitivity training and field procedures.

While most of the study was based on the WMH-CIDI 3.0, modules such as Health Service Utilisation were designed in consultation with subject matter experts from academic institutions and staff from the Department of Health and Aged Care. New study content was tested by the ABS.

Methodology: https://www.abs.gov.au/methodologies/national-study-mental-health-and-wellbeing-methodology/2020-2022

Archive releases: https://www.abs.gov.au/AUSSTATS/abs@.nsf/Lookup/4326.0Main+Features11997?OpenDocument The Standard for Sex, Gender, Variations of Sex Characteristics and Sexual Orientation Variables, 2020 https://www.abs.gov.au/statistics/standards/standard-sex-gender-variations-sex-characteristics-and-sexual-orientation-variables/2020

National Study of Mental Health and Wellbeing: Follow up Study https://www.abs.gov.au/articles/national-study-mental-health-and-wellbeing-follow-study

Data Custodian/Owner: ABS

Source of Metadata Extraction: https://www.abs.gov.au/statistics/health/mental-health/national-study-mental-health-and-wellbeing/latest-release

04.08.2025

Archived on 08.12.2025: https://www.abs.gov.au/statistics/health/mental-health/national-study-mental-health-and-wellbeing/latest-release

Australian Cancer Database (ACD)

Purpose: The Australian Cancer Database (ACD) contains records of primary, malignant cancers diagnosed in Australia since 1 January 1982. It serves as the only comprehensive national source of cancer incidence data. Data from the ACD are used to report on national cancer statistics such as incidence, trends, projections, survival and prevalence.

Main Topic: Health

Other topics:

Demographics

Subtopics:

Cancer incidence
Cancer type and classification
Tumour characteristics
Date of diagnosis and time since diagnosis

Included into an integrated data asset:

Population scope: All individuals diagnosed with a primary, malignant cancer in Australia from 1 January 1982 onward, excluding most non-melanoma skin cancers (basal cell carcinoma and squamous cell carcinoma).

Geographic scope: Australia (national)

Temporal range: 1982-ongoing

Temporal Unit/Frequency: Annually

Unit of Observation: Individual cancer case

Type of Unit of Observation: Event/Process/Activity

Collection & Compilation Methods: The ACD is compiled at the AIHW from cancer data provided by state and territory cancer registries through the Australasian Association of Cancer Registries. These population-based cancer registries receive information on cancer diagnoses from a variety of sources, such as: hospitals, pathology laboratories, radiotherapy centres, and registries of births, deaths and marriages.

ACD is the only repository of national cancer incidence data. AIHW undertakes standardisation, coding harmonisation, de-duplication of inter-state cases, and removes duplicates when individual cancer cases appear in more than one registry.

Data collection and coding practices are standardised when state and territory data are compiled into a single, national database. This is done through the following quality control measures at the AIHW: notifying and adjusting the data for variations in coding procedures; identifying and eliminating potential errors in the data; and undertaking a de-duplication of the ACD so that duplicate records of cases recorded in more than one registry are removed.

The database includes only the first primary malignant cancer diagnosis per individual, excluding recurrences or metastases, and it began with data from 1 January 1982. Reporting coverage expanded over time to include some in situ and benign neoplasms from the early 2000s.

Data Quality (Scope): The ACD has very high coverage of cancers in Australia. It includes all age groups, both sexes, Indigenous and non-Indigenous Australians, and people residing in every region. It is important to note that some non-melanoma skin cancers (basal and squamous cell carcinomas of the skin) are excluded. While they are common, they are not consistently reported nationally, so they are excluded from the ACD.

Data Quality (Other): The ACD includes mandatory cancer notifications from all state and territory cancer registries. It is nearly complete for all primary, malignant cancer cases diagnosed in Australia since 1982. Variables are generally well defined and standardised. Cancer diagnoses are coded using the ICD-O-3 and mapped to ICD-10 groupings. This ensures variables like cancer site, morphology, and behaviour are consistent across all jurisdictions and over time. Variables are described in detail through the METeOR metadata registry and AIHW technical documents. Each variable has clearly defined formats, value ranges, and reference classifications (e.g. SEIFA, ASGS for geography). Some variables such as staging data are not routinely available across all years and cancer types.

Data Access: The AIHW website provides extensive cancer incidence and mortality data that can be downloaded without charge. The main online data product is Cancer data in Australia: https://www.aihw.gov.au/reports/cancer/cancer-data-in-australia/contents/summary, which is updated every year.

The main published report is Cancer in Australia, which is produced in odd-numbered years. This and other reports can be downloaded from the AIHW website without charge.

The AIHW is able to make available a broad range of cancer statistics subject to a scientific and ethical review process. A customised data request can be lodged by using a link below:

Data on request - Australian Institute of Health and Welfare. Further enquiries can be made by contacting the AIHW Cancer Data and Monitoring Unit on (02) 6244 1000 or via email to cancer@aihw.gov.au. Data requests are charged for on a cost-recovery basis.

The ACD is also available for data linkage projects. Such projects must be approved by the AIHW Ethics Committee as well as the data custodians of the state and territory cancer registries and jurisdictional ethics committees.

Geographical coverage: national, state and territory, SA1, SA2, SA3, SA4, SEIFA.

More Information: National Cancer Statistics Clearing House: https://www.aihw.gov.au/about-our-data/our-data-collections/australian-cancer-database/ncsch

National Centre for Monitoring Cancer: https://www.aihw.gov.au/about-our-data/our-data-collections/australian-cancer-database/ncmc

Cancer Statistics for Small Geographic Areas: https://www.aihw.gov.au/reports/cancer/cancer-statistics-for-small-geographic-areas/contents/about

Health system expenditure on cancer and other neoplasms in Australia, 2015–16: https://www.aihw.gov.au/reports/cancer/health-system-expenditure-cancer-other-neoplasms/summary

Email: cancer@aihw.gov.au

Data Custodian/Owner: AIHW State and Territory Cancer Registries

Source of Metadata Extraction: https://www.aihw.gov.au/about-our-data/our-data-collections/australian-cancer-database/about-australian-cancer-database

04.08.2025

Public Dental Waiting Times National Minimum Dataset (PDWT NMDS)

Purpose: The Public Dental Waiting Times (PDWT NMDS) national minimum data set enables reporting on the length of time that adults aged 18 years and over wait for public dental care in Australia, and the characteristics of patients who receive care or who were listed for care in a reference period. The dataset is designed to support monitoring of waiting times by state and territory and to understand patient characteristics such as age, sex/gender, Indigenous status, and socio-economic status. It enables consistent national reporting on delays specifically for general or prosthetic dental services within public dental schemes and informs service planning and policy.

Main Topic: Health

Other topics:

Demographics

Subtopics:

Access to public dental care
Waiting times for public dental care
Health service delivery

Included into an integrated data asset:

Population scope: Adults aged 18 years and over who are eligible for public general or prosthetic dental care and who were placed on a waiting list for such care during the reporting period

Geographic scope: Australia (national)

Temporal range: 2013 - ongoing (2023 is the most recent)

Temporal Unit/Frequency: Annually

Unit of Observation: Waiting list entry for an individual

Type of Unit of Observation: Event/Process/Activity

Collection & Compilation Methods: The Public Dental Waiting Times National Minimum Data Set (PDWT NMDS) is compiled from administrative data routinely collected by state and territory public dental services in Australia. It includes information about adults aged 18 years and over who are placed on public dental waiting lists for general or prosthetic care under government-funded dental schemes. The data collection focuses on three key dates: when an individual is placed on a waiting list, when they are offered care, and when they attend their first dental visit.

Each jurisdiction collects and submits data annually to the AIHW according to standardised NMDS specifications, which define the data elements, coding structure, and inclusion criteria. Individuals seen under emergency-only care, priority arrangements, or private payment are excluded.

Once submitted, the data are compiled by AIHW into national summary statistics, such as median and 90th percentile waiting times by jurisdiction and demographic group. Although only aggregate data are published publicly, the methodology is designed to enable consistent reporting and comparability across jurisdictions, supporting national monitoring of access and equity in public dental care.

Data Quality (Scope): The scope of the data collection is all people eligible for their state or territory public dental scheme, who were aged 18 years or over when they were placed on a general or prosthetic public dentistry waiting list for the purpose of receiving treatment.

The data collection includes: all people specified above with a listing date for dental care within the collection period, all people specified above with a date of offer of dental care within the collection period, all people specified above with a date of first dental visit within the collection period.

The data collection excludes: people who access their local public dental clinic but pay full price and are not eligible for their state or territory’s public dental service, people who are treated under jurisdictional priority client schemes (which can be the majority of clients treated in some jurisdictions), treatments which do not result in removal from a waiting list, such as: relief of pain that does not satisfy other dental treatment needs, emergency treatment that does not satisfy other dental treatment needs.

Data Quality (Other): Each state and territory manages its own public dental programs, which may differ in eligibility criteria, prioritisation policies, data systems, and service delivery models. This can affect the comparability of waiting time data across jurisdictions. There may be inconsistencies in how listing dates, offer dates, and first visit dates are recorded. Similarly, completeness and accuracy of demographic variables depends on how consistently this information is collected and reported by individual dental services. While the dataset includes adults (18+) eligible for public dental care, it excludes emergency-only patients, those treated under priority access arrangements (e.g. First Nations Australians), and private-pay clients. Because the dataset is structured around waiting list events rather than individuals, people with multiple entries in a year may appear more than once.

Data Access: Publicly available data includes publications, summary tables published in electronic form.

Client specified tables are available on request.

Restricted unit record access subject to Ethics Committee approval and/or the agreement of all relevant data custodians in all states and territories (charges may apply).

Geographical coverage: national, states and territories.

More Information: Oral health and dental care in Australia https://www.aihw.gov.au/reports/dental-oral-health/oral-health-and-dental-care-in-australia/contents/summary

Dental and oral health https://www.aihw.gov.au/reports-data/health-conditions-disability-deaths/dental-oral-health/overview

Email: dental@aihw.gov.au

Data Custodian/Owner: AIHW

Source of Metadata Extraction: https://www.aihw.gov.au/about-our-data/our-data-collections/public-dental-waiting-times

05.08.2025

Hospital Casemix Protocol Data Collection (HCP)

Purpose: The purpose of the Hospital Casemix Protocol (HCP) Data Collection is to provide detailed, standardised information on privately insured admitted patient hospital episodes in Australia. HCP data is used to inform policy development, support the Medical Costs Finder app, and assist the Independent Health and Aged Care Pricing Authority in calculating the national efficient price (NEP) for hospital services, which guides Australian Government funding for public hospitals. It also serves as a valuable resource for research and evaluating healthcare services.

Main Topic: Health

Other topics:

Demographics

Subtopics:

Clinical casemix
Hospital charges
Health insurer and Medicare benefits
Patient out-of-pocket expenses
Medical services

Included into an integrated data asset:

Population scope: The population scope of the HCP Data Collection includes all admitted patient separations for which private health insurers have paid benefits in both public and private hospitals across Australia.

Geographic scope: Australia (national)

Temporal range: 2010- ongoing (2024 is the latest)

Temporal Unit/Frequency: Collected monthly (aggregated to financial year for regular reporting)

Unit of Observation: Admitted patient separation

Type of Unit of Observation: Event

Collection & Compilation Methods: Private health insurers collect HCP data.

Hospitals, including day facilities, initially upload their HCP data to Data Submission Portal (DSP) for data validation.

Once the files are validated, hospitals upload them to individual health insurer portals. They must submit data every month, within 6 weeks of a patient being discharged. Hospitals are using nationally defined HCP data specifications. Hospitals and insurers are expected to follow standard coding systems (e.g., ICD-10-AM, ACHI, DRGs), ensuring consistent classification of diagnoses and procedures.

Health insurers then submit the data to DSP within 20 weeks of the end of the reporting month. The data is stored in the Enterprise Data Warehouse.

Data Quality (Scope): The data set covers all hospital separations (admissions and discharges) for which a benefit was paid by a private health insurer, across both public and private hospitals. Only admissions with private health insurance claims are included, uninsured and public-only admissions are excluded.

Data Quality (Other): Data may vary in completeness depending on hospital reporting practices and insurer compliance. Some variables (e.g., clinical complexity, comorbidities) may be under-reported due to claim-focussed rather than clinical-focussed data capture. Episodes without a benefit paid (e.g., full out-of-pocket) are not captured. Overall, the HCP dataset covers about 87% of privately insured episodes recorded in the AIHW National Hospital Morbidity Database (NHMD). Coverage varies by diagnosis-related group (AR DRG), especially for low volume AR DRGs where completeness is lower.

Data Access: The AIHW provides aggregate summary tables, reports, and interactive dashboards based on HCP data. These outputs show trends in hospital charges, insurer benefits, and patient costs but do not include individual-level data. For more detailed breakdowns such as custom tables you can request data via AIHW’s “Data on Request” service.

Researchers can request new tables within the HCP dataset if the required data are not publicly available. Access is governed by the Five Safes framework and may incur a minimum cost.

If applicant needs de identified individual records or data linkage, a formal request must be submitted.

Some HCP data might be available under the DATA Scheme which is a legal framework that allows accredited users (e.g., university researchers) to access Commonwealth data for public-interest research.

More information about data access strategy is available here: https://www.health.gov.au/topics/health-data-and-medical-research/data-strategy

More Information: Hospital Casemix Protocol data collection* https://www.aihw.gov.au/about-our-data/our-data-collections/hospital-casemix-protocol-hpc-data-collection

HCP annual report 2023-2024 https://www.health.gov.au/resources/publications/hcp-annual-report-2023-24?language=en

Data Custodian/Owner: AIHW Department of Health, Disability and Ageing

Source of Metadata Extraction: https://www.aihw.gov.au/about-our-data/our-data-collections/hospital-casemix-protocol-hpc-data-collection

05.08.2025

Disability, Ageing and Carers (Survey of) (SDAC)

Purpose: The main aims of the Disability, Ageing and Carers (Survey of) (SDAC) are to provide information on: people with disability, people aged 65 and over, and primary carers of people with disability.

The purpose of the SDAC is to enable government departments and community groups to plan for the future and develop relevant policies. The size and distribution of groups eligible for assistance under different program legislation is used by the Department of Health and Ageing, and Department of Families, Housing, Community Services and Indigenous Affairs as the basis for allocating and distributing program funds to State governments, and by State and Territory departments for service planning and fund distribution.

Main Topic: Community services

Other topics:

Health
Demographics

Subtopics:

Long-term health conditions
Need for and receipt of assistance for persons with disability or aged 65 years and over
The use of aids to help manage a person’s disability
Experiences of violence, abuse and neglect of people with disability or aged 65 years and over
Accessibility issues and discrimination experienced by people with disability
Primary carers’ need for and access to support in their caring role
For primary carers, the impact of their caring role on their health, wellbeing and employment
Access to health services and satisfaction with level of social participation for all target populations
Demographic and socio-economic characteristics of all people in the survey.

Included into an integrated data asset:

NDDA
PLIDA

Population scope: Australian residents who live in private dwellings and selected non-private dwellings and belong to one or more the groups below: people with disability, older people (65+), and primary carers of people with disability

Geographic scope: Australia (national)

Temporal range: 1981- ongoing (the latest release is 2022-2023)

Temporal Unit/Frequency: Point in time, irregular

Unit of Observation: Individual person

Type of Unit of Observation: Individual

Collection & Compilation Methods: The 2022 Survey of Disability, Ageing and Carers (SDAC) was the tenth in the national series conducted by the Australian Bureau of Statistics, following surveys in 1981, 1988, 1993, 1998, 2003, 2009, 2012, 2015, and 2018. The 2022 survey was conducted between June 2022 and February 2023, collecting data from approximately 13,700 households and 1,100 cared-accommodation establishments across Australia.

Data was collected through two components based on type of residence: the household component and the cared-accommodation component. The household component covered people living in private dwellings such as houses, flats, townhouses, apartments, and self-care units in retirement villages. Households were randomly selected, and data was collected via an online questionnaire, face-to-face interview, or a combination of both. The cared-accommodation component included individuals residing for three months or more in hospitals, nursing homes, hostels, in the 2022 survey also disability group homes with fewer than six residents (previously included in the household sample). Health establishments were invited via online form to confirm eligibility, with a higher chance of selection given to those with more long-term residents. If selected, a designated staff member completed the survey on behalf of sampled residents between 5 July and 6 September 2022.

In the household component, information was collected about all usual residents and the dwelling by a responsible adult. Screening questions identified people with disability and carers. Those with disability, people aged 65 and over, and identified primary carers completed personal interviews, with proxy interviews conducted where necessary (e.g. for children under 15, young people whose guardians declined participation, or individuals unable to respond due to illness, disability, language, or absence). For people under 65 without disability or caring responsibilities, basic demographic and lifestyle information was collected by proxy.

Two sensitive topics: (1) primary carer attitudes and experiences, and (2) experiences of violence, abuse and neglect among people aged 65+ and people with disability aged 18+ were collected via self-completed forms (paper or secure online section).

The cared-accommodation component collected a more limited range of information than the household component, reflecting the suitability of questions for proxy completion by establishment staff.

A long-term health condition is defined as an illness, injury, or disability that has lasted, or is expected to last, six months or more. Conditions reported in the 2022 SDAC were classified using an updated version of the International Classification of Diseases, 10th Revision (ICD-10). A concordance between the 2022 and 2018 classification systems is available.

As the household component is based on a sample survey, results were converted into population estimates using weighting. Each person or household was assigned a weight reflecting how many others they represent, based on their probability of selection. These weights were then calibrated to population benchmarks to ensure representativeness, aligning estimates to the September 2022 estimated resident population of 25,433,431 people and 10,029,883 households, excluding those in non-private dwellings, very remote areas, and discrete Aboriginal and Torres Strait Islander communities.

Data Quality (Scope): All usual residents in Australia aged 0 years and over living in private dwellings, self-care retirement villages, or health establishments that provide long-term cared accommodation (for at least three months).

The following people were excluded: visitors to private dwellings and self-care retirement villages, non-Australian diplomats, diplomatic staff and members of their households, members of non-Australian defence forces (and their dependents) stationed in Australia, overseas visitors who have not been living in Australia for 12 months or more, or do not intend to do so, people who usually live in hotels, motels, short-stay caravan parks, religious or educational institutions, hostels for the homeless or night shelters, gaols or correctional institutions, staff quarters, guest houses or boarding houses, people in very remote areas, discrete Aboriginal and Torres Strait Islander communities, and people living in households where all usual residents are less than 15 years of age.

Data Quality (Other): Some demographic details such as about language, visa, education etc. were completed by one adult from household. Similarly, staff members in care facilities were completing the survey on behalf of the residents introducing a potential bias.

In 2022, around 27% of primary carers and 34% of eligible older adults or people with disability did not complete these questions. While non-response did not significantly bias results for the carer topic, there was a statistically significant lower response rate from males to the violence and abuse questions, warranting caution in interpreting these data. Proxy interviews are conducted when respondents are under 15, aged 15–17 without guardian consent, or unable to respond due to illness, disability, language barriers, or unavailability. Proxy responses may introduce bias, particularly for subjective or sensitive topics (e.g. wellbeing, carer burden, discrimination). As a sample survey, estimates are subject to sampling error. 2022 SDAC introduced mixed-mode collection: some respondents completed the survey online, others via face-to-face interview, or a combination. Differences in mode can affect how people respond to questions (e.g. privacy, comprehension, willingness to disclose sensitive information)

Data Access: Publicly available summary statistics can be accessed for free on the ABS website. These include key findings and aggregated tables from the latest survey.

Data downloads https://www.abs.gov.au/statistics/health/disability/disability-ageing-and-carers-australia-summary-findings/2022#data-downloads The ABS offers de-identified individual-level data through TableBuilder. This platform allows registered institutional users, such as universities and government agencies, to analyse a wide range of variables using a secure online interface. The data includes individual-level responses but is subject to confidentiality protections and output restrictions.

More detailed individual-level data is available through the ABS DataLab. Access to DataLab requires submitting a formal research proposal. DataLab users can analyse more granular variables, including extended demographic, geographic, and health-related information not available in TableBuilder.

Simpler BAS https://www.ato.gov.au/businesses-and-organisations/preparing-lodging-and-paying/business-activity-statements-bas/goods-and-services-tax-gst/gst-reporting-methods?=redirected_simplerBASreporting&anchor=SimplerBAS#SimplerBAS

Data is available at SA2, SA3 and SA4 levels as well state and territoriy

More Information: Disability, Ageing and Carers, Australia: Summary of Findings https://www.abs.gov.au/statistics/health/disability/disability-ageing-and-carers-australia-summary-findings/latest-release

Disability and Carer resources: https://www.health.gov.au/topics/disability-and-carers/resources

Email : microdata.access@abs.gov.au

Data Custodian/Owner: ABS

Source of Metadata Extraction: https://www.abs.gov.au/AUSSTATS/abs@.nsf/DSSbyCollectionid/4926CFF764B65A25CA256BD000288447

07.08.2025

Archived on 08.12.2025: https://www.abs.gov.au/AUSSTATS/abs@.nsf/DSSbyCollectionid/4926CFF764B65A25CA256BD000288447

ABS Business Register (ABSBR)

Purpose: The purpose of the ABS Business Register (ABSBR) is to serve as the central statistical register of businesses in Australia, maintained by the Australian Bureau of Statistics (ABS). It provides a reliable and up-to-date frame for business surveys, supports the production of official economic and industry statistics, and enables longitudinal and structural analysis of the Australian business population.

The ABS Business Register provides a frame for most ABS economic surveys to enable a consistent, coherent, point-in-time picture of the Australian economy. Data is extracted from the ABS Business Register on a quarterly basis, producing the “Common Frame”. Subsequently, survey frames are extracted from the Common Frame and supplied to various areas of the ABS on cyclical intervals.

Main Topic: Employment, income, taxation, wealth, and consumption

Other topics:

Organisational characteristics

Subtopics:

Business structure
Business size (measured by employment and/or turnover)
Business type (company, sole trader, partnership, etc.)
Geographic location (state/territory, postcode, SA2/SA4 levels)
Status and activity (active/inactive, start and end dates)
Institutional sector (e.g. private non-financial corporations, general government)
Employment indicator
Turnover indicator

Included into an integrated data asset:

LEED

Population scope: All organisations, with an active ABN on the ABR, undertaking productive activity in Australia

Geographic scope: Australia (national)

Temporal range: 2003- ongoing (the latest update –2025)

Temporal Unit/Frequency: Monthly/annually

Unit of Observation: Business entity

Type of Unit of Observation: Organisation; Geographic area

Collection & Compilation Methods: The ABS Business Register (ABSBR) is compiled and maintained by the Australian Bureau of Statistics using administrative data sourced primarily from the Australian Business Register (ABR), which is maintained by the Australian Taxation Office. The ABS receives regular updates from the ABR, including information on Australian Business Numbers (ABNs), business structure, location, and industry classification. However, the ABS applies a series of refinements and classifications to ensure that the register is suitable for statistical purposes.

To be included in the ABSBR, businesses must meet criteria indicating economic significance, such as being registered for Goods and Services Tax (GST), having employees, or meeting a turnover threshold. These filters are applied to remove non-trading or inactive entities that may be present in the broader ABR. In addition, the ABSBR applies a hierarchical structure to the data, organising businesses into Enterprise Groups, Legal Entities, and Type of Activity Units (TAUs) to reflect the way businesses operate and report economically. Each unit is classified using the Australian and New Zealand Standard Industry Classification (ANZSIC) system and linked to geographic and size indicators.

Administrative data collected quarterly or annually for Australian Business Number (ABN) registrations recorded in the Australian Business Register (ABR), and business data from the Australian Tax Office (ATO) The ABSBR also links and classifies entities into structured units such as Enterprise Groups, Legal Entities, and Type of Activity Units (TAUs), allowing complex businesses to be accurately represented in official statistics. It supports consistent measurement of business demographics (such as size, industry, and location), and provides a robust platform for designing ABS business surveys and for constructing integrated data assets like BLADE.

Data Quality (Scope): The ABSBR is derived from the broader Australian Business Register (ABR) but is refined by the Australian Bureau of Statistics to include only those entities that are considered economically significant. These are generally businesses registered for Goods and Services Tax (GST), those with employees, or those meeting turnover thresholds. As a result, the ABSBR excludes dormant entities, self-managed super funds, and other ABN holders not engaging in economic activity. It offers near-complete coverage of active businesses across all industries, sectors, and regions of Australia that are relevant to economic measurement. However, because some small or non-employing businesses may not register for GST or may operate below the turnover threshold, there may be limited under-coverage of microbusinesses or sole traders that are economically active but fall outside inclusion rules.

Excludes: Reserve Bank of Australia, General Government, and Non-Profit Institutions Serving Households.

Data Quality (Other): One key consideration is the accuracy of industry coding, which is based on self-reported information provided to the Australian Business Register (ABR). While the ABS applies validation and reclassification procedures errors or outdated classifications can still affect the accuracy of ANZSIC codes, particularly for small businesses. Timeliness is another consideration. Although the register is updated monthly, there can be delays in the reflection of changes such as new business registrations, cancellations, mergers, or structural adjustments. Finally, the ABSBR is not intended to include all entities with an ABN, but only those deemed economically active. As a result, it does not capture the entire universe of legal business entities in Australia.

Data Access: The ABS Business Register (ABSBR) is not publicly available as a standalone dataset due to confidentiality and privacy restrictions. It is maintained internally by the Australian Bureau of Statistics and used primarily as a statistical frame for business surveys and the production of official statistics. Researchers and government users cannot access unit-level data from the ABSBR directly.

However, selected aggregated outputs derived from the ABSBR, such as business counts by industry, geography, or size, are published by the ABS in statistical releases like Counts of Australian Businesses. https://www.abs.gov.au/statistics/economy/business-indicators/counts-australian-businesses-including-entries-and-exits

In some cases, de-identified and structured ABSBR-derived data may be integrated into secure environments such as BLADE, where access is strictly controlled and subject to approvals through the ABS DataLab.

Geographic coverage: national, states and territories, SA2, and LGA.

More Information: Methodology https://www.abs.gov.au/methodologies/counts-australian-businesses-including-entries-and-exits-methodology/jul2020-jun2024

Email: business.statistics@abs.gov.au

Data Custodian/Owner: ABS

Source of Metadata Extraction: https://www.abs.gov.au/ausstats/abs@.nsf/dossbytitle/AC79D33ED6045E88CA25706E0074E77A

08.08.2025

Archived on 08.12.2025: https://www.abs.gov.au/ausstats/abs@.nsf/dossbytitle/AC79D33ED6045E88CA25706E0074E77A

Business Activity Statement (BAS)

Purpose: The purpose of the Business Activity Statement (BAS) dataset is to provide detailed and reliable financial information about businesses’ activity across the Australian economy. Originally collected by the Australian Taxation Office (ATO) for taxation compliance purposes, this data is integrated into the ABS’s BLADE environment to support economic research, productivity analysis, and evidence-based policy development.

The BAS dataset enables longitudinal analysis of business performance, allowing tracking of revenue, expenses, and input costs over time at the firm level. It supports studies on firm dynamics such as entry and exit, growth, survival, and responses to economic shocks or policy changes. For policymakers, the dataset helps evaluate the effectiveness of tax and business regulations, understand industry trends, and design targeted support measures for small and medium-sized enterprises.

Main Topic: Employment, income, taxation, wealth, and consumption

Other topics:

Subtopics:

Total sales and turnover
Goods and Services Tax (GST)
Export sales
Capital purchases
Non-capital purchases
PAYG instalments
PAYG withholding
Other taxes and credits

Included into an integrated data asset:

BLADE
LEED (indirectly, via ATO)

Population scope: All businesses in Australia that are registered for the Goods and Services Tax (GST)

Geographic scope: Australia (national)

Temporal range: 2001-02- ongoing

Temporal Unit/Frequency: Quarterly/monthly/annually

Unit of Observation: Business entity

Type of Unit of Observation: Organisation

Collection & Compilation Methods: The Business Activity Statement (BAS) dataset is compiled using administrative data collected by the ATO. All businesses registered for the Goods and Services Tax (GST) in Australia are required to lodge BAS forms at regular intervals depending on their turnover and business structure. These forms are submitted electronically or via paper, and they contain detailed financial information such as total sales, GST collected and paid, purchases, wages (if applicable), and other tax obligations like PAYG instalments or fringe benefits tax.

Once received by the ATO, the data is processed and stored in secure systems for compliance and tax administration. For statistical use, the ABS receives an extract of this administrative data. The BAS data is then linked by the ABS to other datasets within the BLADE, using the Australian Business Number (ABN) as a common identifier.

The ABS applies additional data cleaning, validation, and transformation procedures to ensure consistency across time and comparability between businesses. This includes adjustments for missing records, aligning financial periods, and linking each BAS record to the ABS business structure.

Data Quality (Scope): The data quality scope of the BAS dataset is generally high due to its administrative origin and mandatory nature. Since BAS lodgement is a legal requirement for businesses registered for GST or PAYG obligations, the dataset captures a large and consistent portion of the active business population in Australia. It provides near-complete coverage of medium and large businesses, and a significant share of small businesses that meet or voluntarily opt into reporting thresholds.

However, the scope does not include businesses that are not registered for GST or PAYG, such as micro-businesses below the reporting threshold, informal or unregistered enterprises, and non-operational entities. Additionally, while the dataset includes detailed financial information, it does not contain business demographic or structural characteristics on its own.

Data Quality (Other): The dataset may not be directly comparable across all businesses or time periods without adjustment. Differences in reporting frequency (monthly, quarterly, annually) require harmonisation. Additionally, interpretation of BAS items may vary slightly between businesses, especially for capital purchases and GST allocations.

Businesses may lodge amended statements or report late, which can introduce revisions and affect the completeness or stability of data over short time frames. The timing and accuracy of lodgements can vary more significantly among small businesses. Incomplete lodgement or missing fields for certain tax items may require imputation or cleaning during processing.

From 2017-18 financial year, businesses with GST turnover less than $10 million are no longer obligated to report some items on BAS (e.g. capital purchases, export sales which may require some harmonisation.

Data Access: While some aggregated statistics is available in the form of publications, e.g. https://www.abs.gov.au/statistics/economy/business-indicators/monthly-business-turnover-indicator/latest-release, the BAS dataset is not publicly available in raw form due to its origin as confidential administrative data collected by ATO. Access is restricted and governed by strict confidentiality and privacy protections. Researchers can access the BAS dataset through the Australian Bureau of Statistics (ABS) as part of the Business Longitudinal Analysis Data Environment (BLADE). Access is provided via the ABS DataLab, a secure on-site or virtual environment for accredited researchers with approved projects.

More Information: Business Activity Statement Guide https://cehl.com.au/wp-content/uploads/2024/06/0323-Business-Activity-Statement-Guide.pdf

Explanatory documents about BASS from ATO https://www.ato.gov.au/businesses-and-organisations/preparing-lodging-and-paying/business-activity-statements-bas

Data Custodian/Owner: ABS

Source of Metadata Extraction: https://www.abs.gov.au/about/data-services/data-integration/integrated-data/business-longitudinal-analysis-data-environment-blade/blade-data-and-legislation#data-in-blade

08.08.2025

Archived on 08.12.2025: https://www.abs.gov.au/about/data-services/data-integration/integrated-data/business-longitudinal-analysis-data-environment-blade/blade-data-and-legislation#data-in-blade

Pay As You Go (PAYG)

Purpose: The Pay As You Go (PAYG) payment summary data provide employer-reported information on employees and wages, derived from reports lodged with the Australian Taxation Office. The dataset captures workforce size and wage outlays over time, offering a consistent administrative view of employment and labour costs across Australian businesses

PAYG data are useful for monitoring labour market conditions, studying employer hiring and wage-setting behaviour, and assessing how businesses respond to economic shocks or policy changes. They support analysis of employment growth and decline, job stability, industry and regional labour demand, and the distribution of wages across firms.

Main Topic: Employment, income, taxation, wealth, and consumption

Other topics:

Organisational characteristics

Subtopics:

PAYG withholding liabilities by entity type (summary over recent years)
PAYG instalments by entity type (summary over recent years)
PAYG withholding distribution by industry, entity type, and type of withholder (detailed, longer time series)
PAYG instalments distribution by industry and entity type (detailed, longer time series)

Included into an integrated data asset:

BLADE
LEED
PLIDA

Population scope: All entities in Australia that are registered for, and report under, the Pay As You Go (PAYG) withholding and/or PAYG instalments system to the Australian Taxation Office

Geographic scope: Australia (national)

Temporal range: 2001-02- ongoing

Temporal Unit/Frequency: Annually

Unit of Observation: Business entity

Type of Unit of Observation: Organisation

Collection & Compilation Methods: The Pay As You Go (PAYG) dataset in BLADE is sourced from the Australian Taxation Office (ATO) and contains information collected under the Taxation Administration Act 1953. Employers are legally required to report payments made to employees and certain contractors through the PAYG withholding system.

Historically, this reporting was undertaken via annual PAYG payment summaries lodged with the ATO, detailing total payments and tax withheld for each worker. Since the introduction of Single Touch Payroll (STP) from 2018, and its mandatory adoption for most employers from July 2021, payroll information has been reported directly to the ATO each pay cycle.

For BLADE, the historical series remains based on annual payment summary data, with more recent years increasingly supplemented or replaced by STP-derived aggregates. The population covered by the dataset comprises all Australian employing businesses that withhold tax from payments to workers, excluding entities not required to report under PAYG rules.

The ATO supplies the PAYG payment summary dataset to the Australian Bureau of Statistics (ABS) for statistical purposes, authorised under the Census and Statistics Act 1905. Before integration into BLADE, personally identifiable information is removed or de-identified to protect confidentiality. The ABS undertakes data cleaning and validation, which includes edit checks to identify missing or inconsistent entries, correction of invalid records, and removal of outliers such as implausible wage amounts or employee counts. Variables are standardised across reference years to ensure consistent formats, field names and classifications. Each record is matched to the ABS Business Register using Australian Business Numbers (ABNs) or other identifiers, enabling linkage to other administrative and survey datasets in BLADE, such as Business Activity Statements (BAS), Business Income Tax (BIT) data and STP records.

The processed data is then compiled annually to create a time series covering financial years from 2001–02 to 2022–23. In BLADE, the PAYG dataset is primarily represented at the business level, containing annual aggregates such as the total number of employees and total wages paid.

Data Quality (Scope): The dataset represents the entire reporting population of entities with PAYG obligations for each financial year. This provides very high coverage for the intended population, essentially all registered employers and entities required to make PAYG instalments in Australia. For businesses without employees, coverage depends on whether they are required to make PAYG instalments toward their income tax. Many sole traders, partnerships, trusts, and companies that generate taxable income are included via the PAYG instalments system. This means the dataset does not include every Australian Business Number (ABN) ever issued, but it does cover nearly all active, income-generating businesses that meet PAYG reporting requirements. The proportion of the overall business population represented will be slightly less than 100 percent because non-employing microbusinesses with no instalment obligations are outside the scope.

Data Quality (Other): The quality is dependent on the accuracy and completeness of the information reported to the ATO. Late lodgements, amendments to payment summaries or instalment activity statements, and reporting errors can result in revisions to previously published figures. The ATO applies validation and processing checks to ensure internal consistency, but the statistics reflect the data as lodged, and some discrepancies or misclassifications may remain. In particular, the allocation of entities to industries and entity types is based on ATO registration and reporting information, which may not always match their current operational status.

Data Access: The PAYG statistics dataset is publicly available in aggregated form through the ATO’s website as part of the annual Taxation Statistics release. The publicly released tables include national-level figures for PAYG withholding and PAYG instalments, broken down by entity type, industry classification, and type of withholder. No microdata or identifiable business-level information is released.

The aggregated tables can be freely accessed online without registration, downloaded in spreadsheet format, and reused subject to standard ATO copyright and attribution conditions. Historical tables from earlier editions of Taxation Statistics are also available for time-series analysis.

Microdata from the underlying PAYG payment summaries and instalment activity statements is not publicly available due to confidentiality provisions in the Taxation Administration Act 1953 and the Privacy Act 1988.

Access to these detailed records is restricted to approved projects conducted within secure environments such as the ABS DataLab, where PAYG data forms part of integrated datasets like BLADE. Such access requires formal approval from both the ABS and the data custodians, adherence to the Five Safes framework, and the application of statistical disclosure controls.

More Information: Pay as you go statistics for Taxation statistics 2022–23 https://www.ato.gov.au/about-ato/research-and-statistics/in-detail/taxation-statistics/taxation-statistics-2022-23/?page=63

PAYG Table 1 (Data.gov) Taxation Statistics 2022-23 - PAYG - Table 1 - Data.gov.au

PAYG withholding liabilities by entity type (summary table, three years): https://www.ato.gov.au/uploadedFiles/Content/CR/downloads/taxstats/Taxation-statistics-2022-23-table-18.xlsx

PAYG instalments by entity type (summary table, three years) https://www.ato.gov.au/uploadedFiles/Content/CR/downloads/taxstats/Taxation-statistics-2022-23-table-19.xlsx

AYG withholding by broad industry and entity type (detailed table, long time series) https://www.ato.gov.au/uploadedFiles/Content/CR/downloads/taxstats/Taxation-statistics-2022-23-table-20.xlsx

PAYG withholding by type of withholder and broad industry (detailed table, long time series): https://www.ato.gov.au/uploadedFiles/Content/CR/downloads/taxstats/Taxation-statistics-2022-23-table-21.xlsx

PAYG instalments by broad industry and entity type (detailed table, long time series https://www.ato.gov.au/uploadedFiles/Content/CR/downloads/taxstats/Taxation-statistics-2022-23-table-22.xlsx

Data Custodian/Owner: ABS

11.08.2025

Archived on 08.12.2025: https://www.abs.gov.au/about/data-services/data-integration/integrated-data/business-longitudinal-analysis-data-environment-blade/blade-data-and-legislation#data-in-blade

ASIC Insolvency Data (ASIC)

Purpose: The purpose of the ASIC Insolvency data iis to provide a consistent record of Australian companies that enter formal insolvency or external administration processes, including liquidation, voluntary administration, restructuring, and related appointments. It documents key insolvency events and their timing, creating an authoritative source for tracking business distress and exit over time.

The data help identify and characterise business exit and financial distress events. This enables researchers and policymakers to examine patterns in corporate failure across industries, regions, and periods, and to assess how insolvency trends shift with broader economic conditions.

Purpose in BLADE: ASIC Insolvency Data (ASIC) provides a consistent, event-based record of Australian business that enter formal insolvency or external administration procedures.

Main Topic: Employment, income, taxation, wealth, and consumption

Other topics:

Organisational characteristics

Subtopics:

Type of insolvency event
Event dates
Jurisdiction and administration details
Event outcomes

Included into an integrated data asset:

BLADE

Population scope: Australian-registered companies that have entered a formal insolvency process and have been recorded by the ASIC in its insolvency registers for the relevant financial years

Geographic scope: Australia (national)

Temporal range: 2000-01- ongoing

Temporal Unit/Frequency: Annually

Unit of Observation: Business entity

Type of Unit of Observation: Organisation

Collection & Compilation Methods: The ASIC Insolvency data in BLADE is sourced from the Australian Securities and Investments Commission’s (ASIC) administrative records of companies entering formal insolvency processes such as external administration, liquidation, receivership, or voluntary administration.

Collection begins with ASIC’s statutory role under the Corporations Act 2001 to receive and maintain registers of insolvency events. Insolvency practitioners, such as administrators and liquidators, are required to lodge prescribed forms and reports with ASIC when appointed and as the administration progresses. These lodgements contain information such as company identifiers, type of insolvency event, appointment and cessation dates, and sometimes details of assets, liabilities, and causes of failure.

AB) receives extracts of these ASIC insolvency records under a data supply agreement. The transfer includes company identifiers that enable ABS to link the insolvency events to the ABS Business Register, which is the central linkage spine in BLADE.

Once at the ABS, the data undergoes standard processing and compilation for integration into BLADE. This includes validation checks for completeness and consistency of key fields (e.g., ensuring event dates are valid, company identifiers match active or historical business records), standardisation of variable formats, and mapping of insolvency event categories to consistent codes across years. Duplicates or overlapping records for the same company and event are resolved.

The final integrated dataset is structured at the business (enterprise) level and linked longitudinally, so insolvency events can be analysed in relation to other BLADE modules.

Data Quality (Scope): Coverage is high for the intended population because all Australian-registered companies that enter formal insolvency processes are legally required under the Corporations Act 2001 to lodge relevant forms with ASIC. This ensures that the dataset captures virtually all corporate insolvency events for the period covered.

Data Quality (Other): The quality of the data depends on the accuracy and completeness of lodgements submitted by insolvency practitioners. Errors can occur due to late reporting, incomplete forms, or inconsistencies in the way event types and dates are recorded. ASIC applies validation checks on lodgements, but the information is self-reported by administrators and may contain gaps or inaccuracies.

Linking quality depends on the accuracy of identifiers such as the Australian Company Number (ACN) and company name. Misreported or missing identifiers can lead to unmatched records, although the ABS uses multiple matching strategies to minimise linkage error.

Data Access: No aggregated insolvency tables from the BLADE version of the data are routinely published by ABS, although ASIC publishes separate, high-level insolvency statistics on its own website for public use.

Researchers must submit a project proposal that is assessed under the ABS Five Safes framework and must obtain approval from both the ABS and the data custodian (ASIC). Only the variables approved for that project are made available in the DataLab workspace. All analytical outputs undergo confidentiality and disclosure control checks by ABS staff before they can be released.

More Information: Item list: Identifier - deidentified CAN; Integration version; (internal ABS reference) Time series ID ; (last 2 digits of end year in a financial year); The quarter of the insolvency appointment; The calendar month of the insolvency appointment; Type of insolvency appointment; Effective date of insolvency appointment.

Insolvency statistics (ASIC): https://www.asic.gov.au/about-asic/corporate-publications/statistics/insolvency-statistics/#s1-2

ASIC Annual Report 2023-2024 https://download.asic.gov.au/media/nwridckz/asic-annual-report-2023-24_full.pdf

ASIC gazette https://www.asic.gov.au/about-asic/corporate-publications/asic-gazette/

Email: info@mydata.abs.gov.au

Data Custodian/Owner: ABS

12.08.2025

Archived on 08.12.2025: https://www.abs.gov.au/about/data-services/data-integration/integrated-data/business-longitudinal-analysis-data-environment-blade/blade-data-and-legislation#data-in-blade

Business Income Tax (BIT) filings

Purpose: The purpose of the Business Income Tax (BIT) is to provide a comprehensive, standardised source of annual financial information about Australian businesses drawn from their annual income tax returns. BIT covers major business entity types, including companies, trusts, partnerships, and sole traders, and includes detailed items reported for tax purposes, such as income, deductions/expenses, taxable profit or loss, and selected balance sheet components.

BIT filings support assessment of business financial position and performance over time, including profitability, financial stress indicators, and structural characteristics by industry and business type.

Purpose in BLADE: Business Income Tax (BIT) filings as a core financial module provides consistent, longitudinal measures of business income, expenses, and balance sheet items for Australian businesses.

Main Topic: Employment, income, taxation, wealth, and consumption

Other topics:

Organisational characteristics

Subtopics:

Total and gross income from sales of goods and services
Investment income
Rent
Royalties
Cost of sales
Labour expenses
Interest expenses
Depreciation
Net profit or loss
Tax payable and other taxation-related amounts

Included into an integrated data asset:

BLADE
LEED

Population scope: Australian businesses and organisations that are required to lodge an income tax return with ATO for the relevant financial year

Geographic scope: Australia (national)

Temporal range: 2001-02-ongoing

Temporal Unit/Frequency: Annually

Unit of Observation: Business entity

Type of Unit of Observation: Organisation

Collection & Compilation Methods: The Business Income Tax (BIT) dataset in BLADE is compiled from administrative data collected by the ATO under the Taxation Administration Act 1953. Each year, businesses in Australia that are required to lodge an income tax return submit detailed financial information to the ATO, including income, expenses, and, for some entities, asset and liability details. There are four main types of businesses that report annual income tax; these are partnerships and partners; companies; individuals; and trusts and beneficiaries.

The ATO provides these tax return records to the ABS under the Census and Statistics Act 1905. Within the ABS, the BIT data undergoes processing to ensure quality and usability in BLADE. This includes validation checks to identify missing or inconsistent entries, correction of errors, and standardisation of variables across financial years so that time-series analysis is possible. The records are linked to the ABS Business Register via ABNs and other identifiers, which allows BIT to be integrated with other BLADE datasets such as Business Activity Statement (BAS) data, Pay As You Go (PAYG) employment data, and Single Touch Payroll (STP) data.

Data Quality (Scope): Coverage is very high for the intended population because the dataset includes all entities required to lodge an income tax return in Australia. This means it effectively captures the full population of tax-reporting businesses for each financial year, with no sampling error. The quality of the data depends on the accuracy and completeness of lodgements provided to the ATO, as well as the correctness of identifiers that allow records to be matched to the ABS Business Register.

Data Quality (Other): Potential quality issues may arise from late lodgements, amended returns, or reporting errors in tax forms. The ATO applies its own validation and compliance processes, and the ABS undertakes additional quality checks, including edits for consistency, outlier detection, and standardisation of variables across years. However, the figures reflect the data as lodged and may contain some residual inconsistencies or misclassifications.

The dataset is longitudinal from 2001–02 onwards, but comparability across time can be affected by changes in tax form design, reporting thresholds, or accounting standards. Entity classification (e.g., industry coding) comes from the ABS Business Register rather than the tax form, which can improve comparability but also introduces dependency on the accuracy of ABS’s business profiling.

Data Access: Aggregated BIT statistics at the business level are not published by the ABS.

The researchers must use DataLab access for any type of analysis. Access is granted on a project-by-project basis and requires approval from both the ABS and the data custodian (the ATO), as well as compliance with the Five Safes framework.

More Information: Business and professional items schedule instructions 2024 https://www.ato.gov.au/forms-and-instructions/business-and-professional-items-schedule-2024-instructions?utm_

Email: info@mydata.abs.gov.au

Data Custodian/Owner: ABS

11.08.2025

Archived on 08.12.2025: https://www.abs.gov.au/about/data-services/data-integration/integrated-data/business-longitudinal-analysis-data-environment-blade/blade-data-and-legislation#data-in-blade

Intellectual Property Longitudinal Research Data (IPLORD)

Purpose: Purpose of the Intellectual Property Longitudinal Research Dataset (IPLORD) is to provide researchers with an applicant activity-centric view of Australian IP right filings. IPLoRD leverages IPGOD data to provide a history of an applicant’s filings over time broken down by financial year. Where available, the ABN of the applicant is provided to allow linkage with other government research datasets. IPLoRD makes it possible for economists and other researchers to examine relationships between the filer’s economic circumstances and their intellectual property portfolio.

Purpose in BLADE: IPLORD provides longitudinal information on intellectual property (IP) activity by Australian businesses. When linked into BLADE, it allows researchers to examine relationships between business innovation, IP rights, financial performance, employment, exports, and other firm-level characteristics.

Main Topic: Employment, income, taxation, wealth, and consumption

Other topics:

Demographics

Subtopics:

Types of intellectual property rights, including patents, trade marks, designs and plant breeder’s rights
Application and registration details such as filing dates, examination results, registration status, renewal events and expiry dates
Classification details
Legal and administrative status changes over time

Included into an integrated data asset:

BLADE

Population scope: Applicants who have filed for or held registered intellectual property rights in Australia since the beginning of record-keeping for each IP type, as maintained by IP Australia

Geographic scope: Australia (national)

Temporal range: 2001-02- ongoing

Temporal Unit/Frequency: Daily/annually

Unit of Observation: Intellectual property right

Type of Unit of Observation: Object

Collection & Compilation Methods: The Intellectual Property Longitudinal Research Data (IPLORD) dataset is compiled from administrative systems operated by IP Australia for patents, trade marks, designs and plant breeder’s rights. Data collection begins when an applicant files for an intellectual property right with IP Australia. Information is captured directly from the official registers maintained under the relevant Australian legislation. Each register records details such as applicant names and addresses, filing and registration dates, classification codes, legal status changes, and renewal events. Registers are updated continually as applications progress through examination, granting, renewal, amendment or lapse.

IP Australia periodically extracts complete historical records from each register, covering all applications from 1901 onwards. The extracted data is standardised across the four intellectual property types to create consistent formats for variables such as classification codes, date fields and status codes. Applicant names and addresses are cleaned and standardised, and where possible linked to ABNs or other identifiers to enable linkage with business-level datasets. The data is then organised into a longitudinal structure that allows tracking of applicants and their intellectual property rights over time, including filings, renewals and legal status changes.

When IPLORD is supplied to the Australian Bureau of Statistics for integration into the BLADE, the data undergoes additional processing to link applicants to the ABS Business Register spine. This linkage enables integration with economic, trade, innovation and employment datasets.

Data Quality (Scope): The IPLORD dataset has a high level of coverage in its source form from IP Australia, because it includes all patents, trade marks, designs, and plant breeder’s rights ever recorded in the national registers. That makes it a census of registered IP rights in Australia, not a sample. However, when IPLORD is linked into BLADE, the effective coverage depends on whether the applicant can be matched to the ABS Business Register. For Australian businesses and organisations with valid ABNs or strong identifiers, coverage is very high. For individuals without ABNs, foreign applicants, or entities with incomplete contact details, linkage rates are lower

Data Quality (Other): There is variation in the way applicant names and addresses are recorded in the original IP Australia registers. Spelling inconsistencies, formatting differences, and the presence of multiple names for the same entity can lead to challenges in linking records to the ABS Business Register. This is especially common for older historical records. Not all IP rights in IPLORD have strong identifiers like ABNs. In these cases, probabilistic linkage is required which increases the risk of incorrect and missed matches This limitation primarily affects IP rights held by individuals, sole traders, and foreign applicants without an ABN. The earliest years for each IP right type have less detailed metadata. For example, classification codes or address fields may be incomplete in older records, reducing their analytical value for certain research questions.

Data Access: Intellectual Property Longitudinal Research Data (IPLORD) – 1901 to 2020 Full Data Set is available for download at data.gov.au

For the public release of IPLORD on data.gov.au, the dataset is confidentialised to remove or generalise potentially identifying information such as full street addresses, while retaining sufficient detail for meaningful research. https://data.gov.au/data/dataset/intellectual-property-longitudinal-research-data-2020/resource/8ff87fe0-d50e-450f-9b51-21366072d449

The IPLORD dataset is a longitudinal microdata resource constructed from IP Australia’s administrative registers for patents, trade marks, designs, and plant breeder’s rights. It provides detailed, applicant-level records of IP rights activity in Australia from 1901 to 2020. The dataset is intended for research into the role of intellectual property in economic performance, innovation, and business dynamics. IPLORD can be used standalone or, when supplied to the ABS, linked with other datasets in the Business Longitudinal Analysis Data Environment (BLADE).

To increase accessibility, IP Australia has provided IPLORD as a full-size single file, and as smaller files partitioned as the below time periods: to 1990 to 1995 to 2001 to 2005 to 2010 to 2016 to 2020 IPLORD in BLADE is fully linked to ABS’s Business Register Spine and integrated with over 20 other datasets offering more opportunities for research. The integrated version is available only through the ABS DataLab under controlled access conditions and with data custodian approval while the public version can be downloaded freely.

Geographical availability: state and territory, LGA, SA1, SA2, SA3, SA4, mesh block.

BLADE access contact: data.services@abs.gov.au

More Information: IPLORD Data Dictionary https://data.gov.au/data/dataset/intellectual-property-longitudinal-research-data-2020/resource/808dafcd-7cb3-4a39-94d0-81211f138a6f

Types of IP in Australia https://www.ipaustralia.gov.au/understanding-ip/types-of-ip

Overview of the IP government open data https://www.ipaustralia.gov.au/tools-and-research/professional-resources/data-research-and-reports/publications-and-reports/overview-of-the-ip-government-open-data

Email: ipdataplatform@ipaustralia.gov.au

Data Custodian/Owner: IP Australia

Source of Metadata Extraction: https://data.gov.au/data/dataset/intellectual-property-longitudinal-research-data-2020

12.08.2025

Archived on 08.12.2025: https://data.gov.au/data/dataset/intellectual-property-longitudinal-research-data-2020

JobMaker Hiring Credit Scheme Dataset (JMHC)

Purpose: The JobMaker Hiring Credit Scheme dataset (JMHC) in BLADE aims to support analysis of the uptake, effectiveness and broader economic impacts of the JobMaker program by linking it with other business and economic data.

Within BLADE, the dataset provides a detailed administrative record of businesses that registered for and received JobMaker payments, along with information about the eligible employees for whom the payments were claimed.

Main Topic: Employment, income, taxation, wealth, and consumption

Other topics:

Demographics

Subtopics:

When the employment commenced and ceased
Baseline headcount
Baseline payroll
Current headcount
Current payroll
Headcount increase amount
Payroll increase amount

Included into an integrated data asset:

BLADE
PLIDA

Population scope: All employers in Australia who registered for the JobMaker program with the ATO and lodged at least one valid claim for eligible employees

Geographic scope: Australia (national)

Temporal range: 2020-2023

Temporal Unit/Frequency: Quarterly

Unit of Observation: Employer–employee claim record for a specific JobMaker period

Type of Unit of Observation: Event/Process/Activity

Collection & Compilation Methods: The JobMaker Hiring Credit Scheme was introduced as an incentive for businesses to hire additional young job seekers aged between 16 and 35, with the aim of stimulating employment growth during the recovery period following the COVID-19 pandemic.

The JobMaker Hiring Credit Scheme dataset in BLADE is derived entirely from administrative data collected and maintained by the ATO. Employers wishing to participate in the scheme were required to register with the ATO and to provide specific information about each eligible employee. Much of this information was reported through the Single Touch Payroll system, which employers use to submit payroll and employment details directly to the ATO at the time employees are paid.

The data collection process began when an employer lodged a JobMaker registration, which included their Australian Business Number and declarations of eligibility. For each claim period, the employer reported details for each eligible employee, including the tax file number, full name, date of birth, employment start date, employment end date if applicable, and whether the average hours worked requirement was met. These reports were submitted within legislated timeframes for each quarterly claim period. The ATO also collected employer-level information on total headcount changes and baseline employment figures to determine eligibility.

Compilation of the dataset involved collating all JobMaker registration and claim records held by the ATO and preparing them for integration into BLADE. This included standardising identifiers, most notably the ABN, to align with the ABS Business Register and other ATO-sourced datasets.

Data cleaning and validation were undertaken to ensure consistency across reporting periods and to resolve discrepancies between JobMaker claims and other linked administrative data such as Single Touch Payroll records. Once processed, the data was linked within BLADE to other business and economic datasets, enabling longitudinal analysis of firm characteristics and outcomes associated with program participation.

Data Quality (Scope): Completeness is high for the target population, because the program’s design required employers to submit all mandatory information for each eligible employee before a claim could be processed or paid. However, the dataset only covers participants who participated in the program and therefore does not represent all Australian because non-participating businesses and ineligible hires are absent.

Data Quality (Other): The significant part of the information, specifically payroll amounts and employment dates was cross-checked against Single Touch Payroll data, further reducing the likelihood of missing or inconsistent records. As a result, for the population of registered claimants with successful claims, completeness is close to 100% for the core administrative variables.

Data Access: The JMHC dataset is not publicly available as an open dataset.

When incorporated into the BLADE, the integrated version is managed by the ABS. Access to the JMHC data in BLADE is restricted and provided only to approved researchers.

Researchers must apply through the ABS Data Integration process, clearly outlining the research purpose, methodology, and required datasets.

More Information: JobMaker Hiring Credit eligibility criteria: https://omnisgroup.com.au/jobmaker-hiring-credit-eligible-additional-employees/

Data Custodian/Owner: ATO

Source of Metadata Extraction: https://www.abs.gov.au/about/data-services/data-integration/integrated-data/business-longitudinal-analysis-data-environment-blade

14.08.2025

Archived on 08.12.2025: https://www.abs.gov.au/about/data-services/data-integration/integrated-data/business-longitudinal-analysis-data-environment-blade

JobKeeper Payment Scheme Dataset (JobKeeper)

Purpose: The purpose of the JobKeeper Payment Scheme dataset is to provide a complete administrative record of the businesses and not-for-profit entities that participated in the JobKeeper program, along with details of the employees for whom payments were claimed.

Within BLADE, the dataset provides a detailed administrative record of businesses that registered for and received JobKeeper payments, along with information about the employees for whom the payments were claimed, enabling examination of the program’s role in sustaining employment and supporting economic activity during the COVID-19 pandemic. By linking JobKeeper records with other business and labour datasets in BLADE researchers can assess how the program influenced business behaviour, workforce stability, and sectoral performance over time.

Main Topic: Employment, income, taxation, wealth, and consumption

Other topics:

Demographics

Subtopics:

Participation and eligibility status
Payment amounts and periods
Workforce supported
Administrative outcomes
Business size

Included into an integrated data asset:

BLADE
PLIDA

Population scope: All Australian employing and non-employing entities that enrolled in JobKeeper and received at least one payment or any fortnight between 30 March 2020 and 28 March 2021

Geographic scope: Australia (national)

Temporal range: April 2020-March 2021

Temporal Unit/Frequency: Monthly

Unit of Observation: A business that enrolled in and received JobKeeper

Type of Unit of Observation: Organisation

Collection & Compilation Methods: The JobKeeper Payment Scheme dataset was collected by the ATO as part of administering the JobKeeper wage subsidy program introduced during the COVID-19 pandemic. Employers who wished to participate were required to register with the ATO and submit formal nomination notices for each eligible employee, accompanied by written agreements from the employees themselves. The program’s “one in all in” requirement meant that employers were obliged to include all eligible employees in their claims.

To confirm eligibility, employers had to demonstrate either an actual or forecasted decline in turnover, using calculations aligned with their GST reporting method. The ATO provided detailed guidance through official rulings and compliance guidelines to help employers determine eligibility accurately. During the program’s operation, employers were also required to provide periodic updates, such as monthly turnover data, to support compliance checks. The ATO used data-matching arrangements with Services Australia to cross-check employee details, such as tax file numbers, names, and dates of birth, against social security records. This process helped ensure that claims were legitimate and prevented duplication.

Once collected, the JobKeeper administrative data was compiled for integration into the BLADE. The ABS standardised and linked the data using ABNs so that it could be connected with other administrative and survey datasets, including Business Activity Statements, Single Touch Payroll, and business tax records. This integration allows researchers to examine the impact of JobKeeper on business survival, employment, and economic recovery.

Data Quality (Scope): The JobKeeper dataset in BLADE comes from from ATO administrative records (enrolments, monthly declarations and paid claims), so coverage is high for entities that actually received payments, but excludes ineligible, withdrawn or unpaid claims; counts for individuals cover employees and eligible business participants as defined by the program rules.

Data Quality (Other): Accuracy reflects lodgement-time reporting and later compliance adjustments; phase changes and eligibility amendments across 2020–2021 introduce structural breaks which need to be considered.

Data Access: The dataset is not publicly downloadable in its integrated form within BLADE. Aggregated JobKeeper statistics is available on ATO’s website for public use: https://www.ato.gov.au/about-ato/research-and-statistics/in-detail/taxation-statistics/taxation-statistics-previous-editions/taxation-statistics-2019-20/statistics/jobkeeper

The JobKeeper Payment Scheme dataset is available in BLADE as a restricted-access administrative dataset through approved ABS DataLab projects.

More Information: Item list: De-identified ABN De-identified employer id The JK prefix and number previously given to an ABN that was, up until this release, unable to be de-identified Integration version of dataset (internal ABS reference) Disbursements in April Amount Disbursements in May Amount Disbursements in June Amount Disbursements in July Amount Disbursements in August Amount Disbursements in September Amount Disbursements in October Amount Disbursements in November Amount Disbursements in December Amount Disbursements in January Amount The JobKeeper Payment: Three-month review https://treasury.gov.au/publication/jobkeeper-review

Data Custodian/Owner: ATO

Source of Metadata Extraction: https://www.abs.gov.au/about/data-services/data-integration/integrated-data/business-longitudinal-analysis-data-environment-blade/blade-data-and-legislation

14.08.2025

Archived on 08.12.2025: https://www.abs.gov.au/about/data-services/data-integration/integrated-data/business-longitudinal-analysis-data-environment-blade/blade-data-and-legislation

Settlement Database (SDB)

Purpose: The Settlement Database (SDB) is a consolidated database of information on persons who have been granted a permanent or provisional/temporary visa.

Its primary purpose is to provide a comprehensive record of permanent migrants who settle in Australia and to support the Department of Home Affairs in monitoring migration flows, settlement patterns, and service eligibility.

Main Topic: Employment, income, taxation, wealth, and consumption

Other topics:

Demographics

Subtopics:

Visa stream and subclass
Application status
Application location
Migration program
Visa grant date and arrival date
Refugee and humanitarian status

Included into an integrated data asset:

ACMID
PLIDA
PITMID

Population scope: All people granted permanent visas to settle in Australia (Skilled, Family, Humanitarian, Special Eligibility). Certain long-term provisional visa categories that are pathways to permanent residency (e.g., Regional Sponsored Migration Scheme, some family/provisional skilled visas). Refugees and others granted protection under the humanitarian program. It generally excludes temporary visa holders.

Geographic scope: Australia (national)

Temporal range: 2000 - ongoing

Temporal Unit/Frequency: Annually

Unit of Observation: Individual person

Type of Unit of Observation: Individual

Collection & Compilation Methods: The Settlement Database (SDB) is an administrative dataset compiled by the Australian Government from various departmental systems and a number of external sources, including the Department of Home Affairs and Department of Human Services (Medicare Australia). The main source of information is Home Affairs’ visa application and grant systems, which provide details on visa stream, subclass, applicant status, country of birth, language, and the dates of visa grant and arrival. These visa records form the backbone of the dataset. Linking with Medicare data helps confirm settlement activity and improves the overall coverage of the database.

The Department of Home Affairs compiles these sources annually into the SDB. During this process, duplicate records are resolved and a range of internal checks are performed to ensure consistency, such as aligning visa subclasses with visa streams. The data are standardised to align with ABS statistical classifications.

The ABS receives annual extracts of the SDB for use in integrated data assets. For the Personal Income Tax and Migrants Integrated Dataset (PITMID), the ABS produces a statistical extract known as the Permanent Migrant Data (PMD) from the SDB and links it with Australian Taxation Office income tax records. Within the Person Level Integrated Data Asset (PLIDA), the SDB is linked to the ABS Person Linkage Spine.

Data Quality (Scope): The SDB has high coverage of all permanent and eligible provisional visa holders who arrived in Australia from 2000 onwards. It excludes temporary migrants (students, visitors, working holiday makers, etc.) and most New Zealand citizens (who do not require a visa under the Trans-Tasman Travel Arrangement).

Data Quality (Other): Visa information (visa stream, subclass, grant date, applicant status) is highly accurate, as it comes directly from Home Affairs’ operational systems. Demographics (sex, date of birth, country of birth) are reliable, though some variables rely on self-report at application stage. English proficiency is self-assessed and may be less precise. Intended address may not always match actual long-term settlement location, particularly at arrival.

Data Access: SDB is not publicly available as standalone dataset. SDB is only accessible through integrated data assets managed by the Australian Bureau of Statistics (ABS), primarily: PLIDA, where SDB records are linked to health, education, tax, and other government datasets; PITMID, where SDB extracts (the Permanent Migrant Data, PMD) are linked to ATO income tax record.

The PITMID data is available in the ABS DataLab for the following financial years: 2014-15, 2015-16 and 2016-17, 2011-12, 2012-13 and 2013-14, 2009-10 and 2010-11.

More Information: Personal Income of Migrants, Australia methodology https://www.abs.gov.au/methodologies/permanent-migrants-australia-methodology/2021 https://www.abs.gov.au/methodologies/personal-income-migrants-australia-methodology/2016-17

Email: migration.statistics@abs.gov.au

Data Custodian/Owner: ABS Department of Home Affairs

Source of Metadata Extraction: https://www.abs.gov.au/about/data-services/data-integration/integrated-data/personal-income-tax-and-migrants-integrated-dataset-pitmid#:~:text=The%20Personal%20Income%20Tax%20and%20Migrants%20Integrated%20Dataset,unincorporated%20business%20income%2C%20investment%20income%2C%20and%20other%20income%29

10.09.2025

Archived on 08.12.2025: https://www.abs.gov.au/about/data-services/data-integration/integrated-data/personal-income-tax-and-migrants-integrated-dataset-pitmid

National Notifiable Diseases Surveillance System (NNDSS)

Purpose: The primary purpose of the National Notifiable Diseases Surveillance System (NNDSS) is to facilitate the national surveillance of communicable diseases that are considered significant to public health.

Main Topic: Health

Other topics:

Demographics

Subtopics:

Vaccine preventable diseases
Sexually transmissible infections
Bloodborne viruses
Gastrointestinal diseases
Vectorborne and zoonotic diseases
Other bacterial infections
Emerging and other high-consequence diseases

Included into an integrated data asset:

COVID-19 Register

Population scope: All people in Australia irrespective of their residency status (residents, temporary visitors, migrants, etc.) who are diagnosed with a nationally notifiable communicable disease

Geographic scope: Australia (national)

Temporal range: 1990-ongoing

Temporal Unit/Frequency: Case notification event/weekly/monthly/annually

Unit of Observation: A notified case of diseases in a person

Type of Unit of Observation: Event/Process/Activity

Collection & Compilation Methods: Every day, the state and territory health authorities supply the NNDSS with de-identified notification data about new cases of notifiable diseases. This data includes: a unique record reference number. a state or territory identifier, a disease code, the date of onset, the date of notification to the health authority, sex of the case, age of the case, Indigenous status of the case, postcode where the case lives.

The quality and completeness of the information varies, because: notifications come from various sources, including clinicians, laboratories and hospitals, states and territories have different ways for these sources to report cases, some people may choose to not provide all relevant information to health authorities.

The data are compiled against a list of nationally notifiable diseases, agreed by all jurisdictions through the Communicable Diseases Network Australia (CDNA). Case definitions are standardised nationally, so that a “case” of a given disease means the same thing across states and territories.

Records are checked for internal consistency, validity of codes, and completeness. Duplicate or erroneous entries are investigated and corrected in consultation with jurisdictions.

The NNDSS is included in the COVID-19 integrated dataset.

Data Quality (Scope): The NNDSS aims for complete coverage of all notifiable diseases nationally. It has very high population coverage for the diseases on the national list. However, the scope is limited to diagnosed and reported cases. People who do not seek medical care, or who are not tested, are not included.

Data Quality (Other): Testing practices vary across jurisdictions and over time (for example, COVID-19 PCR vs. rapid antigen test reporting) Indigenous status is frequently incomplete or missing in notifications, limiting equity analyses Country of birth, occupation, and risk factor information are inconsistently collected, depending on disease and jurisdiction Onset date is often missing

Data Access: The NNDSS is not publicly available as unit-record data due to privacy and confidentiality requirements. Instead, the Department of Health and Aged Care makes aggregate outputs publicly available through: the NNDSS Data Visualisation Tool, which provides interactive case counts and rates by disease, age, sex, Indigenous status, jurisdiction, and year, weekly, quarterly and annual Communicable Diseases Intelligence (CDI) reports, and special situation/outbreak reports (e.g. COVID-19, influenza). General public and researchers can freely use the data visualisation tool and published reports. Approved researchers or agencies may request customised data extracts from the Department of Health and Aged Care, but approval is granted only under strict conditions, usually requiring ethics approval and a demonstrated public health purpose. NNDSS data are also linked into special purpose integrated datasets, such as the AIHW COVID-19 Register and PLIDA, which can be accessed by approved researchers through the ABS DataLab under strict governance arrangements.

More Information: Diseases on the National Notifiable Disease List

The NNDSS keeps track of the following nationally notifiable diseases. Bloodborne diseases; Hepatitis B (newly acquired and unspecified); Hepatitis C (newly acquired and unspecified); Hepatitis D; Gastrointestinal diseases; Botulism; Campylobacteriosis; Cholera; Cryptosporidiosis; Haemolytic uraemic syndrome (HUS); Hepatitis A; Hepatitis E; Listeriosis; Paratyphoid fever; Salmonellosis Shiga toxin-producing E. Coli (STEC) or Verotoxin-producing E. Coli (VTEC); Shigellosis; Typhoid fever.

Listed human diseases

Listed human diseases are those listed in the Biosecurity (Listed Human Diseases) Determination 2016. Human influenza with pandemic potential is a listed human disease, but is nationally notifiable under ‘influenza (laboratory confirmed)’.

Human influenza with pandemic potential; Human coronavirus with pandemic potential; Middle East respiratory syndrome (MERS); Plague; Severe acute respiratory syndrome (SARS); Smallpox; Viral haemorrhagic fevers; Yellow fever; Sexually transmissible infections; Chlamydia; Donovanosis; Gonococcal infection; Syphilis (congenital, less than 2 years duration, or more than 2 years or unspecified duration); Vaccine preventable diseases; Diphtheria; Haemophilus influenzae type b; Measles; Meningococcal disease – invasive; Mumps; Pneumococcal disease (invasive); Poliovirus infection; Rotavirus; Rubella (including congenital rubella); Tetanus; Varicella zoster infection (including chickenpox, shingles and unspecified Varicella zoster infection); Respiratory diseases; Influenza (laboratory confirmed); Legionellosis; Pertussis; Respiratory syncytial virus infection (RSV); Tuberculosis; Vectorborne diseases; Barmah Forest virus infection; Chikungunya virus infection; Dengue virus infection; Flavivirus infection (unspecified); Japanese encephalitis virus infection; Malaria; Murray Valley encephalitis virus infection; Ross River virus infection; West Nile/Kunjin virus infection; Zoonoses; Avian influenza in humans (AIH); Anthrax; Australian bat lyssavirus infection; Brucellosis; Leptospirosis; Lyssavirus infection (not elsewhere classified); Monkeypox virus (MPXV) infection; Psittacosis (also known as ornithosis); Q fever; Rabies; Tularaemia; Other notifiable diseases; Group A Streptococcal disease – invasive (iGAS); Hepatitis (not elsewhere classified); Leprosy.

Diseases under national surveillance by other organisations.

The Australian National Creutzfeldt-Jakob Disease Registry and the Kirby Institute are also monitoring: Creutzfeldt-Jakob disease (CJD); Variant Creutzfeldt-Jakob disease (vCJD); Human immunodeficiency virus (HIV).

NNDSS data visualisation tool https://www.health.gov.au/resources/apps-and-tools/nndss-data-visualisation-tool

Email: NNDSS.datarequests@health.gov.au

Data Custodian/Owner: Australian Government Department of Health and Aged Care

Source of Metadata Extraction: https://www.health.gov.au/our-work/nndss

18.08.2025

Archived on 08.12.2025: https://www.health.gov.au/our-work/nndss

National Hospital Morbidity Database (NHMD)

Purpose: The National Hospital Morbidity Database (NHMD) is a compilation of episode-level records from admitted patient morbidity data collection systems in Australian hospitals. It has records for all separations of admitted patients from essentially all public and private hospitals in Australia.

The purpose of the NMDS for Admitted Patient Care is to collect information about care provided to admitted patients in Australian hospitals

Main Topic: Health

Other topics:

Demographics

Subtopics:

Hospital activity
Clinical information such as principal and additional diagnoses
Care type (acute, sub-acute, mental health etc.)
Hospital stay characteristics
Diagnostics
Specialised services
Hospital performance indicators

Included into an integrated data asset:

COVID-19 Register

Population scope: All episodes of admitted patient care in Australian hospitals for the reporting period

Geographic scope: Australia (national)

Temporal range: 1993-94-ongoing

Temporal Unit/Frequency: Quarterly or annually (financial year)

Unit of Observation: An episode of admitted patient care

Type of Unit of Observation: Event/Process/Activity

Collection & Compilation Methods: Data are collected at each hospital from patient administrative and clinical record systems. Hospitals forward data to the relevant state or territory health authority on a regular basis (e.g. monthly). State and territory health authorities provide the data to the Australian Institute of Health and Welfare for national collation, on an annual basis.

State and territory health authorities provide the data to the Independent Health and Aged Care Pricing Authority (IHACPA) for national collation, on a quarterly basis.

The data supplied is structured according to the National Minimum Data Set (NMDS) for Admitted Patient Care. This ensures consistency across jurisdictions and includes demographic characteristics, administrative details, length of stay, principal and additional diagnoses, procedures undertaken, and information on external causes of injury and poisoning. Each episode of admitted patient care is captured as a statistical record, and classification standards such as the International Classification of Diseases (ICD-10-AM) for diagnoses and the Australian Classification of Health Interventions (ACHI) for procedures are applied to support national comparability.

Once the AIHW receives the data, they are subject to extensive validation, cleaning, and standardisation to resolve inconsistencies and improve quality, working closely with state and territory data providers. The result is a comprehensive census of admitted patient episodes, covering essentially all public hospitals and almost all private hospitals in Australia.

The NHMDI is included in the COVID-19 integrated dataset.

Data Quality (Scope): The NHMD covers nearly all admitted patient separations (discharges, transfers, deaths) in Australian hospitals. Public hospitals: comprehensive coverage across all states and territories. Private hospitals: coverage varies slightly across jurisdictions and years, depending on reporting practices and completeness of submissions. Day hospital facilities: included in some states/territories but not universally. Psychiatric hospitals: data coverage can differ by jurisdiction and year. It excludes non-admitted patient episodes (e.g., emergency department care unless admitted, outpatient clinics). Some admitted care provided by private hospitals may be under-reported, particularly for specialised care such as rehabilitation, palliative care, or mental health The NHMD is episode-based rather than person-based. Each record represents a separation (an episode of care ending in discharge, transfer, or death), not a unique individual.

Data Quality (Other): A record is included for each separation, not for each patient, so patients who separated more than once in the year have more than one record in the NHMD. There is some variation between jurisdictions as to whether hospitals that predominantly provide public hospital services, but are privately owned and/or operated, are reported as public or private hospitals. In addition, hospitals may be re-categorised as public or private between or within years. Data on state or territory of hospitalisation should be interpreted with caution because of cross-border flows of patients.

Caution should be used in comparing diagnosis, intervention, and external cause data over time, as the classifications and coding standards for those data can change over time.

Data Access:
The AIHW publishes comprehensive analyses of NHMD data in its Australian Hospital Statistics series and other related reports. These publications include interactive data cubes, downloadable tables, and national and state-level summaries that are freely available on the AIHW website.

For researchers who require more specific information, data requests can be made directly to the AIHW. These requests enable access to customised tabulations of NHMD data, but may require approvals from the relevant state and territory health authorities. Depending on the scope and complexity of the request, charges may apply. Access to detailed unit record or microdata, however, is highly restricted. Researchers must obtain approvals from appropriate human research ethics committees and from the custodians in each jurisdiction. These data are made available only within secure environments to ensure the confidentiality and integrity of sensitive health information.

The NHMD is also included in the National Health Data Hub (NHDH), which provides de-identified, linked health data to approved researchers. https://www.aihw.gov.au/reports-data/nhdh/data

More Information: Admitted patient care NMDS 2023-24 https://meteor.aihw.gov.au/content/756111

Technical appendix https://www.aihw.gov.au/getmedia/937228ab-5de5-436c-aba0-036309746ebc/admitted-patient-care-2023-24-appendix_2.pdf

Email: info@aihw.gov.au

Data Custodian/Owner: AIHW

Source of Metadata Extraction: https://www.aihw.gov.au/hospitals/other-resources/about-the-data

19.08.2025

National Death Index (NDI)

Purpose: The database is a listing of all deaths that have occurred in Australia since 1980. It is an invaluable tool for epidemiologists and clinicians in following up research cohorts using record linkage.

By doing so, the NDI allows for the study of long-term health outcomes, disease trends, survival rates, and the effectiveness of interventions across different population groups. It also provides an authoritative and standardised source of mortality data for use in epidemiological research, health services planning, and policy development.

Main Topic: Demographics

Other topics:

Subtopics:

Causes of death
External causes such as details of injury etc.
Death registration details
Comorbidities

Included into an integrated data asset:

COVID-19 Register
NACDA
NHDH

Population scope: All deaths in Australia since 1980.

Geographic scope: Australia (national)

Temporal range: 1980-ongoing

Temporal Unit/Frequency: Annually

Unit of Observation: Death registration record

Type of Unit of Observation: Event/Process/Activity

Collection & Compilation Methods: The National Death Index (NDI) is a Commonwealth database that contains records of deaths registered in Australia since 1980. Data comes from Registrars of Births, Deaths and Marriages in each jurisdiction, the National Coronial Information System and the Australian Bureau of Statistics.

The data collection and compilation process begins with registrars from states and territories who collect information from death certificates completed by medical practitioners, coroners, or funeral directors. These records contain demographic information, cause of death, and other relevant details.

The registrars provide these death registration records to the ABS, which uses them for official mortality statistics. In parallel, copies of the records are supplied to the AIHW, where they are collated into the NDI.

The NDI is designed specifically as a linkage dataset. It functions as a central index of death records that can be matched against other health, social, and administrative datasets. This linkage allows researchers to track outcomes such as survival, disease progression, or the long-term impact of treatments and exposures. The NDI has been linked into the COVID-19 integrated dataset.

Data Quality (Scope): The NDI is a national register of deaths. It contains records of all deaths registered in Australia since 1980. Its coverage is therefore very high, as it is based on official state and territory death registration systems. This makes the dataset essentially complete for mortality ascertainment within Australia.

Data Quality (Other): Incorrect linkages can result because of errors or incorrect details in personal information supplied when deaths are registered. Examples of such errors are: the changed surname when women marry is not provided; given names are transposed, incorrectly spelt, or partly replaced by nicknames; the date of birth is wrong, the birth day of an elderly relative might be known, but not the year of birth.

Only a small number of variables such as: names, sex, date of birth, date of death and components of address, are utilised from the NDI for the linking purpose. Although the file formats in which data are provided by the Registrars changes from time to time, the contents of data remains constant. To ensure consistency, a substantial cleaning and standardisation of data takes place before loading to the database. For example, names are converted to upper case, dates are standardised to ‘yyyymmdd’ format and gender is set to ‘1’ for males and ‘2’ for females.

Data Access: Access to the NDI is usually for data linkage purposes. Interested parties need to email Data Linkage Unit if they wish to access the NDI for data linkage purposes as part of health and/or epidemiological research purposes.

For death information in tabulated format, which doesn’t involve a linkage to NDI unit record data (e.g. to obtain a count of persons who died of a certain condition within a state or particular region), refer to information on the https://www.aihw.gov.au/about-our-data/our-data-collections/national-mortality-database.

To access unit record data from the NDI for data linkage purposes, approval is required from the AIHW Ethics Committee. Researchers can access the National Death Index if their study generally meets the following set of conditions: the study focuses on health issues; the study has been approved by the researcher’s host institution ethics committee and the AIHW Ethics Committee. Typically this review concentrates on the issues of public interest and use of confidential information; the study is scientifically valid (as judged by a peer review process); the study results will be placed in the public domain (e.g. published papers or books, conference presentations, feedback to patients); the study will not break confidentiality provisions; the study investigators comply with the AIHW legislation under which the data are released; and the data will be secured in an environment that guarantees confidentiality of individual’s data.

To formally apply to the AIHW Ethics Committee, an application needs to be lodged on the AIHW Ethics Online System (EthOS).

More Information: National Death Index https://www.aihw.gov.au/about-our-data/our-data-collections/national-death-index/about-national-death-index

Meteor https://meteor.aihw.gov.au/content/480010

Email: linkage@aihw.gov.au

Data Custodian/Owner: AIHW

Source of Metadata Extraction: https://www.aihw.gov.au/about-our-data/our-data-collections/national-death-index

19.08.2025

National Disability Insurance Scheme (NDIS)

Purpose: The purpose of the NDIS dataset is to support monitoing, evaluation of outcomes, service service delivery, and help ensure the financial sustainability of the scheme.

In the context of COVID-19 it was used to monitor the impact of the pandemic on people with disability who are participants in the scheme, as well as on NDIS workers. It was used to track infection and mortality rates, identify vulnerabilities, and inform targeted public health measures to protect participants and maintain continuity of essential disability services.

Main Topic: Community services

Other topics:

Demographics
Health

Subtopics:

Disability
Level of functional impairment
NDIS participation
NDIS plan characteristics and support
Service use and payments
NDIS providers

Included into an integrated data asset:

COVID-19 Register
NHDH

Population scope: All individuals registered as participants in the National Disability Insurance Scheme (NDIS)

Geographic scope: Australia (national)

Temporal range: 2013-ongoing

Temporal Unit/Frequency: Quarterly

Unit of Observation: Individual NDIS participant

Type of Unit of Observation: Individual

Collection & Compilation Methods: NDIS data are collected through the routine administration of the National Disability Insurance Scheme by the National Disability Insurance Agency (NDIA). Information is generated whenever participants interact with the scheme and when providers deliver or claim for services. Key collection points include:

Participant registration and eligibility assessments: demographic information, disability type, and functional capacity are recorded when individuals apply for the scheme.

Planning and plan approval processes: details of approved supports, budgets, and goals are entered into NDIA systems at the start of each plan period. Plan reviews and updates: information is updated at scheduled or unscheduled reviews, capturing changes in participant circumstances or goals. Provider claims and payments: registered providers submit claims for services delivered, which are processed through the NDIA’s payment systems and logged as administrative records. Ongoing interactions: updates are recorded through service bookings, plan management, and other operational transactions.

Data are collected continuously, as part of NDIA’s statutory role in administering the scheme, and stored in secure agency databases. The system therefore captures near-complete information on all NDIS participants, plans, providers, and claims across Australia.

For public release, the NDIA compiles this raw administrative data into aggregate, de-identified datasets. Prior to publication, extensive cleaning and standardisation are applied to ensure accuracy, consistency, and confidentiality. Compilation involves validation and cleaning, standardisation, aggregation and de-identification.

When used within the AIHW National Health Data Hub (NHDH) or the COVID-19 Register, the unit record data are securely transferred to AIHW under strict governance agreements.

Data Quality (Scope): Complete for the population of NDIS participants, with near-universal capture of this cohort from administrative systems. Does not include people with disability outside the NDIS, and therefore is not representative of the full Australian disability population.

Data Quality (Other): High completeness of administrative identifiers (participant ID, plan ID, provider ID, etc.); core demographics (age, sex, date of birth, state/territory, postcode); scheme participation variables (plan start/end dates, support categories, funding allocations, plan management type, service bookings, payments, utilisation rates). Information such as disability type, Indigenous status, or language spoken is self-reported at registration and may be incomplete or inconsistently coded.

Data Access: The National Disability Insurance Agency (NDIA) makes a variety of de-identified, aggregated data publicly available via its data portal. Users can interact with data grouped under categories such as Participant Data, Provider Data, Payment Data. The interface allows filtering by participant type, time period, location, support class, and service category. Results can be viewed as charts or tables and downloaded for analysis.

Individual level data can be accessed through AIHW’s National Health Data Hub (NHDH), where NDIS data are linked with other administrative datasets. This requires a formal application, ethics approval, AIHW governance clearance, and access is provided only in secure research environments

Geographical availability: state and territory; NDIA service districts, LGAs, SA2, SA3, SA4.

More Information: NDIS https://www.ndis.gov.au/

The COVID-19 Register does not include provider-level or payments-level NDIS data; the focus is exclusively on person-level participant records to enable linkage with COVID-19 case, hospital, and health service data, however the NDIS website in addition to participant datasets also lists providers and payments’ datasets.

NDIS participant datasets https://dataresearch.ndis.gov.au/datasets/participant-datasets

Provider and market datasets https://dataresearch.ndis.gov.au/datasets/provider-datasets

Payment data https://dataresearch.ndis.gov.au/datasets/payments-datasets

NDIS reports https://www.ndis.gov.au/publications/quarterly-reports

Email: scheme.actuary@ndis.gov.au

Data Custodian/Owner: AIHW National Disability Insurance Agency (NDIA)

Source of Metadata Extraction: https://dataresearch.ndis.gov.au/datasets

22.08.2025

Archived on 08.12.2025: https://dataresearch.ndis.gov.au/datasets

National Non-Admitted Patient Emergency Department Care Database (NNAPEDCD)

Purpose: The National Non-Admitted Patient Emergency Department Care Database (NNAPEDCD), a compilation of episode-level records (including waiting times for care) for non-admitted patients registered for care in emergency departments in selected public hospitals. Its purpose is to provide nationally comparable information on emergency department (ED) presentations for non-admitted patients in Australian public hospitals, including waiting times and other characteristics of care.

Main Topic: Health

Other topics:

Demographics

Subtopics:

ED presentation details
Triage and clinical information
Emergency Department waiting times
Length of stay in ED
Departure and outcome

Included into an integrated data asset:

COVID-19 Register
NHDH

Population scope: All non-admitted patient presentations to public hospital emergency departments that meet the National Minimum Data Set/National Best Endeavours Data Set (NMDS/NBEDS) definition of an ED, across all Australian states and territories

Geographic scope: Australia (national)

Temporal range: 2003/2004-ongoing

Temporal Unit/Frequency: Annually

Unit of Observation: A single presentation by a patient to ED

Type of Unit of Observation: Individual

Collection & Compilation Methods: National reporting arrangements State and territory health authorities provide the data to the Australian Institute of Health and Welfare for national collation, on a six-monthly basis within one month of the end of a reporting period and an annual basis within three months of the reporting period.

The Institute and the Commonwealth Department of Health will agree on a data quality and timeliness protocol. Once cleaned, a copy of the data and a record of the changes made will be forwarded by the Institute to the Commonwealth Department of Health. A copy of the cleaned data for each jurisdiction should also be returned to that jurisdiction on request.

Periods for which data are collected and nationally collated: six-monthly and financial year. Extraction of data for each six months or year should be based on the date of the end of the emergency department stay. For example, a presentation that commences at 11pm on 30 June and ends at 2am 1 July is not in scope for the January to June six-monthly period.

The NNAPEDCD provides information on the care provided (including waiting times for care) for non-admitted patients registered for care in public hospital emergency departments that have: • purposely designed and equipped area with designated assessment, treatment, and resuscitation areas • the ability to provide resuscitation, stabilisation, and initial management of all emergencies • availability of medical staff in the hospital 24 hours a day • designated emergency department nursing staff 24 hours per day 7 days per week, and a designated emergency department nursing unit manager When used within the National Hospital data collection or the COVID-19 Register, the unit record data are securely transferred to AIHW under strict governance agreements.

Data Quality (Scope): Includes nearly all public hospital emergency department presentations in Australia (293 EDs in 2023–24), providing a national picture of non-admitted ED care However, there are some coverage gaps:

Services provided to patients who are already admitted and managed in ED (e.g. short-stay or observation units after formal admission); private hospital ED presentations; non-physical/virtual consultations (e.g. telehealth triage not resulting in an in-person ED visit) are not included.

Data Quality (Other): Some fields (e.g., Indigenous status, diagnosis) may be under-reported or inconsistently coded. Principal diagnosis coding was not available before 2014–15, and from 2018–19 jurisdictions use the ICD-10-AM Principal Diagnosis Short List. External causes of injury are not collected. Prior to 2020–21, the following jurisdictions have provided data to the NNAPEDCD using the NAPEDC NBEDS specification: Queensland (from 2015–16 to 2019–20); Victoria and Western Australia (from 2016–17 to 2019–20). All other states and territories used the NAPEDC NMDS. The data provided using the NAPEDC NBEDS may not be entirely comparable with data provided using the NAPEDC NMDS. There may be a variation in hospital reporting.

Data Access: AIHW publishes annual national and jurisdictional statistics derived from NNAPEDCD in its reports and interactive dashboards, e.g. https://www.aihw.gov.au/hospitals/dashboards/emergency-department

These releases provide high-level statistics such as numbers of presentations, waiting times by triage category, proportion seen on time, and length of stay.

Researchers, governments, and other approved users can request custom tabulations or more detailed extracts through the AIHW “Data on request” service.

Requests are subject to data governance, privacy legislation, and agreements with state/territory health authorities.

Raw unit-record data are not publicly released. Because of privacy, identifiability, and custodial agreements, access to record-level data is restricted.

Any project seeking such access would need to apply via AIHW’s formal data request processes, justify public benefit, and meet strict ethics and data custodian approvals.

At the unit-record level, each record is associated with a specific hospital ED, but population-based geographies (e.g., SA2, postcode, LGA) are not included.

More Information: Emergency Department Care https://www.aihw.gov.au/hospitals/topics/emergency-departments

Emergency Department Care 2023-2024 Appendix https://www.aihw.gov.au/getmedia/fa47bf99-b90b-4990-bb7a-f7eec0e6f613/emergency-department-care-2023-24-appendix_1.pdf

Hospital Data, including Emergency Department Care Downloads https://www.aihw.gov.au/hospitals/latest-updates-and-downloads/data?search=%7B%22Subtopics%22:%5B%2220%22%5D,%22ShowRelatedTopics%22:false%7D

Australian Emergency Care Specification https://www.ihacpa.gov.au/sites/default/files/2022-10/australian_emergency_care_classification_fact_sheet.pdf

Email: hospitals@aihw.gov.au

Data Custodian/Owner: AIHW

Source of Metadata Extraction: https://meteor.aihw.gov.au/content/759846

25.08.2025

Australian and New Zealand Intensive Care Society (ANZICS)

Purpose: The Australian and New Zealand Intensive Care Society (ANZICS) datasets bring together standardised data from intensive care units across Australia and New Zealand to enable comparison of outcomes, processes of care and resource use. This allows intensive care units to assess their performance against national and international peers and to identify areas where clinical practice can be improved. The datasets also play an important role in supporting quality improvement activities. By monitoring outcomes and variations in practice, hospitals and clinicians can use the information to guide local initiatives aimed at improving patient safety and care within intensive care settings.

ANZICS datasets also aim to support research and epidemiological studies. They are widely used to investigate outcomes such as mortality, morbidity, resource use and the effectiveness of treatments in intensive care populations.

Main Topic: Health

Other topics:

Demographics

Subtopics:

Clinical characteristics
Illness severity
ICU treatment and interventions
ICU resource use
ICU capacity
Outcomes at ICU discharge

Included into an integrated data asset:

COVID-19 Register

Population scope: All patients admitted to participating ICUs in Australia and New Zealand, across public and private hospitals

Geographic scope: Australian and New Zealand

Temporal range: 1992-ongoing

Temporal Unit/Frequency: Annually

Unit of Observation: ICU admission episode

Type of Unit of Observation: Individual

Collection & Compilation Methods: The ANZICS datasets are compiled from data submitted by participating intensive care units across Australia and New Zealand. Each ICU collects information on patient admissions, including demographics, clinical characteristics, illness severity, interventions, outcomes and resource use. Data are entered directly into local electronic systems that have been standardised to ensure consistency of definitions and coding across sites. These data are then submitted to the ANZICS Centre for Outcome and Resource Evaluation (CORE), which oversees the registry program.

Once submitted, the data undergo a process of validation and cleaning. Automated validation checks are applied to identify missing values, inconsistencies or outliers. Queries are sent back to the contributing ICUs to verify or correct records as needed. This iterative process ensures that the datasets are of a high quality and suitable for benchmarking and research. Data are further standardised through the application of agreed coding frameworks and classification systems, which allow for accurate comparison between hospitals and jurisdictions.

Compilation involves merging data from multiple participating ICUs into five centralised registries: the Adult Patient Database (APD), the Critical Care Resource (CCR) Survey, the Australia and New Zealand Paediatric Intensive Care (ANZPIC) Registry, the Extra Corporeal Membrane Oxygenation (ECMO) Dataset, and the Central Line Associated Bloodstream Infection (CLABSI) Registry. The combined dataset provides a comprehensive picture of intensive care practice across Australia and New Zealand. Annual cycles of data submission and validation allow the dataset to be updated regularly, with cumulative records retained to support longitudinal analyses.

The ANZICS CORE team manages the technical and governance aspects of the dataset, ensuring that privacy and confidentiality are maintained at all stages. Access to the data for benchmarking reports, research projects or health service planning is carefully controlled through formal application and approval processes, with ethical and custodial oversight.

ANZICS is included in the COVID-19 Register.

Data Quality (Scope): The ANZICS registries are among the most comprehensive ICU datasets globally. They capture the vast majority of ICU admissions in both countries. Coverage is estimated at more than 90% of all ICU beds in Australia and New Zealand. However, some smaller regional hospitals with limited ICU capability and some private sector ICUs do not participate. Thus, while the registries provide near-universal coverage of high-acuity and tertiary ICU services, they may slightly under-represent the smallest ICUs and certain private facilities.

Data Quality (Other): Core variables such as demographics (age, sex, admission/discharge times, length of stay, outcome) are highly complete because they are mandatory. Key interventions (ventilation, renal replacement therapy, ECMO) are also consistently reported. However, secondary variables, such as comorbidities, complications, may be more variable in completeness and accuracy across hospitals.

Clinical diagnoses are coded using ICD-10-AM and mapped within registry definitions. While coding is standardised, accuracy may vary depending on local documentation and coder expertise.

Data collection methods may also vary by jurisdiction due to differences in electronic systems, resources, or staff training, although ANZICS CORE provides detailed manuals, training, and audits to minimise discrepancies.

Data Access: Public access to the ANZICS datasets is provided through the publication of annual CORE reports, which present aggregated benchmarking data, trends, and quality indicators across Australia and New Zealand. These reports are freely available on the ANZICS website and provide insights into intensive care admissions, treatments, and outcomes.

The patient-level datasets are only available to approved users. Researchers who wish to use the data must submit a detailed research proposal, obtain ethics approval, and undergo review by the ANZICS CORE management and steering committees. Through completion of the ANZICS CORE Data Information Request form, researchers and other interested parties may apply for access to specific sets of data collected and held by ANZICS CORE through its 5 registries; the Adult Patient Database (APD), the Critical Care Resource (CCR) Survey, the Australia and New Zealand Paediatric Intensive Care (ANZPIC) Registry, the Extra Corporeal Membrane Oxygenation (ECMO) Dataset, and the Central Line Associated Bloodstream Infection (CLABSI) Registry.

It is not possible to obtain direct access to the information held by ANZICS CORE without completion of this form: https://anzics.copelandcreative.com.au/information-requests/

More Information: ANZICS Core Reports https://www.anzics.org/core-reports/

ICU statistics https://intensivecarefoundation.org.au/about-intensive-care-units/icu-statistics

Email: anzics@anzics.org

Data Custodian/Owner: Australian and New Zealand Intensive Care Society (ANZICS) Centre for Outcome and Resource Evaluation (CORE)

Source of Metadata Extraction: https://www.anzics.org/registry-information/

25.08.2025

Archived on 08.12.2025: https://www.anzics.org/registry-information/

National Aged Care Data Clearinghouse (NACDC)

Purpose: The National Aged Care Data Clearinghouse (NACDC) is an independent and central repository of national aged care data. It brings together information on people receiving aged care and the services and organisations providing care. The Data Clearinghouse is located at AIHW for the purpose of making aged care data available to a range of stakeholders including policy makers, researchers, the aged care industry and the public.

The NACDC assists transparency and independence in aged care policy research and evaluation through the provision of data and information in a timely manner for research, evaluation and analysis, and is subject to data release protocols, in accordance with the AIHW Ethics Committee protocol and AIHW policy.

Main Topic: Community services

Other topics:

Demographics

Subtopics:

Admissions and discharges from residential aged care
Home care packages
Services delivered under the Commonwealth Home Support Programme
Short-term restorative care
Transition care
Providers and services

Included into an integrated data asset:

COVID-19 Register
NACDA
NHDH
PLIDA

Population scope: All individuals who are assessed for, or who use, formal aged care services funded or regulated by the Commonwealth.

Geographic scope: Australia (national)

Temporal range: 1997-ongoing

Temporal Unit/Frequency: Annually

Unit of Observation: Individual person

Type of Unit of Observation: Individual

Collection & Compilation Methods: The National Aged Care Data Clearinghouse (NACDC) is managed by the AIHW and relies primarily on administrative records that are generated through the operation of government-funded aged care programs. These data are transferred annually from the Department of Health and Aged Care to AIHW and come through the Aged Care Data Warehouse, also known as CASPER, which brings together information from several government systems. The main sources include the Aged Care Management Payment System (ACMPS), which supports Home Care Packages, residential care, the Transition Care Program and Short-Term Restorative Care; the older SPARC system, which collected residential aged care payment data prior to ACMPS; the Data Exchange, which captures activity from the Commonwealth Home Support Programme; and My Aged Care, which records screening and assessments through the National Screening and Assessment Form and provides care package details.

Once AIHW receives the data, it carries out extensive validation and cleaning to ensure consistency, accuracy, and comparability across time. Historical records are revised where needed, anomalies are investigated, and new derived variables are created to support analysis. The Clearinghouse is managed in a secure environment where identifiers are held separately from content data to protect privacy. This enables person-level linkage for approved projects while maintaining strict confidentiality and governance controls. Through these processes, the NACDC brings together multiple aged care datasets into a harmonised national repository that supports monitoring, evaluation, and policy development in aged care.

Included in the NACDC are data on people receiving aged care, assessments (of care needs), services and providers, system capacity (places), and expenditure. Specifically, the NACDC includes data and information relating to the following: assessments: Aged Care Assessment Program (ACAP) and National Screening Assessment Form (NSAF), Resident Classification Scale (RCS) and Aged Care Funding Instrument (ACFI); Residential aged care (RAC): Permanent and respite residential aged care (RAC); home support: Home and Community Care (HACC) and Commonwealth Home Support Programme (CHSP, which replaced HACC in mid-2015); home care: Community Aged Care Program (CACP), Extended Aged Care at Home (EACH), EACH-Dementia (EACH-D), Home Care Packages (HCP) program (which replaced CACP, EACH and EACH-D on 1 August 2013); flexible aged care: Transition Care Programme (TCP) and the Short-Term Restorative Care (STRC) Programme.

In addition to program-level administrative records, the Clearinghouse incorporates a range of complementary data collections. These include quality indicator data that residential care providers are required to submit on a quarterly basis, consumer experience surveys, workforce census data, and population projections from the Australian Bureau of Statistics. These additional collections are updated at different intervals but are all drawn into the Clearinghouse to enhance its coverage and usefulness for research and policy.

NACDC is included in the COVID-19 Register.

Data Quality (Scope): High coverage and accuracy of government-funded aged care programs. However, NACDC covers only government-subsidised aged care programs and does not include privately funded services and unpaid informal care.

Data Quality (Other): Some non-mandatory fields, such as functional assessments, consumer experience surveys, or detailed workforce information, may be incomplete or inconsistently reported. The introduction of new administrative systems over time (e.g., the transition from SPARC to ACMPS, or the shift to AN-ACC) creates breaks in series that can affect comparability across years. Variable definitions may also change with policy reforms, meaning that longitudinal analysis requires careful attention to metadata.

Data Access: Publicly available data include publications, summary tables published in electronic form: https://www.gen-agedcaredata.gov.au/resources/publications/2025/june/national-aged-care-data-clearinghouse-user-guide?utm

Aggregated statistics are available through AIHW GEN.

Client specified tables on request which may be subject to data provider approval (charges apply).

Access: https://www.gen-agedcaredata.gov.au/resources/access-data

Restricted unit record access subject to Ethics Committee approval and/or the agreement of all relevant data custodians in all states and territories (charges may apply).

More Information: GEN Aged Care Data https://www.gen-agedcaredata.gov.au/

Aged Care Funding Instrument https://meteor.aihw.gov.au/content/735287

Email: gen@aihw.gov.au

Data Custodian/Owner: AIHW

Source of Metadata Extraction: https://www.aihw.gov.au/about-our-data/our-data-collections/national-aged-care-data-clearinghouse

25.08.2025

National Community Mental Health Care Database (NCMHCD)

Purpose: The National Community Mental Health Care Database (NCMHCD) has been established to support monitoring, reporting, and research on the delivery of government-funded community mental health care services across Australia. Its primary purpose is to provide a national repository of information on community mental health care contacts delivered by state and territory specialised public mental health services. These services are usually hospital- or community-based and are designed to support people with mental illness living in the community, outside of admitted patient settings.

Main Topic: Community services

Other topics:

Demographics
Health

Subtopics:

Community mental health service contacts
Principal diagnosis
Additional diagnoses
Mental health legal status
Type of care provided
Date and duration of service contacts

Included into an integrated data asset:

CWDA

Population scope: All government-funded and operated community mental health care services in Australia

Geographic scope: Australia (national)

Temporal range: 2000/01-ongoing

Temporal Unit/Frequency: Annually

Unit of Observation: Service contact

Type of Unit of Observation: Individual; Event/Process/Activity

Collection & Compilation Methods: The National Community Mental Health Care Database (NCMHCD) is compiled annually by the AIHW using data supplied by state and territory health authorities.

Data Quality (Scope): All states estimate that 85–100% of in-scope community mental health care services provided contact data to the collection. Overall service contact data coverage for jurisdictions was estimated to be between 86–100%.

The scope includes: ambulatory mental health care provided by service units covering all target populations.

The scope excludes: all care to admitted patients, including same day admitted patient care delivered by ambulatory mental health care service units, ‘in-reach’ mental health service contacts, that is, service contacts provided to patients admitted to admitted patient mental health care services or residential mental health services, support services that are not specialised mental health care services and services provided by non-government organisations.

Excluded from the CMHC NMDS scope is all activity reported to: the Admitted patient care NMDS, and the Residential mental health care NMDS.

Data Quality (Other): There is some variation in the types of service contacts included in the data. For example, some states or territories may include written correspondence as service contacts while others do not. The Indigenous status data should be interpreted with caution due to the varying quality of Indigenous identification across jurisdictions reporting to the database. While all states and territories consider the quality of Indigenous status data to be acceptable, most acknowledge that further improvement is required. Indigenous status is missing for 4.5% of contacts in the 2021–22 NCMHCD.

Data are reported by the jurisdiction that delivered the service and therefore may include people receiving services in one jurisdiction who reside in another. These cross-border flows are particularly relevant when interpreting ACT remoteness data.

There is variation across jurisdictions in the coverage of services providing contact data and the estimated service contact data coverage.

The quality of principal diagnosis data may be affected by the variability in collection and coding practices across jurisdictions

Data Access: Aggregate statistics from the NCMHCD are freely available through the AIHW’s Mental Health Services in Australia (MHSA) online platform. These include tables, charts, and interactive dashboards describing community mental health service contacts, patient demographics, and service characteristics. AIHW also publishes annual data tables and reports, which can be downloaded directly from its website, e.g. the Mental health online report: https://www.aihw.gov.au/mental-health.

At the customised data level, researchers and policy agencies can request access to more detailed de-identified data extracts. These are available only through a formal request process managed by AIHW and may require ethics approval, depending on the scope and sensitivity of the request. AIHW reviews applications against governance, confidentiality, and privacy requirements before releasing data.

At the integrated data level, the NCMHCD can also be linked with other health and welfare datasets via AIHW’s Data Integration Services Centre (DISC). Access in this case is highly restricted and is only provided within secure environments to approved projects that demonstrate strong public value and have appropriate governance and ethics approvals.

Geographic coverage: national, states and territories.

More Information: Community mental health care NMDS 2021–22: National Community Mental Health Care Database, 2023; Quality Statement https://meteor.aihw.gov.au/content/780645

Community mental health care NMDS 2021–22 https://meteor.aihw.gov.au/content/727348

Email: mentalhealth@aihw.gov.au

Data Custodian/Owner: AIHW

Source of Metadata Extraction: https://www.aihw.gov.au/about-our-data/our-data-collections/national-community-mental-health-care-database

26.08.2025

Non-Admitted Emergency Care (NAEC) Dataset (SA)

Purpose: The South Australian Non-Admitted Emergency Care (NAEC) dataset records presentations to emergency departments in public hospitals across the state where patients are not admitted. It contains demographic, administrative and clinical details for each presentation, including information on triage, waiting times, type of treatment provided and outcome of care. The purpose of the South Australian NAEC dataset is to provide a systematic account of demand for emergency department services in the state and to support monitoring of performance and outcomes in this sector of the health system. The dataset enables state health authorities to assess patterns of service use, identify pressures on emergency departments and evaluate the effects of policy and service reforms.

Main Topic: Health

Other topics:

Demographics

Subtopics:

Hospital characteristics
Mode of arrival
Triage category
Clinical characteristics
Service outcomes

Included into an integrated data asset:

NDDA

Population scope: All non-admitted emergency physical presentations to public hospitals in South Australia

Geographic scope: South Australia

Temporal range: 2003-ongoing

Temporal Unit/Frequency: Annually

Unit of Observation: Episode of non-admitted emergency care

Type of Unit of Observation: Event/Process/Activity

Collection & Compilation Methods: In South Australia, non-admitted emergency activity data is collected in accordance with the standards and guidelines established for the Non-Admitted Emergency Care (NAEC) data collection. The scope of this activity covers patients presenting to public hospital emergency departments; private hospital data is not collected. Emergency department activity data relating to South Australian residents hospitalised in interstate public hospitals is collected by the State/Territory health authority which admitted those patients. The NAEC dataset in South Australia is compiled by SA Health and adheres to the national specifications set by the Australian Institute of Health and Welfare (AIHW) for non-admitted emergency care collections. Data are generated routinely at the point of service delivery, with each presentation to a public hospital emergency department creating an electronic record in the hospital information system. These records are subsequently collated centrally by SA Health to form the statewide NAEC dataset. Data collection follows a nationally agreed set of data elements and definitions, capturing demographic details such as age, sex, and Indigenous status, administrative information such as triage category, waiting time, and mode of arrival, and clinical information including principal diagnosis and the outcome of the presentation. Coding practices are aligned with AIHW data standards to ensure comparability with other jurisdictions. For compilation, records from individual hospitals are transmitted to SA Health on a regular basis, where they are subject to validation and standardisation processes designed to ensure accuracy and consistency. Quality assurance procedures include checks for missing information, logical inconsistencies, and compliance with national coding rules. Once validated, the records are aggregated into the statewide dataset, which is submitted annually to the AIHW to contribute to the national Non-Admitted Emergency Care collection. Extracts from this dataset are also incorporated into the National Disability Data Asset (NDDA).

Data Quality (Scope): The following data are included in the Non-Admitted Emergency Care Data Domain:  Presentations to public hospitals for emergency department care; and  Presentations to public hospitals for emergency service care. The following data are excluded from the Non-Admitted Emergency Care Data Domain: Presentations to a private hospital Emergency Department Advice provided by telephone or videoconferencing is not in scope

Data Quality (Other): The data within the NAEC can be self-reported by the patient (e.g. [Birth Date]), subjectively determined by a clinician (e.g. [Principal Diagnosis Code 1]), or determined by subsequent mapping (e.g. [Principal Diagnosis Short List Code 1]). Thus, the data within NAEC is not said to be accurate because it cannot be compared to any existing determined-to-be-accurate data. Completeness is assumed at the data set level, since there is no independent confirmation that the number of NAEC presentation records matches the number of PAS presentation records. The NAEC database does not require mandatory fields to be populated; therefore, the database does not manage completeness at either the record or column level. However, completeness is achieved via data quality checks, which identify whether data is missing or is in violation of given business rules. Consistency is achieved by mapping native PAS value domains to State and National value domains. Thus, for example, all hospitals can agree on how to map their PASspecific values to the national value for (Arrival Mode National) of 1: Ambulance, air ambulance or helicopter rescue services. However, note that subjective determinations of data elements (e.g. [Principal Diagnosis Code 1]) mean that consistency cannot be guaranteed within the NAEC.

Data Access: At the state level, the dataset is maintained by SA Health (Department for Health and Wellbeing, Government of South Australia). It is not openly available as a public dataset. Access requires a formal request to SA Health, with approval subject to ethics clearance, data governance requirements, and the agency’s data sharing policies. Metadata about the dataset, including standards and reference manuals, is published online, but the underlying episode-level data are restricted. At the national level, de-identified extracts from South Australia are provided annually to the AIHW for inclusion in the national Non-Admitted Emergency Care collection. AIHW publishes aggregate statistics from this national collection in reports such as Australian Hospital Statistics, and detailed metadata specifications are accessible via the METEOR registry. Researchers requiring access to microdata or linked extracts must apply through the AIHW’s data access arrangements, typically under a data custodian agreement and ethics approval. The South Australian NAEC dataset has been incorporated into the National Disability Data Asset (NDDA). Access to the linked dataset is possible, but only for approved projects that meet strict privacy, governance, and ethics conditions.

More Information: Non-Admitted Emergency Care Data Domain: Reference Manual https://www.sahealth.sa.gov.au/wps/wcm/connect/f0b277b4-0940-4007-96e6-b4c7ad2e2b36/Non-Admitted%2BEmergency%2BCare%2BData%2BDomain%2B-%2BReference%2BManual.pdf?MOD=AJPERES&CACHEID=ROOTWORKSPACE-f0b277b4-0940-4007-96e6-b4c7ad2e2b36-pc52Wz4&utm_

Email Health.DataAnalyticsandInsights@sa.gov.au

Data Custodian/Owner: South Australia Department for Health and Wellbeing (SA Health)

Source of Metadata Extraction: https://www.sahealth.sa.gov.au/wps/wcm/connect/public+content/sa+health+internet/about+us/our+performance/our+data+collections/non-admitted+emergency+care/non-admitted+emergency+care?utm_

29.08.2025

Archived on 08.12.2025: https://www.sahealth.sa.gov.au/wps/wcm/connect/public+content/sa+health+internet/about+us/our+performance/our+data+collections/non-admitted+emergency+care/non-admitted+emergency+care?utm_

Admitted Patient Care (APC) (SA)

Purpose: The Admitted Patient Care data set (APC) SA covers all (majority) of inpatient hospitalisations in South Australia and provides SA Health with the information necessary to effectively fund, organise, evaluate, and plan health services. It also allows SA Health to meet national obligations through submissions to the Australian Institute of Health and Welfare (AIHW), the Independent Hospital Pricing Authority (IHPA), the National Health Performance Authority and the National Health Funding Body.

Main Topic: Health

Other topics:

Demographics

Subtopics:

Hospital characteristics
Admission and separation dates
Types of admission
Care type
Clinical information
Outcomes of care

Included into an integrated data asset:

NDDA

Population scope: All admitted patient separations (discharges, transfers and deaths) from every South Australian including Public Acute Hospital, Public Psychiatric Hospital, Private Acute Hospital (licensed by SA Health), Private Psychiatric Hospital (licensed by SA Health), Private Day Surgery (licensed by Commonwealth).

Admitted patient activity data relating to SA residents hospitalised in interstate public hospitals is collected by the other State/Territory health authorities.

The following patients are excluded from the Integrated South Australian Activity data set: ptients in developmental disability institutions, patients in private residential aged care facilities,patients in outpatient and community health services, patients in multi-purpose service hospital hostel accommodation who are not classified as admitted patients, residents of community residential care units, residents of transitional living units under the brain injury rehabilitation program, defence force personnel treated on base, boarders, still births.

Geographic scope: South Australia

Temporal range: Early 2000 -ongoing

Temporal Unit/Frequency: Annually

Unit of Observation: Episode of admitted patient care

Type of Unit of Observation: Event/Process/Activity

Collection & Compilation Methods: Data are collected routinely through hospital patient administration and clinical information systems at the time of service delivery. Each time a patient is admitted to a hospital and subsequently separated (discharged, transferred, or deceased), a record of that episode of care is created.

Individual hospital records are transmitted to SA Health, where they are validated and standardised before being aggregated into the statewide APC dataset. Data undergo consistency and quality checks, including verification of coding rules, logical sequencing (e.g. admission date before separation date), and completeness of mandatory fields. Once validated, the hospital-level records are combined to form a comprehensive statewide dataset of admitted patient separations. The compiled APC dataset is submitted annually to the AIHW for inclusion in the national Admitted Patient Care NMDS. At the same time, SA Health uses the dataset internally for service planning, performance monitoring, and policy evaluation.

The Admitted Patient Care data set forms part of the Admitted Patient Care National Minimum Data Set through submission to AIHW. Extracts from this dataset are also incorporated into the National Disability Data Asset (NDDA).

Data Quality (Scope): The dataset includes virtually all inpatient separations across the state. Completeness is strongest for public hospitals, while some variation may occur in the timeliness and quality of reporting from private hospitals.

Data Quality (Other): The completeness of submitted data is monitored monthly to identify when submission deadlines are not met or when records are outstanding. Significant instances of incomplete submissions are published in the monthly data set refresh notices to ensure data end users such as analysts and researchers are notified of this quality issue.

The Admitted Patient Care data set is reviewed annually to ensure it provides SA Health with the information necessary to effectively fund, organise, evaluate, and plan health services and to meets its national obligations through submissions to the Australian Institute of Health and Welfare (AIHW), the Independent Hospital Pricing Authority (IHPA), and the National Health Funding Body. Common data elements are defined and consistent within and across data sets.

Data Access: Aggregated statistics and performance indicators are released through SA Health’s reporting platforms, such as hospital activity dashboards and performance summaries, for example, the Inpatient dashboard: https://www.sahealth.sa.gov.au/wps/wcm/connect/public+content/sa+health+internet/about+us/our+performance/our+hospital+dashboards/about+the+ip+dashboard/about+the+inpatient+dashboard

At the state level, the dataset is maintained by SA Health and is not publicly available in unit-record form. Access to detailed data requires a formal request through SA Health’s governance processes and is contingent upon approval by the relevant custodians, compliance with data sharing agreements, and approval from a Human Research Ethics Committee.

At the national level, the AIHW publishes this information in the form of aggregate statistics through its Australian Hospital Statistics series and provides detailed metadata in the METEOR registry. In addition to these pathways, extracts of the South Australian APC data may also be incorporated into integrated assets.

More Information: Resources for Admitted Patient Care https://www.sahealth.sa.gov.au/wps/wcm/connect/public+content/sa+health+internet/about+us/our+performance/our+data+collections/admitted+patient+care/admitted+patient+care+resources_

Admitted Patient Care. Data Quality Checks 2024-2025 https://www.sahealth.sa.gov.au/wps/wcm/connect/a9bf5353-9e00-46e0-8220-c2a19a06712c/Admitted+Patient+Care+-+Data+Quality+Checks+-+Reference+Manual+2024-2025.pdf?MOD=AJPERES&CACHEID=ROOTWORKSPACE-a9bf5353-9e00-46e0-8220-c2a19a06712c-pcowv0L

Admitted Patient Care. Data Elements 2023-2024 https://www.sahealth.sa.gov.au/wps/wcm/connect/f2652cc1-996c-4c17-8115-f85beebddbab/Admitted%2BPatient%2BCare%2B-%2BData%2BElements%2B-%2BReference%2BManual%2B2023-2024.pdf?MOD=AJPERES&CACHEID=ROOTWORKSPACE-f2652cc1-996c-4c17-8115-f85beebddbab-pz2Lbz7

Email Health.DataAnalyticsandInsights@sa.gov.au

Data Custodian/Owner: South Australia Department of Health and Wellbeing (SA Health) National dataset publisher: AIHW

01.09.2025

Archived on 08.12.2025: https://www.sahealth.sa.gov.au/wps/wcm/connect/public+content/sa+health+internet/about+us/our+performance/our+data+collections/admitted+patient+care/admitted+patient+care?utm_

Admitted Patient Care (APC) (ACT)

Purpose: The primary purpose of the Admitted Patient Care (APC) dataset in the ACT is to systematically capture detailed information about care provided to admitted patients in in the Australian Capital Territory (ACT) hospitals.

The dataset is primarily used by ACT Health Directorate to: monitor and report on the activity of ACT hospitals, including admission volumes, length of stay, diagnoses and procedures, and discharge outcomes; support planning and resource allocation, ensuring that hospital services meet population health needs; contribute to national reporting obligations by providing ACT data to the Australian Institute of Health and Welfare (AIHW) for inclusion in the national Admitted Patient Care NMDS; and enable analysis of health system performance, equity of access, and patterns of service use by different population groups within the ACT.

Main Topic: Health

Other topics:

Demographics

Subtopics:

Hospital identifier
Admission and separation dates
Types of admission
Source of referral
Care type
Clinical information
Outcomes of care

Included into an integrated data asset:

NDDA

Population scope: All inpatient separations (discharges, transfers and deaths) from all public and private hospitals in ACT.

Geographic scope: ACT

Temporal range: 2004-ongoing

Temporal Unit/Frequency: Irregular

Unit of Observation: Episode of admitted patient care

Type of Unit of Observation: Event/Process/Activity

Collection & Compilation Methods: The Admitted Patient Care (APC) dataset in the ACT is collected routinely through the patient administration systems in both public and private hospitals. Each time a person is admitted and later separated whether by discharge, transfer, or death, a record of that episode of care is created. These records include demographic details, administrative information, and clinical data, with diagnoses coded to ICD-10-AM and procedures to ACHI, ensuring compliance with national standards.

The hospital-level data are then transmitted to the ACT Health Directorate, which is responsible for compiling the statewide dataset. At this stage, the records are subject to validation checks for completeness, logical consistency, and compliance with national data definitions under the Admitted Patient Care NMDS. Once validated, the data are aggregated into a single jurisdictional dataset that represents all admitted patient separations in the ACT.

The ACT Health Directorate maintains this dataset for service planning, performance monitoring, and reporting. It also submits an annual extract to the Australian Institute of Health and Welfare, which combines it with data from other states and territories to produce the national Admitted Patient Care NMDS. Extracts from this dataset are also incorporated into the National Disability Data Asset (NDDA).

Data Quality (Scope): The dataset covers all separations from public and private hospitals in the ACT, which provides near-complete population coverage for admitted patient activity in the jurisdiction. Public hospitals report consistently, while reporting from private hospitals is also included, though some minor variation in timeliness or detail can occur.

Data Quality (Other): Missingness is possible in specific demographic fields such as Indigenous status or country of birth, and occasionally in clinical coding fields, but overall completeness is high.

Consistency is maintained through alignment with the national Admitted Patient Care NMDS standards. Diagnoses are coded to ICD-10-AM, procedures to ACHI, and episodes are grouped into AR-DRGs. This standardisation ensures comparability across states and territories, although coding quality can vary depending on resources and practices at individual hospitals.

Coding is generally of a high standard because it follows national coding frameworks and quality assurance processes.

Data Access: Aggregated statistics and performance reports are available on the ACT Government website: https://www.act.gov.au/open/epidemiology-publications/leading-causes-of-hospitalisation-in-the-act-2016-17-to-2020-21?utm https://www.act.gov.au/__data/assets/pdf_file/0008/2382866/Q4-2020-21-QPR.pdf?utm

Any researcher applying for access to identifiable data held by NSW and ACT Health for research purposes must obtain data custodian and ethics approval. Please contact CHeReL client services at: moh-cherel@health.nsw.gov.au

More Information: Variables List https://metadata.phrn.org.au/dataset/APDC-ACT/documentation

ACT Public Health Services Quarterly Performance Report: 2021 https://www.act.gov.au/__data/assets/pdf_file/0008/2382866/Q4-2020-21-QPR.pdf?utm

Email: MOH-CHeReL@health.nsw.gov.au

Data Custodian/Owner: ACT Health Directorate

Source of Metadata Extraction: https://metadata.phrn.org.au/dataset/APDC-ACT?utm_

01.09.2025

Archived on 08.12.2025: https://metadata.phrn.org.au/dataset/APDC-ACT?utm_

The National Non-admitted Patient (episode-level) Database (NNAP(el)D)

Purpose: The purpose of the National Non-admitted Patient (episode-level) Database (NNAP(el)D) is to provide a nationally consistent record of non-admitted patient care activity at the episode level in Australian public hospitals, LHNs and selected other public hospital services. It captures information about individual occasions of service provided to patients who are not admitted to hospital, including outpatient services delivered through hospital clinics.

The database exists to support a number of policy and research purposes. It enables monitoring of the scale and nature of non-admitted patient care across jurisdictions, including the types of services provided, patient demographics, referral pathways, and outcomes.

Main Topic: Health

Other topics:

Demographics

Subtopics:

Type of clinic
Referral source
Form of non-admitted care
Clinical characteristics
Outcomes

Included into an integrated data asset:

NHDH

Population scope: All patients who receive non-admitted care in public hospitals and Local Hospital Networks (LHNs) in Australia

Geographic scope: Australia (national)

Temporal range: 2003-ongoing

Temporal Unit/Frequency: Annually

Unit of Observation: Episode of admitted patient care

Type of Unit of Observation: Event/Process/Activity

Collection & Compilation Methods: The National Non-admitted Patient (episode-level) Database (NNAP(el)D) is built from data supplied under the Non-admitted Patient National Best Endeavours Data Set (NAP NBEDS). Its collection and compilation methods follow a nationally consistent process coordinated by the AIHW in partnership with state and territory health authorities.

Data are collected routinely by public hospitals through their patient administration and clinical information systems whenever a non-admitted service is provided. These services include outpatient clinic visits and other hospital-based care where the patient is not formally admitted. Each episode of service generates a record that includes demographic information (such as age, sex, and Indigenous status), administrative items (such as referral source, clinic type, and date of service), and clinical details (such as the type of care provided). At the jurisdictional level, state and territory health departments collate hospital-level data into jurisdiction-wide extracts. These are then submitted to the AIHW according to the definitions and standards set out in the NAP NBEDS. Because this is a “best endeavours” dataset, provision of data is not mandatory, and coverage can vary between states and territories or between different hospital services.

The AIHW compiles these jurisdictional extracts into the national NNAP(el)D. During this process, the data are validated against national standards, checked for completeness, logical consistency, and coding accuracy. The AIHW also standardises the records to ensure comparability across jurisdictions.

Data Quality (Scope): The NNAP(el)D is compiled on a “best endeavours” basis through the Non-admitted Patient NBEDS. This means the quality varies across states, territories, and service types, although it is still one of the most comprehensive national sources of non-admitted care data.

The dataset provides broad population coverage, but not all jurisdictions submit complete episode-level data. In some cases, only selected hospital services or clinic types are included, while in others coverage is close to full. Private hospital non-admitted services are outside the scope altogether, which reduces completeness.

Data Quality (Other): Although the dataset follows the NAP NBEDS specifications, there is variability in how jurisdictions interpret and code specific items. For example, clinic type categories may not be applied consistently across states, and the level of detail provided for principal diagnosis or procedures may differ.Some demographic variables, e.g. Indigenous status, country of birth, may be under-reported or recorded inconsistently.

Data Access: Aggregated statistics and summary tables are publicly available through the Australian Hospital Statistics reports published by AIHW: https://www.aihw.gov.au/hospitals/topics/non-admitted-patient-care?utm

Access to the unit-record data is restricted to approved projects only. Researchers and government agencies can apply through the AIHW’s Data Governance Framework. Approved users are usually provided access in secure analysis environments rather than through data extracts.

More Information: Non-Admitted Patient NBEDS 2022-2023 https://meteor.aihw.gov.au/content/742186

Data Custodian/Owner: AIHW

Source of Metadata Extraction: https://www.aihw.gov.au/about-our-data/our-data-collections/national-hospitals-data-collection?utm

02.09.2025

The National Apprentice and Trainee Collection (NATC)

Purpose: The National Apprentice and Trainee Collection (NATC) provides a comprehensive record of apprenticeships and traineeships across Australia. Its main purpose is to collect, collate and publish data on the commencements, completions, cancellations/withdrawals, and training contracts of apprentices and trainees. The data allow governments, industry bodies, researchers, and training providers to: monitor participation and outcomes in the apprenticeship and traineeship system; track trends over time, such as uptake in different occupations, industries, and regions; support policy development and program evaluation in vocational education and training (VET); provide evidence on skills supply, workforce development, and labour market needs; enable national reporting.

Main Topic: Childcare, education, and training

Other topics:

Demographics

Subtopics:

Contract transactions including commencement, recommencement, completion, cancellation, withdrawal or expiry
Employers
Completion and attrition for apprentices and trainees
Training programs
Training organisations

Included into an integrated data asset:

NCVER

Population scope: All individuals who have a registered apprenticeship or traineeship training contract in Australia, regardless of whether the contract is government-funded or employer-funded

Geographic scope: Australia (national)

Temporal range: 1994-ongoing

Temporal Unit/Frequency: Quarterly

Unit of Observation: Individual person

Type of Unit of Observation: Individual

Collection & Compilation Methods: The NATC provides data on all persons employed under a training contract and includes both apprentices and trainees. Data are collected from state training authorities on training activity in apprenticeships and traineeships in Australia, including information on training rates and duration of training. Records submitted include information on the following: people who have participated in an apprenticeship/traineeship training contract, including their demographics, schooling and prior education and cultural and language attributes; all training contract transactions – including each commencement, cancellation, withdrawal, completion or expiry associated with the life of the apprenticeship/traineeship training contract; each employer participating in an apprenticeship/traineeship training contract; each program undertaken as part of the apprenticeship/traineeship training contract; and each registered training organisation associated with an apprenticeship/traineeship training contract.

Information is collected from the apprenticeship/traineeship training contract completed by the employer and employee. https://www.ncver.edu.au/research-and-statistics/vet-statistics-explained#collectiondates The data are downloaded by each state training authority, which supply additional data and report to NCVER using the AVETMISS validation software. Data are extracted from local systems and submitted on a quarterly cumulative basis.

Data Quality (Scope): The NATC includes all registered apprenticeship and traineeship contracts recorded by state and territory training authorities. This means a nearly complete population coverage, however the dataset only covers training arrangements that are formally registered. Any informal, unregistered, or short-term work-based training will not be captured.

Each state and territory has its own register of apprenticeships and traineeships, some are broader than others which means that the same qualification may be recognised as a traineeship in some jurisdictions, but not in others which may impact comparability across jurisdictions.

Data Access: The NATC is not released as a full unit-record dataset for general use. However, aggregated statistics derived from NATC are widely available: NCVER publishes quarterly and annual releases of apprentice and trainee activity, including commencements, completions, cancellations, and in-training counts.

These statistics are available through NCVER’s DataBuilder VOCSTATS (for experienced users) interactive tools, Excel data tables, and summary reports on apprentices and trainees. https://www.ncver.edu.au/research-and-statistics/data/databuilder https://www.ncver.edu.au/research-and-statistics/vocstats Email: vocstats@ncver.edu.au

Access to identified RTO and VET student data is restricted. Researchers and organisations may apply for access to identified data held by NCVER by making an application to the VET Data Access Committee (VDAC). Please refer to Part C of the National VET Data Policy for further details as well as the factors the committee may consider when reviewing a request for identified data.

To request access to identifiable data, researchers need to email NCVER by contacting vet_req@ncver.edu.au for surveys or administrative data.

More Information: Apprentices and trainees 2024: December quarter https://www.ncver.edu.au/research-and-statistics/publications/all-publications/apprentices-and-trainees-2024-december-quarter

Completion and attrition rates for apprentices and trainees 2023 https://www.ncver.edu.au/research-and-statistics/publications/all-publications/completion-and-attrition-rates-for-apprentices-and-trainees-2023 Guide to Recognising Apprenticeships and Traineeships https://skillsinsight.com.au/wordpress/wp-content/uploads/2024/07/Ag-Trade-Apprenticeship-Supp.3-Guide-to-Recognising-Apprenticeships-and-Traineeships.pdf?utm Email: ncver@ncver.edu.au

Data Custodian/Owner: National Centre for Vocational Education Research (NCVER)

Source of Metadata Extraction: https://www.ncver.edu.au/research-and-statistics/collections/apprentices-and-trainees-collection

02.09.2025

Archived on 08.12.2025: https://www.ncver.edu.au/research-and-statistics/collections/apprentices-and-trainees-collection

VET in Schools (VETiS)

Purpose: The collection VET in Schools (VETiS) captures data on vocational education and training (VET) undertaken by school students as part of their senior secondary certificate of education (SSCE). This includes training that is nationally recognised and may be delivered by schools or external registered training providers.

For research, the collection enables analysis of trends in VET participation among school students, including differences by state or territory, industry field, qualification level, and demographic characteristics. Researchers can use the data to examine the relationship between VETiS participation and later educational or labour market outcomes, as well as to track equity of access across diverse groups of young people. For policy, the collection supports governments and education authorities in monitoring the effectiveness of VET in Schools programs, planning workforce development initiatives, and aligning training opportunities with national and state skills priorities. The data also assist policymakers to evaluate whether VETiS is providing viable pathways to employment, apprenticeships, and further study, and to adjust program design or funding models accordingly.

Main Topic: Childcare, education, and training

Other topics:

Demographics

Subtopics:

Student participation in VET in schools
Course enrolments
Level of qualifications
Training packages
Training delivery
Assessment and certification

Included into an integrated data asset:

NCVER

Population scope: All secondary school students in Australia who undertake nationally recognised vocational education and training (VET) as part of their senior secondary certificate of education (SSCE)

Geographic scope: Australia (national)

Temporal range: 1996-ongoing

Temporal Unit/Frequency: Annually

Unit of Observation: Individual person

Type of Unit of Observation: Individual

Collection & Compilation Methods: This collection provides data for vocational education and training (VET) undertaken by school students as part of their senior secondary certificate of education (SSCE), where the training is nationally recognised or delivered by schools or other training providers.

Data are collected and reported via the senior secondary assessment authority in each state or territory (known as Boards of Studies) to NCVER using the VET Provider Collection Specifications and the AVETMISS validation software.

Data collection dates for 2025: https://www.ncver.edu.au/research-and-statistics/vet-statistics-explained#collectiondates Information on participation, students, courses and qualifications, and subjects, relating to VET in Schools students of all ages, is included.

NCVER compiles the state and territory submissions into a national database. Records are harmonised to match national statistical standards (e.g., training package and qualification codes, demographic categories). VETiS is aligned with the National VET Provider Collection, ensuring comparability across the wider VET system.

Data Quality (Scope): The population scope completeness for VETiS is very high for nationally recognised VET undertaken by secondary students, but it excludes non-accredited school-developed programs and students who do VET outside their school studies.

Data Quality (Other): Some fields that rely on self-identification (e.g., Indigenous status, disability status, language background) are prone to under-reporting or missing values, which affects subgroup coverage rather than the overall population count. Data rely on schools and registered training organisations (RTOs) providing accurate information to state/territory authorities.

Although AVETMISS standards are applied, there can be inconsistencies in how states and territories record or classify enrolments. Examples include differences in reporting partial completions, recognition of prior learning, or the granularity of units of competency.

Data Access: The VETiS data is not released as a full unit-record dataset for general use. However, aggregated statistics derived from VETiS are widely available. These statistics are available through NCVER’s DataBuilder, VOCSTATS (for experienced users) interactive tools, Excel data tables, and summary reports. https://www.ncver.edu.au/research-and-statistics/data/databuilder#vis-students https://www.ncver.edu.au/research-and-statistics/vocstats Email: vocstats@ncver.edu.au

To request access to identifiable data, researchers need to email NCVER by contacting vet_req@ncver.edu.au for surveys or administrative data.

Geographic coverage: national, states and territories, SA2.

More Information: VET in Schools 2023 https://www.ncver.edu.au/research-and-statistics/publications/all-publications/vet-in-schools-2023

NCVER policies https://www.ncver.edu.au/research-and-statistics/accessing-vet-data

VOCEDplus Database voced.edu.au/challenge?destination=%2Fstatistical-resources

National VET data https://www.dewr.gov.au/national-vet-data?utm

Email: ncver@ncver.edu.au

Data Custodian/Owner: National Centre for Vocational Education Research (NCVER)

Source of Metadata Extraction: https://www.ncver.edu.au/research-and-statistics/collections/vet-in-schools

03.09.2025

Archived on 08.12.2025: https://www.ncver.edu.au/research-and-statistics/collections/vet-in-schools

Students and Courses

Purpose: The Students and Courses Collection provides information on the number of students and full year training equivalents, participation rates, program and subject enrolments, program completions and training providers. Its purpose is to capture data on the delivery of nationally recognised training by Registered Training Organisations (RTOs), covering both government-funded and fee-for-service activity.

The collection enables analysis of VET participation trends over time. It records the number of students, their demographic characteristics, enrolments in programs and subjects, program completions, and the volume of training delivered in hours. Researchers can use these data to investigate participation by age, gender, Indigenous status, or location, as well as to assess how VET pathways contribute to skills development and workforce supply. The collection underpins government monitoring and evaluation of the VET system.

Main Topic: Childcare, education, and training

Other topics:

Demographics

Subtopics:

Training activity
Qualification level
Field of education
Training packages
Provider information
Student participation
Program completion/outcomes

Included into an integrated data asset:

NCVER

Population scope: All students enrolled in nationally recognised vocational education and training (VET) programs or subjects delivered by Australian Registered Training Organisations (RTOs).

Geographic scope: Australia (national)

Temporal range: 1994-ongoing

Temporal Unit/Frequency: Quarterly and annually

Unit of Observation: Individual person

Type of Unit of Observation: Individual

Collection & Compilation Methods: The National VET Provider Collection (from which the Students and courses data releases are produced) collects data on vocational education and training (VET) delivered by Australian training providers, to a nationally agreed standard.

The collection has historically reported on government-funded VET, which is broadly defined as Commonwealth and state/territory government-funded training delivered by TAFE institutes and other government providers, community education and other registered providers. This is collected and reported quarterly.

In 2014, the scope of the collection was expanded to include total VET activity. This collection covers all onshore and offshore nationally recognised VET activity delivered by Australian registered training organisations (RTOs) and reports on students who undertook VET on a government funded or fee-for-service basis. This is collected and reported annually.

Data are submitted to NCVER either directly by RTOs or through state and territory training authorities. Information covers student characteristics, providers, program and subject enrolments, completions, training hours, and funding sources. Once submissions are validated and compiled, NCVER removes duplicate activity and prepares the data for national reporting.

Two main reporting products are derived from the Students and Courses dataset. The Government-funded students and courses release provides statistics on onshore government-funded VET activity only, while the Total VET Activity (TVA) release covers the full scope of nationally recognised training, whether funded publicly or delivered on a fee-for-service basis. Together, these outputs provide a comprehensive view of how Australians engage with VET.

Data Quality (Scope): Pre-2014 coverage was limited to government-funded training activity only, meaning students enrolled in fee-for-service training were excluded. This provided partial coverage of the national VET population.

From 2014 onwards the scope was expanded to include Total VET Activity (TVA), covering all students enrolled in nationally recognised VET delivered by Australian RTOs, regardless of funding source (government-funded or fee-for-service, domestic or international, onshore or offshore). This provides near-complete coverage of the intended population. Remaining exclusions: • Non-accredited training (not part of the national training system). • Some potential under-reporting where providers fail to submit or provide incomplete data (though compliance is strong due to regulatory requirements).

Data Quality (Other): Some fields that rely on self-identification (e.g., Indigenous status, disability status, language background) are prone to under-reporting or missing values, which affects subgroup coverage rather than the overall population count. Offshore delivery by Australian RTOs has been included since 2014, but coding of country and mode of delivery is sometimes inconsistent, limiting the reliability of offshore breakdowns.

Data Access: The SCC data is not released as a full unit-record dataset for general use. However, aggregated statistics derived from SCC are available through NCVER’s DataBuilder, VOCSTATS (for experienced users) interactive tools, Excel data tables, and summary reports. https://www.ncver.edu.au/research-and-statistics/data/databuilder# https://www.ncver.edu.au/research-and-statistics/vocstats Email: vocstats@ncver.edu.au

To request access to identifiable data, researchers need to email NCVER by contacting vet_req@ncver.edu.au for surveys or administrative data.

Geographic coverage: national, states and territories, SA2.

More Information: Government-funded students and courses https://www.ncver.edu.au/research-and-statistics/collections/students-and-courses-collection/government-funded-students-and-courses

Total VET students and courses https://www.ncver.edu.au/research-and-statistics/collections/students-and-courses-collection/total-vet-students-and-courses

VET qualification completion rates https://www.ncver.edu.au/research-and-statistics/collections/students-and-courses-collection/vet-qualification-completion-rates

National VET data https://www.dewr.gov.au/national-vet-data?utm

Email: ncver@ncver.edu.au

Data Custodian/Owner: National Centre for Vocational Education Research (NCVER)

Source of Metadata Extraction: https://www.ncver.edu.au/research-and-statistics/collections/students-and-courses-collection

03.09.2025

Archived on 08.12.2025: https://www.ncver.edu.au/research-and-statistics/collections/students-and-courses-collection

National Student Outcomes Survey (NSOS)

Purpose: The National Student Outcomes Survey (NSOS) collects information on VET students’ reasons for training, their employment outcomes, satisfaction with training, and further study outcomes. It aims to gather information that helps enhance the social and economic outcomes of students who undertake vocational education and training (VET) in Australia. The survey data helps training providers and government bodies improve the quality, relevance, and effectiveness of VET programming.

Main Topic: Childcare, education, and training

Other topics:

Demographics

Subtopics:

Reasons for VET training
Satisfaction with training
Further study
Employment outcomes
Reasons for non-completion

Included into an integrated data asset:

NCVER

Population scope: Students aged 15 years and over who have completed at least one subject of recognised vocational education and training (VET) in Australia during the previous calendar year

Geographic scope: Australia (national)

Temporal range: 2017-ongoing

Temporal Unit/Frequency: Annually

Unit of Observation: Individual student

Type of Unit of Observation: Individual

Collection & Compilation Methods: The National Student Outcomes Survey (NSOS) is administered each year by the National Centre for Vocational Education Research (NCVER) to capture information about the experiences and outcomes of students who have completed vocational education and training in the previous calendar year. Data collection is carried out through a large-scale survey process. Eligible students are contacted using details drawn from the National VET Provider Collection, which records enrolments and completions across the sector. Invitations are distributed by email, SMS or post, and students are encouraged to respond through an online survey platform. To improve coverage, follow-up phone interviews are also undertaken by a contracted research organisation.

The survey gathers detailed information on students’ motivations for undertaking training, their satisfaction with the course and provider, their employment situation before and after training, their further study outcomes, and where relevant, their reasons for not completing the training.

The survey has three main stages. 1. Project preparation (March to June). NCVER selects the sample of students. Contact details of selected students are then provided directly to the fieldwork contractor by NCVER, State Training Authorities or the Office of the Student Identifiers Registrar (OSIR).

Fieldwork (June to August). Invitations are sent in June via email, SMS or hard-copy letter, depending on the availability of contact details. Survey invitations include a unique login code and/or a link for accessing the online survey. Email, letter and/or SMS reminders are sent to students if they haven’t completed the survey. From July, some students may get a follow-up phone call to complete the survey by phone.

3.Data analysis and reporting (September to March). Responses are checked and analysed. Results are prepared for release.

Results of the Student Outcomes Survey are published late November/early December each year.

Once collected, the data undergoes cleaning and coding to ensure accuracy and consistency across all records. It is then weighted to adjust for survey design and non-response, so that the results are representative of the wider VET graduate population. The cleaned and weighted data is integrated with the administrative information from the National VET Provider Collection, which provides a robust statistical foundation.

Data Quality (Scope): The survey covers students who have an Australian address as their residential address (VET student outcomes) and, from 2017 to 2023, international students who completed their training onshore in Australia (International onshore VET qualification completer outcomes). It includes: • Qualification completers: Students who completed a training package qualification or accredited qualification. • Qualification part-completers: Students who enrolled in but only completed part of a training package qualification or accredited qualification (and are no longer undertaking that training). • Short course students: Students who have completed or partially completed, and are no longer undertaking, a training package skill set or accredited course. • Subject(s) only completers: Students who completed one or more subjects not delivered as part of a nationally recognised program and who are no longer undertaking training in the VET sector.

Data Quality (Other): The NSOS is not a census but a sample survey, so the responses collected must be weighted to reflect the national population of VET graduates. This weighting corrects for differences in response rates across demographic groups, training providers, qualifications and fields of study. Despite this, some sub-groups of students may remain under-represented if response rates are low, and this can limit the reliability of detailed breakdowns.

Some students may be less likely to respond, for example, those who are disengaged from study, did not complete their training, or who have changed contact details. NCVER mitigates this risk through follow-up reminders and the use of multiple survey modes (online and phone), but there remains the potential for bias in the results.

Data Access: NCVER produces national summary reports and detailed statistical tables for public use, as well as infographics that highlight key findings.

Users can access more flexible tabulations by using DataBuilder and VOCEDplus: https://www.ncver.edu.au/research-and-statistics/data/databuilder#sos-tva https://www.voced.edu.au/pod-student-outcomes

Researchers can also apply for access to de-identified microdata through NCVER’s data access arrangements. Email: support@ncver.edu

More Information: VET student outcomes 2024 https://www.ncver.edu.au/research-and-statistics/publications/all-publications/vet-student-outcomes-2024

National Student Outcomes Survey 2024: data dictionary https://www.ncver.edu.au/research-and-statistics/collections/student-outcomes/vet-student-outcomes/national-student-outcomes-survey-2024-data-dictionary

How to interpret survey results https://www.ncver.edu.au/__data/assets/pdf_file/0037/9692704/2024_SOS_How_to_interpret_survey_results.pdf

Email: ncver@ncver.edu.au vet_req@ncver.edu.au

Data Custodian/Owner: National Centre for Vocational Education Research (NCVER)

Source of Metadata Extraction: https://www.ncver.edu.au/research-and-statistics/collections/student-outcomes

04.09.2025

Archived on 08.12.2025: https://www.ncver.edu.au/research-and-statistics/collections/student-outcomes

National VET Funding Collection

Purpose: The purpose of the National VET Funding Collection is to provide information on the flow and distribution of government contributions that stimulate or support publicly-subsidised vocational education and training (VET) activity in Australia.

Main Topic: Childcare, education, and training

Other topics:

Subtopics:

Jurisdictions’ contributions and allocations
Funding activity and distribution
VET delivery
Employer assistance
Student assistance
Capital funding
System administration and governance
Funding for VET student loans

Included into an integrated data asset:

NCVER

Population scope: All public funding for vocational education and training (VET) provided by the Australian Government and the state and territory governments

Geographic scope: Australia (national)

Temporal range: 2017-ongoing

Temporal Unit/Frequency: Annually

Unit of Observation: Funding activity

Type of Unit of Observation: Event/Process/Activity

Collection & Compilation Methods: VET funding data has three distinct parts: jurisdictions’ contributions and allocations; funding activity and distribution including funding activities and distributions (excluding loan values) and funding for VET Student Loans and public VET asset base.

Reporting includes direct and indirect funding for VET including employer incentive programs for workforce training.

The National VET Funding Collection began in 2017, with a subset of data collected and reported for 2017 and 2018, and full implementation from 2019 onwards. This collection has replaced the previous National VET Finance collection.

The data are supplied by the Australian Government Department of Employment and Workplace Relations and the state and territory training authorities, along with other relevant bodies as applicable. This ensures that all sources of public VET funding are captured. 

This is a jurisdictional-level financial reporting collection. It collects aggregated funding figures to align transparently with VET activity data for national reporting, policy analysis, transparency, and accountability. NCVER checks the submitted data for accuracy, consistency, and coherence with previous years. Once validated, NCVER compiles the data into a national dataset which presents aggregate-level financial information.

Data Quality (Scope): The completeness of the VET Funding Collection is high from 2019 onwards, when the collection became fully implemented under the new national financial reporting framework. Since then, it has captured the entire population of government funding flows into the VET system, with data supplied annually by the Australian Government and all state and territory training authorities.

The coverage includes recurrent and capital funding, student and employer assistance, system administration, and valuation of public VET assets, ensuring comprehensive reporting of public expenditure. Earlier years (2017–18) represent a transitional phase with partial coverage, and the collection does not include private or employer-only contributions outside government reporting.

Data Quality (Other): Some fields that rely on self-identification (e.g., Indigenous status, disability status, language background) may have under-reported or missing values, which affects subgroup coverage. Offshore delivery by Australian RTOs has been included since 2014, but coding of country and mode of delivery is sometimes inconsistent, limiting the reliability of offshore breakdowns.

Data Access: Summary statistics and standard tables are openly available to anyone via NCVER’s website.

Users can access more flexible tabulations by using DataBuilder and VOCEDplus: https://www.ncver.edu.au/research-and-statistics/publications/all-publications/government-funding-of-vet-2023 https://www.voced.edu.au/pod-funding

Individual-level data is not available.

More Information: Framework for the VET Funding Collection https://www.ncver.edu.au/research-and-statistics/collections/vet-funding/the-national-vet-funding-collection-explained

Government funding of VET 2023 https://www.ncver.edu.au/research-and-statistics/publications/all-publications/government-funding-of-vet-2023

Terms and definitions: Government funding of VET 2023 https://www.ncver.edu.au/__data/assets/pdf_file/0040/9692761/Government-funding-of-VET-2023-terms-and-definitions.pdf

Email: ncver@ncver.edu.au

Data Custodian/Owner: National Centre for Vocational Education Research (NCVER)

Source of Metadata Extraction: https://www.ncver.edu.au/research-and-statistics/collections/vet-funding

04.09.2025

Archived on 08.12.2025: https://www.ncver.edu.au/research-and-statistics/collections/vet-funding

The Longitudinal Surveys of Australian Youth (LSAY)

Purpose: Longitudinal Surveys of Australian Youth (LSAY) provides an understanding of the key transitions and pathways in the lives of young people, particularly the transitions from compulsory schooling to further education, training and the labour market. LSAY also helps to inform policy development by governments to provide more effective support to young people.

Main Topic: Childcare, education, and training

Other topics:

Demographics

Subtopics:

Student achievement and aspirations
Attitudes to school
School characteristics
Subject choice
Post-school plans
Social background
Vocational and further education
Employment and job seeking
Satisfaction with various aspects of life
Living arrangements
Financial difficulties
Volunteering activities

Included into an integrated data asset:

NCVER

Population scope: Young people in Australia who are around 15 years of age at the time of recruitment

Geographic scope: Australia (national)

Temporal range: 1995-ongoing

Temporal Unit/Frequency: Annually

Unit of Observation: Individual student

Type of Unit of Observation: Individual

Collection & Compilation Methods: The Longitudinal Surveys of Australian Youth (LSAY) uses large, nationally representative samples of students at school to collect information about education, training, work, financial matters, health, social activities, and related issues.

The LSAY focus on the progress of young Australians as they move from their mid-teens to their mid-20s. It includes surveys conducted from the mid-1970s through to the mid-1990s: the Youth in Transition Survey (YITS); the Australian Longitudinal Survey (ALS); the Australian Youth Survey (AYS); and the current LSAY collection, which began in 1995.

LSAY uses large, nationally representative samples of students at school to collect information about education and training, work, financial matters, health, social activities and related issues. Since 2003, the initial survey wave has been integrated with the OECD Programme for International Student Assessment (PISA).

Data are initially collected through a combination of school achievement tests and a questionnaire administered at school. Subsequent data are gathered through annual telephone interviews. Since 2012, survey participants have had the option to complete their interview online.

LSAY operates on a cohort model. Every few years, a new nationally representative cohort of students is recruited, typically beginning at around age 15 when participants are in Year 9. Recruitment is usually linked to their participation in the OECD Programme for International Student Assessment (PISA), ensuring that the starting point for each cohort is both standardised and internationally comparable. From this base, the same individuals are then surveyed once a year in subsequent waves.

Since 1995, the first wave of data collection administered to students in schools included reading and numeracy tests and a background questionnaire for students about their educational and vocational plans and attitudes to school. Information was also obtained from their schools regarding curricula and school organisation. The second wave of data was gathered through a mailed questionnaire one year after the initial survey, and followed up with annual Computer-Assisted Telephone Interviews (CATI) from wave 3 onwards. In terms of structure, LSAY surveys each cohort for around 10 years. Currently, it consists of six cohorts beginning in 1995, 1998, 2003, 2006, 2009, and 2015 with more than 60,000 young Australians participating. This overlapping cohort design ensures continuity of data while also allowing changes across generations of young Australians to be examined.

Once the data have been collected, they are processed by the National Centre for Vocational Education Research (NCVER) in consultation with the Social Research Centre, which delivers the fieldwork. Responses are cleaned and coded to ensure consistency across variables and over time. Weights are then applied to correct for survey design and attrition, ensuring that the data remain representative of the national youth population despite inevitable dropout over the ten years of follow-up.

The cleaned and weighted survey responses from each wave are then linked together to form a longitudinal record for each participant. This cumulative design allows researchers to track changes in individual circumstances over time.

Data Quality (Scope): As a longitudinal survey, LSAY suffers from attrition, especially between the initial school-based wave and subsequent follow-ups. This can affect the representativeness of remaining respondents (e.g. students from low socio-economic backgrounds; those with weaker school engagements; CALD students).

Data Quality (Other): Many variables are collected annually using a standardised questionnaire, which ensures consistency across waves. However, some variables change wording, scope, or coding across different cohorts and survey years, which can affect comparability over time. LSAY’s Data Dictionary and Technical Papers note where variables are modified or discontinued.

Most LSAY variables (education participation, employment status, wellbeing, living arrangements, etc.) are self-reported. This is generally reliable for factual information (e.g. current education, job status), but more subjective measures (e.g. satisfaction, wellbeing, attitudes) are vulnerable to recall bias and social desirability bias. Data collection moved from school questionnaires in the first wave to annual telephone interviews, and in later years also to online surveys. These changes in mode can affect how some questions are understood or answered, introducing minor measurement differences.

Data Access: The following data tools provide quick and easy access to summary LSAY data so users can readily explore results from the LSAY surveys:

LSAY Quickstats (data presented as a series of tables and charts and includes information on education and employment pathways, as well as social indicators) https://www.lsay.edu.au/data/lsay-quickstats

Frequency tables (frequency tables provide the frequency counts for each data item in the LSAY datasets; available for each cohort at each survey wave) https://www.lsay.edu.au/search/all-publications?collection=ncver~sp-lsay-publications&facetScope=f.Publication%2520type%257Cx%3Dquestionnaires%2520and%2520frequency%2520tables&query=!showall&sort=date

Pivot tables (customised tables) https://www.lsay.edu.au/data/pivot-tables

LSAY unit record (including linked data) files are deposited with the Australian Data Archive (ADA) at the Australian National University. Access to the data is free via a formal request and registration process managed by the ADA.

The data can be accessed by registering with the ADA Dataverse: Select ‘Sign Up’ from the top right corner and complete the Dataverse registration form. You will need to validate you email address for your registration to be accepted by Dataverse.

Requesting access to the LSAY datasets: Navigate to the LSAY Dataverse and login to your ADA Dataverse account. Navigate to the LSAY cohort you want to access from the list of datasets. Note: If you want access to multiple cohorts at one time you can select this option when filling out the online application form. Scroll down to the data files, select the file type/s you wish to access. Click on ‘Request Access’ and complete the online application form. Users must comply with the terms and conditions outlined in the user undertaking in order to obtain access to the data. A notification email will be sent to you from the ADA. If your request is approved, you will be able to download the requested files via the LSAY Dataverse.

More Information: LSAY variable listing and metadata https://www.lsay.edu.au/publications/search-for-lsay-publications/2621

Questionnaires and frequency tables https://www.lsay.edu.au/search/all-publications?collection=ncver~sp-lsay-publications&profile=publications&facetScope=f.Publication%2520type%257Cx%3Dquestionnaires%2520and%2520frequency%2520tables&query=%21showall&sort=date

User guides https://www.lsay.edu.au/publications/user-guides

Email: lsay@ncver.edu.au

Data Custodian/Owner: Department of Education

Source of Metadata Extraction: https://www.lsay.edu.au/data

05.09.2025

Archived on 08.12.2025: https://www.lsay.edu.au/data

The Employers’ Use and Views of the VET System (EUV-VET)

Purpose: The aim of the Employers’ use and views of the VET system survey (EUV-VET) is to provide information on employer engagement and satisfaction with vocational education and training in meeting the skill needs of their workforce.

The data from the survey provides the Australian government and state and territory governments with a strategic monitor over time of employer use of the VET system and how relevant the system is to training their workforce

Main Topic: Childcare, education, and training

Other topics:

Organisational characteristics

Subtopics:

Employer engagement with VET
Types of training used
Employer Satisfaction with training
Reasons for training decisions
Training providers
Employer skills need

Included into an integrated data asset:

NCVER

Population scope: All organisations in Australia with at least one employee even if they have not used any training

Geographic scope: Australia (national)

Temporal range: 1995-ongoing

Temporal Unit/Frequency: Biennially

Unit of Observation: Employer organisation

Type of Unit of Observation: Organisation

Collection & Compilation Methods: The survey collects information on the various ways employers meet their skill needs. Through accredited training this may include hiring staff with vocational qualifications, employing apprentices and trainees, or providing staff with other nationally recognised training. Employers can also utilise or provide unaccredited and other forms of training. The survey relates to employers’ training experiences in the preceding 12 months. The 2023 survey was conducted both online and using computer assisted telephone interviewing (CATI).

Fieldwork was conducted in two phases. Sampled employers were sent a personalised letter and brochure approximately two weeks before initial telephone contact to allow enough time for the letter to reach the appropriate person and to give time for those who wanted to complete the survey online to do so. The letter and brochures were sent in four separate batches throughout the fieldwork period to ensure that employers were contacted in a timely manner.

Once collected, responses are cleaned, coded, and weighted to ensure representativeness. As the 2023 survey was undertaken as a sample rather than a census, responses have been weighted to represent population benchmarks of in scope organisations from the ABS Business Register at the time of sampling. In order to represent the ABS Employers’ population benchmarks, two weighting stages were applied. First the data were adjusted for non-response using the illion population (used as the sampling frame) and then weighted to the ABS population benchmarks using the following stratification variables: state (each of the 8 states and territories); industry (19 ANZSIC divisions) ; and employer size (small = 1-9 employees, medium = 10-99 employees, large = 100 or more employees). NCVER then compiles the data into structured outputs, producing both unit-record datasets (for research use) and statistical summaries published in reports and tables.

Data Quality (Scope): The survey is designed to be nationally representative of Australian employers with at least one employee. This is achieved through stratified sampling by industry, size, and location, with survey weights applied to correct for differences in response rates. Results can therefore be generalised to the population of employers. Some groups of employers (e.g., very small businesses) may be harder to reach, and weighting only partially corrects for this.

The survey excludes employers with no employees (sole traders/self-employed), so findings apply only to businesses that employ at least one person.

Data Quality (Other): Core factual measures such as whether an employer uses apprentices/trainees, provides nationally recognised training are usually of high quality. Subjective variables such as measures of satisfaction are more prone to bias.

Some questions were removed after COVID-19 and new questions have been introduced to reflect emerging training issues which may affect comparability between the different waves. More details are available in the technical notes.

Data Access: NCVER publishes summary findings and reports every November in each survey year, detailing key metrics. Detailed outputs such as data tables are available: https://www.ncver.edu.au/research-and-statistics/data/all-data/employers-use-and-views-of-the-vet-system-2023-data-tables?utm

A time-series data visualisation is also provided: https://www.ncver.edu.au/research-and-statistics/data/all-data/employers-use-and-views-of-the-vet-system-2023-time-series

For researchers needing non-aggregated, unit-record (de-identified) data, NCVER offers customised data services on a cost-recovery basis.

Geographic coverage: national, states and territories.

More Information: Employers’ use and views of the VET system 2023 https://www.ncver.edu.au/research-and-statistics/publications/all-publications/employers-use-and-views-of-the-vet-system-2023?utm

Employers’ use and views of the VET system: history of employer survey https://www.ncver.edu.au/__data/assets/file/0022/9085/SEUV_2021_History_of_the_survey.pdf

Email: surveys@ncver.edu.au

Data Custodian/Owner: National Centre for Vocational Education Research (NCVER)

Source of Metadata Extraction: https://www.ncver.edu.au/research-and-statistics/collections/employers-use-and-views-of-the-vet-system?utm

09.09.2025

Archived on 08.12.2025: https://www.ncver.edu.au/research-and-statistics/collections/employers-use-and-views-of-the-vet-system?utm

Temporary Visa Holders in Australia (TE)

Purpose: The Temporary Visa Holders in Australia (TE) dataset aims to provide a reliable statistical snapshot of all people present in the country on a temporary visa at a given point in time. By offering this point-in-time perspective, the dataset serves as an essential tool for understanding the role of temporary migration in Australia’s population.

Main Topic: Demographics

Other topics:

Subtopics:

Student visas
Temporary skilled work visas
Working holiday visas
Bridging visas
Special category visa
Trends over time

Included into an integrated data asset:

ACTEID
PLIDA

Population scope: All individuals in Australia on a temporary visa

Geographic scope: Australia (national)

Temporal range: 2014-ongoing

Temporal Unit/Frequency: Quarterly

Unit of Observation: Individual person

Type of Unit of Observation: Individual

Collection & Compilation Methods: The Temporary Visa Holders in Australia dataset is derived directly from the administrative systems of the Department of Home Affairs. These systems maintain authoritative records on visa grants, conditions, and the legal status of non-citizens in Australia. On a specified reference date—usually the end of a quarter—the Department extracts a point-in-time count of all people who hold a valid temporary visa and are present in the country. This includes New Zealand citizens on Special Category visas (subclass 444).

Each visa grant, arrival, and departure is logged in the Department’s Integrated Client Service Environment (ICSE). To produce the dataset, records are compiled to identify individuals who are lawfully in Australia on the reference date. Departures, expired visas, and cancelled visas are excluded so that only current temporary entrants are counted.

For public release, the raw administrative records are aggregated into tabulations. Data are grouped by visa subclass and can be further disaggregated by demographic and citizenship characteristics, such as age, sex, or country of citizenship. In addition to these direct extracts, the dataset can be used in statistical data integration projects. Data integration combines information from different sources—administrative, survey, and census data—to produce richer datasets for research and policy analysis. This process often involves data linkage, in which unit records representing individual persons are linked across datasets using common identifiers. As part of the Australian Census and Temporary Entrants Integrated Dataset (ACTEID), the estimates are calibrated to the total number of temporary visa holders in Australia on Census Night. This calibration accounts for unlinked records by assigning weights to linked records, ensuring the integrated dataset is representative of the full temporary visa holder population. The 2021 calibration method was broadly consistent with the approach used in 2016, adjusting for characteristics such as age, sex, visa information, and country of birth.

Data Quality (Scope): Data quality is generally high. It includes all people in Australia on a temporary visa at the reference date (student, work, visitor, bridging, working holiday, etc.). There is no sampling because the dataset is based on the full administrative register of visa holder.

Data Quality (Other): Strong quality variables – visa subclass, country of citizenship, age, are recorded from visa applications and are generally reliable. Visa subclass codes may change over time with policy reforms which complicates longitudinal analysis.

Data Access: The Temporary Entrants Visa Holders dataset is made publicly available by the Department of Home Affairs through the Australian Government’s open data portal, data.gov.au. Releases are published on a quarterly basis and provide a snapshot of the number of people in Australia holding temporary visas at the reference date. Historical releases are available from 2014 onwards, which allows for time-series analysis of changes in the stock of temporary visa holders over time. Each release includes CSV files and accompanying metadata that describe the contents and structure of the dataset.

Publicly available files contain only aggregated tabulations. De-identified unit record data, is not released due to privacy and confidentiality requirements. Researchers who need access to microdata or customised extracts must apply directly to the Department of Home Affairs or through approved data integration projects, such as PLIDA. Such access is subject to governance processes, ethics approvals, and strict confidentiality agreements.

Geographic coverage: national, state/territory levels

More Information: Temporary Visa Holders- ABS https://www.abs.gov.au/statistics/people/people-and-communities/temporary-visa-holders-australia/latest-release?utm

Temporary Visa Holders in Australia – Methodology https://www.abs.gov.au/methodologies/temporary-visa-holders-australia-methodology/2021?utm_

Email: Statistical.coordination@homeaffairs.gov.au

Data Custodian/Owner: Australian Government Department of Home Affairs

Source of Metadata Extraction: https://data.gov.au/data/dataset/temporary-entrants-visa-holders?utm

10.09.2025

Archived on 08.12.2025: https://data.gov.au/data/dataset/temporary-entrants-visa-holders?utm

National Prisoner Census (NPC)

Purpose: The National Prisoner Census (NPC) was established to provide a comprehensive statistical picture of the prison population in Australia. Its primary purpose is to count and describe all persons held in adult corrective services facilities across the country on a single reference date – 30 June each year. It aims to provide a national view of adult prisoners in Australia, as well as comparable data across states and territories, and provide a basis for measuring change over time.

Main Topic: Justice

Other topics:

Demographics

Subtopics:

Legal status
Sentence details
Type of custody
Offence type
Imprisonment rates

Included into an integrated data asset:

Population scope: All persons remanded or sentenced to adult custodial corrective services agencies in each state and territory in Australia

Geographic scope: Australia (national)

Temporal range: 1982-ongoing

Temporal Unit/Frequency: Annually

Unit of Observation: Individual prisoner

Type of Unit of Observation: Individual

Collection & Compilation Methods: Data are collected from the administrative records of correctional authorities in each state and territory. On the reference date jurisdictions extract a record for every adult prisoner held in custody in their facilities. This includes information on demographic characteristics (such as age, sex, Indigenous status), legal status (sentenced or unsentenced), offence type, sentence length, and other relevant custodial details. Once these records are supplied to the ABS, they undergo a process of standardisation and validation. Each jurisdiction uses its own information management systems, and variables may differ in naming or coding. The ABS applies consistent classifications, definitions, and coding frameworks to harmonise the data nationally. This includes using standard offence classifications and ensuring uniform treatment of demographic variables like Indigenous status. Compilation involves aggregating the validated unit-level records into a national dataset. The ABS checks for data quality issues such as duplicate records, inconsistencies in offence coding, or implausible values. The final output is a complete count of all prisoners in Australia on the census night, presented in tables and analyses that describe the size, composition, and characteristics of the prison population. The Prisoner Census is taken on 30 June each year, with the publication usually released in December of that year. The main publication is Prisoners in Australia, with a set of companion tables released in Excel spreadsheets on the same day. The companion tables reflect the information contained in the main publication, further disaggregated by state and territory.

Data Quality (Scope): Included in the National Prisoner Census are prisoners in the legal custody of corrective services but who, at the time of the census, were: absent on an authorised temporary leave permit; absent from the correctional facility on a work release permit or program; located in secure wards in a hospital outside the correctional facility; periodic detainees. Excluded from the collection are: prisoners who were unlawfully absent from corrective services legal custody, e.g. escapees or prisoners who failed to return from an authorised temporary absence from a correctional facility; prisoners whose legal custody had been transferred to another agency, e.g. police or mental health institutions. The count of periodic detainees covers the number of persons with an active periodic detainee warrant. However, periodic detainees who have breached orders may be excluded.

The types of correctional facilities and programs where prisoners are held varies between the states and territories.

Included in the collection are: gazetted adult prisons in all jurisdictions; periodic detention centres in New South Wales and the Australian Capital Territory; community custody centres and work camps in Queensland; cells in court complexes administered by corrective services in New South Wales; transitional centres in New South Wales; lock-ups in Western Australia operated by the police but designated as a prison by the Chief Executive Officer of Corrective Service; gazetted police prisons in the Northern Territory which are administered and controlled by the Director of Corrective Services. Excluded from the collection are persons held in facilities administered and controlled by other agencies: police lock-ups, police prisons and cells in court complexes; immigration detention centres; home detention programs; military prisons; mental health facilities; juvenile facilities, including those under the authority of adult corrective services.

Data Quality (Other): Each state and territory manages its own correctional information systems. While the ABS applies standard definitions and classifications (e.g., ANZSOC for offences, Indigenous status standards), there can still be differences in how jurisdictions record or code data. Indigenous status is under-reported.

The Census provides a snapshot on 30 June each year. It does not capture flows in and out of prison, such as admissions and discharges during the year.

Data Access: Key results, tables, and data cubes are published free of charge in Prisoners in Australia. These include national and state/territory breakdowns by age, sex, Indigenous status, legal status, offence, and sentence length.

Standardised data tables (in Excel/CSV format) are made available on the ABS website with each annual release.

Special tabulations may be produced on request to meet individual user requirements. For further information about these and related statistics visit www.abs.gov.au/about/contact-us

NPC unit record microdata are generally not released publicly, due to sensitivity and confidentiality restrictions. However, researchers may be able to apply for secure access through ABS’s DataLab.

Geographic coverage: national, states and territories.

More Information: The collection was established in 1983 by the Australian Institute of Criminology (AIC). The AIC maintained the collection until June 1993. In September 1995 the ABS took over responsibility for the collection and has undertaken the publication of all national corrective services statistics from June 1994 onwards. The first official ABS release of Prisoner Census statistics was through the 2000 publication, Prisoners in Australia. Prior to this, the data were presented as an annual report for the Corrective Services Ministers’ Council by the National Corrective Services Statistics Unit. From 2000 onwards, the following history is relevant: 2001 - The Australian Standard Offence Classification 1997 replaced the Australian National Classification of Offences, resulting in a break in series for some offence types. Imprisonment rates by birthplace were also introduced; 2002 - The calculation of imprisonment rates for NSW and the ACT was changed; 2003 - Scope changes were made to include prisoners held in community custody centres and work outreach camps in Queensland. The definition of an episode changed in consultation with the National Corrections Advisory Group. Tasmania introduced the National Offence Index (NOI) to determine most serious offence/charge; 2004 - Historical rates for total prisoners, and Indigenous prisoners, were revised using population estimates benchmarked on the 2001 Census of Population and Housing and back cast for the period 1994 to 2003. Prior to 2004 rates for all states and territories were calculated using adult population for persons aged 17 and over. For 2004 and 2005 adult population figures used in the calculation of rates changed to persons aged 18 years and over for all states and territories except for Victoria and Queensland, where the adult population used was that of persons aged 17 years and over. From 2006 the definition of an adult changed to 18 years and over for Victoria. The rules for determining the most serious offence for prisoners returning to prison with a breach of parole were also modified; 2006 - The NOI was introduced to determine most serious charge in Victoria, Queensland, South Australia, and the Australian Capital Territory. Tasmania continued to use the NOI for most serious offence/charge; 2007 - The Northern Territory introduced the NOI to determine most serious charge; 2008 - New South Wales introduced the NOI to determine most serious charge; 2009 - The Australian Standard Offence Classification 2008 (ASOC08) replaced the Australian Standard Offence Classification 1997 (ASOC97); and the revised National Offence Index 2009 replaced the 2002 National Offence Index. All states and territories, except Queensland and Western Australia implemented the ASOC08 for the 2009 collection. Queensland and Western Australia continued to use the ASOC97. Historical rates by Indigenous status were updated based on Indigenous population projections data benchmarked on 2006 Census of Population and Housing data; 2010 - Queensland and Western Australia implemented ASOC08. National offence data all presented on an ASOC08 basis; 2011 - Offence data are based on the Australian and New Zealand Standard Offence Classification (ANZSOC) (cat. no. 1234.0). The Australian Standard Offence Classification 2008 (ASOC08) was renamed ANZSOC in July 2011. ANZSOC contains the same offence details and classification as ASOC08 and therefore there were no impacts on offence data in the publication.

Prisoners in Australia, 2024 https://www.abs.gov.au/statistics/people/crime-and-justice/prisoners-australia/2024

Prisoners in Australia, 2024, Methodology https://www.abs.gov.au/methodologies/prisoners-australia-methodology/2024