Geospatial data analysis and data linkage work at the AIHW Evolving approaches to answer more complex questions

Who are we? Major national information and statistics agency with a specialist focus on Australia’s health and welfare Independent statutory agency established under the AIHW Act (1987) Strong collaborations with governments, government agencies such as the ABS and PC, and NGOs Annual budget of around $45m with staff around 400

What do we do? Custodian of major national health and welfare collections Manage range of health and CS statistical infrastructure such as data standards Provide information and analysis across health, housing and community services sectors in around 150 reports a year Increasing contribution to performance reporting related to government services in the health and welfare sectors Manage the MyHospitals website Taking on an expanding national role in relation to data linkage

4 Current state – geospatial work Emerging interest and pockets of capability Growing recognition of power and importance of geospatially based analysis Project based approach to geospatial analysis Most reports contain basic geographic analysis (ARIA, SEIFA) Focus is on implementation of ASGS into collection design and reporting, but… Very low dedicated resource for staff or necessary infrastructure

Measurement of Access to GP Care for Indigenous Australians A pilot project

6

7 Pilot test Western Australia only Proof of concept test Does methodology work? Is there variation across areas? Preliminary analyses conducted at the Census Collection District level (4352 CDs)

8 Index Creation Index of AccessIndex of Need for GP services Index of Access compared to Need

9 Map 1 First step: collate basic information on location of GP services and density of indigenous population

10 Map 1

11 Requirements for measuring Access GIS software (MapInfo) Health services: FTEs and addresses Medical Directory of Australia, DoHA, RFDS, WAH Geocode the addresses (free online geocoder) Routing Data (Drivetime) CD boundary data (ABS) CD population data (ABS)

12 Spatial accessibility index Data on FTEs, locations, drive times, and population are used to construct weighted population/provider ratios for each service location An accessibility score for each CD is then calculated using those data Result: a numerical index where higher values indicate higher spatial accessibility

13 Step 2: Construct access index

14 Step 3: Construct needs index

15 Combined index of access & needs The health needs index is used to adjust the spatial access index The combined index provides a relative measure of access and needs Areas with a higher index have better access to primary care, adjusted for underlying health needs

16

17

18 Strengths of the approach Can analyse access at a small geographical level, even mesh block (2011) Can incorporate need for services if necessary Numerical index quantifies differences Maps make it easy to see differences Can conduct “what-if” analyses Approach can be used for other services Policy implications Comparisons across areas Identify areas requiring greater services Measure impact of change

19 Potential drawbacks to the approach Complex methodology Relative index may be hard to interpret Measuring change over time in health needs requires administrative data at higher geographic levels Currently cannot include other modes of transport

Data linkage at the AIHW

21 Data linkage at the AIHW creating person records from event-based data assessing and improving the quality of information on selected administrative data sets supplementing information on one data set with information from other data sets to investigate complex health and welfare issues for which no single data set can provide a complete picture establishing pathways through health and community services through the linkage of multiple clinical, health care and community services data sets creating researchable databases containing information from multiple sources

Current state – data linkage work 15 years data integration experience (87 projects last year) highly skilled staff the protection of privacy and confidentiality under established privacy and ethics regime detailed knowledge of, and experience with many, national datasets experience with dealing with many data custodians technical capability and resources for management and analysis of large complex datasets Now an accredited Commonwealth Integrating Authority

Linkage projects approved at one Ethics Committee Health-related quality of life and long term survival of patients after cardiac surgery The Australian Paediatric Cancer Registry Psychopathology following traumatic injury: screening for high risk Investigating the long term psychological impact of bushfire exposure Sedation practices in intensive care in Australia and New Zealand Impact of opioid substitution therapy Geelong osteoporosis study Australian and New Zealand Diabetes and Cancer collaboration National Diabetes Register Validation of the Enhanced Indigenous Mortality Database using NSW Native Title register data

Some examples of linkage projects For outside researchers: CT scans in children Complex data flows: Diabetes Care Pilot AIHW long-term research: Pathways in Aged Care

CT Scans in Children and Cancer Exposure DataIncidence Data Is there a link?

Diabetes Care Pilot Three-year pilot of a new model of healthcare delivery designed to improve care for people with diabetes, 150 practices in three states Comparing two intervention groups of general practices and a control group Elements include better information sharing, flexible funding model, Care Facilitator role, education and training programs. AIHW managing data flow and undertaking linkage

PHC AIHW McKinsey State Health Depts Uni SA Patient Identifiers Survey Data Patient Identifiers Survey Data Enrolment Information Patient Identifiers Linked Hospital Data DoHA MBS Data PBS Data MBS Data PBS Data DCP Participants GPs Diabetes Aust. Patient Enrolment Survey Data NDSS data Enrolment Information Practice data (e.g. payments) Practice data De-identified Evaluation Data National Death Index

Pathways: system view

Pathways: person view

Broad strategy: 7 linkage stages Source: Karmel et al. 2010

Data linkage The linkage resulted in: …linking records of episodes of service use …at the person level …to allow statistical analysis of pathways

Case studies: home→package→permanent RAC HACC (Example only)

First program after assessment

Addressing a policy issue: DoHA asked “are people having unnecessary assessments?”

Data linkage future developments Consolidation of new system Continuing growing collaboration with data custodians, other data linkage institutions and researchers Increasing number and variety of projects Increasing complexity of AIHW role