Geospatial data analysis and data linkage work at the AIHW - Evolving approaches to answer more complex questions
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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 • 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
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
4
Measurement of
Access to GP Care
for Indigenous Australians
A pilot project
6
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)
7Index Creation
Index of Need for GP services Index of Access
Index of Access compared to Need
8Map 1
First step: collate basic
information on location
of GP services and
density of indigenous
population
9Map 1
10Requirements 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)
11Spatial 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
12Step 2: Construct
access index
13Step 3: Construct
needs index
14Combined 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
1516
17
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 18Potential 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
19Data linkage at the AIHW
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 21Current 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
Data Linkage under the IA Framework
Linkage and
linkage Validation
fields
Data Set 1
Data set and project
specific linkage keys
Data Users / Researchers
analysis
Data Secure data
Data Set 2 fields
Integration access
Integrating AuthoritySome 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
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 dataCT Scans in Children and Cancer
Is there a link?
Exposure Data Incidence DataDiabetes 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
Patient
Enrolment Uni Enrolment
McKinsey
Survey Data SA Information
Enrolment
DCP Information
Participants De-identified
Patient Identifiers Evaluation Data Practice data
Practice data
Survey Data (e.g.
payments)
National Death PHC
Index
AIHW
Diabetes NDSS data
Aust.
MBS Data
Linked Hospital PBS Data
Data
GPs
Patient Identifiers
State
Health DoHA
DeptsPathways in Aged Care (PIAC)
Pathways: system view
Pathways: person view
Broad strategy:
7 linkage stages
Source: Karmel et al. 2010Data 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
t † Period of 1st ACAT
Joe a CACP/EACH
Respite RAC
Permanent RAC
May
a a a † Death
a ta a Additional ACAT
a a †
John
t Transfer
Mary
a
†
James
a
Mabel
Year 1 Year 2 Year 3
(Example only)First program after assessment
50 No previous care group
41
40
Per cent
30
19 19
20
10
10 6 5
0
Death None HACC/VHC Package Respite Permanent
RAC
First program after assessmentAddressing a policy issue: DoHA asked “are
people having unnecessary assessments?”
80.0
70.0
Per cent of clients
Continuing path
60.0
50.0 HACC and/or VHC
before
40.0 No previous care
30.0
20.0
10.0
0.0
0 1 2 3 4+
Number of re-assessmentsData 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
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