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Paul Konings

Paul Konings

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Paul Konings

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  1. WHO GRAPHC . National Centre for   Geographic & Resources Analysis in Primary Health Care To enhance the capacity of Primary Health Care by using geographically based tools, methods, data and web-based mapping platforms to support research into primary health care. Paul Konings National Centre for Geographic & Resource Analysis in Primary Health Care (GRAPHC),Australian Primary Health Care Research Institute (APHCRI), Australian National University (ANU)Credits: Nicholas Glasgow, Kirsty Douglas, Danielle Butler, Bob Wells, Mark Carrozza, Andrew Bazemore, Bob Phillips, Michael Hewett

  2. WHY Challenges & Opportunities: Global: Population Growth Urbanisation Climate Change National: Aging Population Rural and Remote Chronic Disease Regional: Supply & Demand Budgets Resources Variation Technology: Connectivity Cloud Computing GIS Data: Big Data Access to data Demography Open Data Issues: Privacy & Confidentiality Expertise Information / Knowledge Paul Konings: GRAPHC, APHCRI, ANU

  3. WHY O. Gudes 2011 • Medicare Locals:L • Local Communities • Connected services • Where: Demand • Where: Services • Where: Gaps ML 401: pop: 534,000 Where Where Where Paul Konings: GRAPHC, APHCRI, ANU

  4. WHAT • Public Health & demographic datasets. • Spatial Analysis Tools. • Map-based Visualisation. • Location as data. Paul Konings: GRAPHC, APHCRI, ANU

  5. WHAT GRAPHC Resources Maps / Visualisations INFRASTRUCTURE Functionality G-Tag System: Geo-Attribution / Geo-Linking G-Tag System: Geo-Attribution / Geo-Linking Data, Data, Data Paul Konings: GRAPHC, APHCRI, ANU

  6. HOW G-Tag System Principles • Small Geography is Important • Privacy is Critical. Paul Konings: GRAPHC, APHCRI, ANU

  7. WHY G-Tag System Principles • Small geography is Important Paul Konings: GRAPHC, APHCRI, ANU

  8. WHY G-Tag System Principles • Small geography is Important • Socio-Economic Indexes for Areas (SEIFA) is a product developed by the ABS that ranks areas in Australia according to relative socio-economic advantage and disadvantage. The indexes are based on information from the five-yearly Census. • SEIFA 2011 is the latest version of this product and consists of four indexes: • The Index of Relative Socio-Economic Disadvantage (IRSD) • The Index of Relative Socio-Economic Advantage and Disadvantage (IRSAD) • The Index of Education and Occupation (IEO) • The Index of Economic Resources (IER). • Each index is a summary of a different subset of Census variables and focuses on a different aspect of socio-economic advantage and disadvantage. Paul Konings: GRAPHC, APHCRI, ANU

  9. HOW G-Tag System Principles • Small geography is Important 4350, Pop’n: 102,259, IRSAD: 975 4352, Pop’n: 24,802, IRSAD: 1049 West Moreton-Oxley MedicareLocal Paul Konings: GRAPHC, APHCRI, ANU

  10. HOW G-Tag System Principles • Small geography is Important Postcode = 4350 SA1’s: 264 AvgPop’n = 387 IRSAD: 765 – 1166 22 x National Decile = 1 12 National Decile = 10 Paul Konings: GRAPHC, APHCRI, ANU

  11. HOW HOW G-Tag System: Geo-attribution / Geo-linking 3. Researcher takes de-identified clinical data including GTAGs & undertakes research enquiry 1. Extract clinical data using extraction tool ie Pen- CAT General Practice General Practice 4. GTAG -> Spatial attributes using Geo-Attribution or Link to Statistics via Geo-Linking 2. Register Addresses using GRAPHC G-Tag Registration tool Patient Identifiable Data De-Identified Clinical Data Health Research / Administration Geo-Attribution / Geo-Linking / Geo-Processing Tools GRAPHC G-UI GRAPHC G-UI GTAG Address GTAG GRAPHC Database Region ID &/or Statistical Indicators 5. Review data spatially using GRAPHC Quick Themes tool 2 (a) GRAPHC Server-side geo-coding NB coordinates are NOT available. Paul Konings: GRAPHC, APHCRI, ANU

  12. HOW • Case study: • Looks at relationships between diabetes and socio-economic status. • We had access to patient clinical records. • Knowing where patients reside gives us an indication of their socio economic status. • What region has the highest spatial resolution AND SEIFA indicators (SA1). • Can we convert addresses to SA1 regions. Paul Konings: GRAPHC, APHCRI, ANU

  13. HOW G-Tag System Applied Paul Konings: GRAPHC, APHCRI, ANU

  14. HOW G-Tag System Applied Paul Konings: GRAPHC, APHCRI, ANU

  15. HOW G-Tag System Applied Paul Konings: GRAPHC, APHCRI, ANU

  16. HOW G-Tag System Applied Paul Konings: GRAPHC, APHCRI, ANU

  17. WHY ABS – Statistical Area 1 versus Postcodes Paul Konings: GRAPHC, APHCRI, ANU

  18. HOW GRAPHC Work Flow Model Geo-attributed Demographic & socio economic data. CSV Geo-attributed & Linked topic data. CSV Researcher 1 1 2 3 GRAPHC Services HLA Quick Themes Map Visualisation G-ET G-Tag Paul Konings & Michael Hewett: GRAPHC, APHCRI, ANU

  19. WHO GRAPHC . National Centre for Geographic & Resources Analysis in Primary Health Care Acknowledgement: The research reported in this presentation is a product of the Australian Primary Health Care Research Institute, which is supported by a grant from the Australian Government Department of Health and Ageing under the Primary Health Care Research, Evaluation and Development Strategy. The information and opinions contained in it do not necessarily reflect the views or policies of the Australian Government Department of Health. http://GRAPHC.APHCRI.ANU.EDU.AU Paul Konings National Centre for Geographic & Resource Analysis in Primary Health Care (GRAPHC),Australian Primary Health Care Research Institute (APHCRI), Australian National University (ANU)Credits: Paul Konings, Michael Hewett