Access to and use of primary care using administrative data collections

1. Access to and use of primary care using administrative data collections Elizabeth Comino, Mark Harris, Gawaine Powell Davies, and others Acknowledgements: HERON network, NHMRC, SSWAHS Introduction Define administrative data collections Define primary care � includes looking a primary medical care Acknowledge co investigators Acknowledge funding sources Introduction Define administrative data collections Define primary care � includes looking a primary medical care Acknowledge co investigators Acknowledge funding sources

2. This presentation Scope of program: medical care, GP maternal and child health Gudaga cohort study Background to interest in primary care Conceptual framework A case study Emerging opportunities Conclusions

3. Why Primary care using admin. data? Major entry point to health services Fragmented Federal/state funding Private/public practice Different billing/salary structures Range of health care professionals Multiple structures involved Consequently Under-represented in health statistics No comprehensive primary care data collection Poor understanding of primary care Opportunity Interest in better understanding the sector Establishment of the HERON network

4. Sources of primary care data Hospitalisation Ambulatory care sensitive admissions Medicare Australia data Medical and Pharmaceutical data Billing data BEACH data GP activity (ongoing survey) GP report Population health survey data Health status and health service use Include individual characteristics Potential to provide information on primary care not explored Specific data collections General practice: HCN, CARDIAB Maternal and child health: ODP, COMCAS, IBIS

5. Aim of research program To explore use of administrative data collections to inform access to and use of primary care develop a conceptual framework of access to and use of best practice primary health care explore routine data collections to identify potential indicators of access to quality primary health care Demonstrate with case studies on diabetes asthma, immunisation, cancer screening Develop other research opportunities

6. Why diabetes? Major public health problem Suitable for ongoing management in primary care sector Strong supportive research evidence related to management Well accepted management guidelines Supported by policy and funding initiatives Dissemination and education

7. Conceptual framework* Seven domains of care Prevention Early detection Proactive care Monitoring Complications screening Multidisciplinary care Outcomes * Comino et al., Using population health surveys to provide information on access to and use of quality primary health care. Australian Health Review 2006; 30: 485-495 There has been substantial investment in population health surveys by government and stakeholder groups. Most are designed to provide population based benchmarks on health status and use of health and related services. We were interested in what information they could provide on access to and use of primary care. We reviewed available diabetes related management guidelines and policy documents to identify key management domains, nest we identified indicators of these domains and finally we applied these to population health surveys. We identified seven domains of that represent quality care for people with diabetes. There has been substantial investment in population health surveys by government and stakeholder groups. Most are designed to provide population based benchmarks on health status and use of health and related services. We were interested in what information they could provide on access to and use of primary care. We reviewed available diabetes related management guidelines and policy documents to identify key management domains, nest we identified indicators of these domains and finally we applied these to population health surveys. We identified seven domains of that represent quality care for people with diabetes.

8. This slide summarises the This slide summarises the

9. Case study* 2001 National Health Survey (NHS) probability sampling techniques one person 18 years or more in selected households 9,472 aged 45 years or more 572 reported type 2 diabetes Proactive care, complication screening, hospitalisation, and multidisciplinary care Stratifying variables: age, gender, country of birth socio-economic factors behavioural risk factors health related indicators *Comino et al. The National Health Survey 2001: usefulness to inform a discussion on access to and use of quality primary health care using type 2 diabetes mellitus as an example. Aust Health Rev 2006; 30: 496-506

10. Proactive care 50.5% used medication for high blood pressure or lipids Associated with: Male - 0.67 (0.48 - 0.94) O/S birth - 0.58 (0.41 - 0.82) Curr. Smoking - 0.55 (0.32 � 0.94) Age - 1.62 (1.15 - 2.27)), Low income - 2.45 (1.56 � 3.86) Disadvantage - 1.64 (0.92 � 2.91) Co-morbidity - 2.45 (1.66 - 3.62)

11. Hospitalisation 20.6% - hospitalisation during last 12 months Associated with: Age - 1.83 (1.20 - 2.79) Co-morbidity - 2.92 (1.67 - 5.09) Obesity - 1.81 (1.16 � 2.83) Not associated with gender, O/S birth, SES

12. Multidisciplinary care 5.5% - m/d care in last 2 weeks (GP: 45.9%, dietician: 1.2%, podiatrist: 5.4%, nurse: 3.5%) Associated with: Male - 0.22 (0.09 - 0.58) O/S birth - 0.39 (0.16 - 0.98) Hospitalisation - 2.82 (1.30 � 6.13) Not associated with Age, co-morbidity, CVD, SES

13. What does this mean? The conceptual framework underlying this research defines a set of indicators for investigation Interesting patterns of care n.b. hospitalisation determinant of access to M/D care May extend use of health survey data beyond benchmarking of health status And enable examination of questions relating to primary care

14. How has this research progressed? The research has developed into a number of areas: Repetition using other primary care data sources Testing of other disease models: asthma, cancer screening, immunisation Development of linked data models

15. Emerging opportunities 45 and Up cohort study The NSW Centre for Health Record Linkage (CHeReL) NHMRC study: Investigating best practice primary care for older Australians with diabetes using record linkage

16. Conclusion Primary care data collections are fragmented Sources of data on primary care exist in many data collections Population health surveys � could be used to explore access to and use of primary care Data linkage is an exciting development for primary care