European Forum for Primary Care Graz, 16 September 2011 Gerrard Abi-Aad

1. QUALITY VARIATIONS: AN EXPLORATIVE STUDY TO ASSESS THE LINK BETWEEN PRIMARY CARE QUALITY AND PRIMARY CARE SYSTEM CHARACTERISTICS European Forum for Primary Care Graz, 16 September 2011 Gerrard Abi-Aad OECD Policy Analyst (Employment, Labour and Social Affairs Division)

2. Agenda • Primary care in health systems and epidemiological transition • Background/justification of the work • Data • Methodology • Preliminary results • Conclusions • Next steps

3. 1.Primary care in health systems and epidemiological transition Strong evidence supporting the important role of primary care in preventing illness and promoting health and, in turn, reducing the need for costly hospital care and potentially the number of premature deaths. However, little attention is paid to the study of the development of primary care systems and in particular to the known attributes through which primary care mediates its benefits.

4. 1.Primary care in health systems and epidemiological transition • In most developed countries, chronic conditions account for both the majority of deaths and the majority (up to 75%) of health care spending. • The increase in chronic disease prevalence is accompanied by a steep increase in the prevalence of multi morbidity • E.g. - a study based on data extracted from general practice registers in the Netherlands (Fortin, 2010) showed that the prevalence of multi-morbidity (patients with two or more co-existing conditions), ranged from around 17% in patients aged 20-39 to 77% patients aged 80 and over

5. 1.Primary care in health systems and epidemiological transition • Chronic conditions cause most deaths and most health spending (up to 75%) • Steep increase in multi morbidity: Patients with 2 or more conditions in the Netherlands • 17% of 20-39 age group • 77% of over 80s. • Good primary care minimises acute exacerbation of chronic disease and reduce the volume of unplanned (expensive) avoidable admissions • Patients often receiving treatment in multiple care settings – strong care coordination is more important than ever before

6. Multi morbidity and its significance Multimorbidity: impact on health systems and their development; Guthrie et al 2011: Commissioned paper by the OECD.

7. 2. Background and justification of the work • The proposal to carry out this work was presented and endorsed at a special meeting of the HCQI Expert Group on 7 October 2010. • We will use this work to catalyse a new focus for the HPPP project including indicator development and utilisation of health system characteristic information. • Finally, we see this work as a first step in our aim to better understand primary care quality variations and how they relate to the way in which primary care services are organised

8. 3. Data • Dependent • Potential years of life loss for conditions amenable to primary care management • Potential years of life loss for cancers amenable to early detection • Potentially preventable admissions • Independent • Health system characteristics (Paris et al., 2010) • PHAMEU Monitor (NIVEL)

9. 4. Methodological approach Indirect measures of primary care quality (PYLL & PPA) to better understand how quality varies from country to country 1 3 2 Explore the link between primary care organization and quality measures using multivariable fractional polynomial regression Use of cluster techniques to assess quality patterns within and across country clusters

10. 5. Preliminary results • High variation of quality of care: • General decrease in potential years of life loss in almost all countries • BUT some significant outliers (amenable mortality)

11. 5. Preliminary results • Cancers amenable to early detection

12. 5. Preliminary results Cluster analysis Level of copayment for primary care services. Density of family physicians per 100 000 population Total national expenditure on health as a proportion of GDP. Extent of GP gate keeping Ability to choose own GP Predominant practice structure (solo, mixed, multi)

13. 5. Preliminary results Cluster analysis Organizational features of primary care are highly variable But it is possible to group countries based on available system characteristic information

14. 5. Preliminary results • Cluster analysis (2) • Ranking of clusters using quality scores may help in identifying quality trends?

15. 5. Preliminary results Regression modelling • We fitted multivariable fractional polynomial (MFP) regression models. This type of model was deemed suitable because of the presence of a combination of continuous and categorical variables. MFP is also flexible in that it provides a range of options for model optimisation. All analyses were carried out using STATA (version 11.1) • None of the fitted models had an adjusted R squared value above 0.5.

16. 5. Preliminary results Regression modelling Density of GPs and total national expenditure on health seem to emerge as important ‘predictive’ variables in the model

17. 6. Conclusions Lots of problems when trying to measure the ‘quality’ or ‘performance’ of a primary care system (missing data etc.). • Modelling real causation (rather than correlation) is a difficult exercise and may not be feasible (or desirable) • Real merit in the collection of system characteristic information (including PC funding and staffing structure) • Making sense of common organizational features and grouping of countries (and in demonstrating the utility of system characteristic information) – may also have spin offs for relative comparative quality assessment (added value component) • Added value in using additional quality of care measures (PYLL cancer and amenable mortality)

18. 7. Next steps • To collect nationally verifiable primary care system characteristic information from all OECD countries.. • To explore more fully the utility of statistical clustering and relative benchmarking in the context of health system comparative quality monitoring by using key primary care system attributes. • To explore the potential for an enhanced suite of primary care quality measures and in particular to focus the development of new measures encompassing; multi morbidity, cost effective prescribing and poly pharmacy, embedding mental health care in the primary care setting, a new suite PYLL indicators for amenable mortality and cancers amenable to early detection in primary care settings.

19. 7. Acknowledgements • Y-Ling Chi • Dione Kringos and Wienke Boerma and the NIVEL Institute • Professor Bruce Guthrie

20. Contact Gerrard.Abi-Aad@oecd.org