1. Improving the Measurement of Financial Protection in Health Systems Dr Rodrigo Moreno-Serra Centre for Health Policy, Imperial College London r.moreno-serra@imperial.ac.uk PCPH, Imperial College London, 5 th October 2011

2. Background Financial protection (FP): extent to which people are protected from the financial consequences of illness – Key objective of health care (HC) systems, multidimensional – Financial hardship and lack of access to HC due to costs still widespread (WHR 2010) – FP may suffer in a context of economic downturn – Monitoring FP is crucial for sound health policy

3. FP measurement: where are we? Focus on households’ living standards before and after direct payments for health (OOPs) OOPs reported in household surveys Catastrophic spending – OOPs cross set threshold in terms of share of disposable income Impoverishing spending – OOPs push household income below a chosen poverty line

4. FP metrics: criticisms 1.Measurement of capacity to pay, effects of lost income etc... 2.Effect of financial barriers to access: the elephant in the room – Ability to pay may deter access to necessary HC – Linked to equity but indicator of FP extent – Sole focus on incurred spending may provide misleading picture of FP

5. Catastrophic spending incidence and DTP3 immunization coverage among 1 year-olds, 87 countries (various years) Source: Immunization data from WHO. Catastrophic spending incidence data from Xu et al. (2007). Financial catastrophe is defined as OOPs for health reaching at least 40% of a household’s non-subsistence income.

6. Financial barriers to access in high-income countries with low incidence of financial catastrophe Source: IHPS, Commonwealth Fund (Schoen et al. 2010).

7. Financial Protection Measures: Suggested Areas for Development

8. I. Complementing conventional FP indicators Coverage indicators – WHR 2010 – Generally feasible route – But often limited information available – Role of various other determinants of coverage levels Access surveys – E.g., IHPS (Commonwealth Fund), World Health Surveys (WHO), LSMS (World Bank) – Need implementation on routine and comparable basis

9. II. Improving conventional FP indicators ‘Need-adjusted’ FP metrics – Estimate expected utilization and OOPs according to ‘medical need’ characteristics – Adjust catastrophic and impoverishing spending incidence (expected incidence) – May yield very different policy conclusions from conventional analysis (e.g., Pradhan and Prescott 2002) – But methodologically challenging

10. III. An exploratory tool: Data Envelopment Analysis (DEA) Based on economic concept of production frontier Through linear programming, find units that achieve same (or better) outputs at lower use of inputs Efficiency = actual/optimal performance (OQ A /OQ 1 ) Can examine efficiency based on multiple outputs (e.g., FP indicators) and inputs

11. DEA applied to FP assessment Financial protection proxy MeanStd. Dev.Countries Protection against catastrophic spending (%)96.92.758 Median immun. coverage (6 vaccines) (%)84.411.858 Births attended by skilled personnel (%)73.627.458 THE per capita (PPP, constant 2005 US$)253.49244.9358 Question: How do developing countries compare concerning efficiency in ‘producing’ FP given available resources (constraints)? Criteria for efficiency analysis: FP indicators relative to total health spending (THE) per capita (input orientation) Gets at the issue of achievable FP performance

12. DEA applied to FP assessment

14. Concluding remarks Financial barriers: distorting effects on conventional FP assessments Despite recent progress, we need better FP metrics for: – Policy guidance – International performance comparisons Huge potential gains from a health policy perspective