Assessing the potential for efficiency gains in the public health sector Christophe André, OECD Economics Department Presentation to the Fagerberg Committee Friday 5 November 2010

Context and approach Economic Policy Committee, Working Party No. 1 on Macroeconomic and Structural Policy Analysis (Joumard et al., OECD Economics Department Working Paper No. 769) Definition of outcomes and inputs Methodology: efficiency frontier (DEA and panel regressions) Information on institutional settings gathered through questionnaires

Efficiency in health care is difficult to measure and analyse No obvious definition of health care outcomes and inputs A large variety of actors (hospitals, outpatient physicians, drug companies, etc.) Cross-country data on health care outcomes are imperfect Mix of public and private spending Data on institutions are largely missing

Choosing the level of analysis System level Disease level Sub-sector level Reference: Häkkinen and Joumard, OECD Economics Department Working Paper No. 554.

Measuring health care outcomes Raw mortality/longevity indicators (life expectancy, premature mortality, infant mortality…) Longevity indicators adjusted for morbidity/disability (HALE, DFLE) Amenable mortality Other health-related indicators (equity, public satisfaction)

Identifying the determinants of health status (“inputs”) Health care resources per capita (spending on health care, number of health practitioners…) Lifestyle factors (diet, tobacco, alcohol…) Socio-economic factors (GDP per capita, education, pollution…)

Deriving efficiency indicators Econometric approach: the unexplained component from panel regressions is assumed to reflect mainly health system efficiency Data Envelopment Analysis (DEA): construction of an efficiency frontier for a given year using a non-parametric optimisation technique

Econometric approach Estimation of a production function; panel data regressions on a panel of 23 OECD countries over the period Reference: Joumard et al. (2008), OECD Economics Department Working Paper No. 627.

Panel regressions: unexplained differences in life expectancy (Health care resources measured in monetary terms) Years

DEA: efficiency frontier and measurement of inefficiency

DEA: output-oriented efficiency scores (spending efficiency)

DEA and panel regression results (spending efficiency)

DEA sensitivity analysis

Characterising health care systems Identify the institutional features which most differentiate OECD countries Assess empirically how the various institutional features are combined across OECD countries (health care systems) Assess whether one health care system provides better value for money

Cluster analysis: identifying country groups

Efficiency across and within groups

Norway: Policy and institutions Group 6: Hungary, Ireland, Italy, New Zealand, Norway, Poland, United Kingdom.

Norway: Efficiency and quality Group 6: Hungary, Ireland, Italy, New Zealand, Norway, Poland, United Kingdom.

Norway: Activity and consumption Group 6: Hungary, Ireland, Italy, New Zealand, Norway, Poland, United Kingdom.

Conclusions Benchmarking OECD countries is possible; single number efficiency estimates are not perfect but reasonably robust Groups of countries sharing broadly similar institutions can be identified No big-bang reform and no one-size-fits-all recommendations Areas for efficiency improvements can be identified

Thank you !