“Analyzing Health Equity Using Household Survey Data” Owen O’Donnell, Eddy van Doorslaer, Adam Wagstaff and Magnus Lindelow, The World Bank, Washington.

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Analyzing Health Equity Using Household Survey Data
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Presentation transcript:

“Analyzing Health Equity Using Household Survey Data” Owen O’Donnell, Eddy van Doorslaer, Adam Wagstaff and Magnus Lindelow, The World Bank, Washington DC, 2008, Analyzing Health Equity Using Household Survey Data Lecture 16 Who Pays for Health Care? Progressivity of Health Finance

“Analyzing Health Equity Using Household Survey Data” Owen O’Donnell, Eddy van Doorslaer, Adam Wagstaff and Magnus Lindelow, The World Bank, Washington DC, 2008, What is progressivity? A vertical equity concept – extent to which those with unequal ability to pay do pay differentially for health care The extent to which payments for health care are proportional to ability to pay Progressive - payments are an increasing proportion of ability to pay. Regressive – payments are a decreasing proportion of ability to pay. Proportional – payments remain a constant proportion of ability to pay.

“Analyzing Health Equity Using Household Survey Data” Owen O’Donnell, Eddy van Doorslaer, Adam Wagstaff and Magnus Lindelow, The World Bank, Washington DC, 2008, Measuring progressivity Two distinct stages: 1.Measure progressivity of each source of health finance 2.Weight each source to establish progressivity of health financing system in total Stage 1 requires survey data on health payments, tax/social insurance contributions, health insurance premiums, etc Stage 2 requires macro (National Health Accounts) data on the health financing mix

“Analyzing Health Equity Using Household Survey Data” Owen O’Donnell, Eddy van Doorslaer, Adam Wagstaff and Magnus Lindelow, The World Bank, Washington DC, 2008, Definitions & measurement of key variables Ability to pay –proxied by income/expenditure/consumption (lecture 6) –should indicate welfare before payments for health care –Adjust for hhold size and structure through equivalence scale Health care payments: –Out of pocket (OOP) payments –Private insurance –Social insurance –Taxation (direct and indirect, earmarked and non-earmarked) Non specific sources of finance allocated pro-rata to share of total health sector finance.

Incidence Nominal payer not always the real payer. But difficult to establish real incidence Common incidence assumptions:  income and property taxes- legal taxpayer  corporate taxes - shareholder (or labor) sales and excise taxes- consumer  employer and employee SI/PI- employee Sales tax – apply relevant rate to each item of exp. Allocate taxes for which distribution cannot be estimated as taxes to which are most similar Concentrate on allocating the main sources

“Analyzing Health Equity Using Household Survey Data” Owen O’Donnell, Eddy van Doorslaer, Adam Wagstaff and Magnus Lindelow, The World Bank, Washington DC, 2008, Assessing progressivity – a first pass In Egypt, the share of OOP payments in total expenditure is larger for the top quintiles. This indicates progressivity

“Analyzing Health Equity Using Household Survey Data” Owen O’Donnell, Eddy van Doorslaer, Adam Wagstaff and Magnus Lindelow, The World Bank, Washington DC, 2008, Assessing progressivity across the full distribution Health payments concentration curve (L H (p)) plots the cumulative % of health payments against the cumulative % of the population ranked by ATP Assess progressivity by comparing L H (p) with the Lorenz curve of ATP (L(p)) L H (p) everywhere on top of L(p)  proportionality L H (p) everywhere below L(p)  progressivity L H (p) everywhere above (dominates) L(p)  regressivity

“Analyzing Health Equity Using Household Survey Data” Owen O’Donnell, Eddy van Doorslaer, Adam Wagstaff and Magnus Lindelow, The World Bank, Washington DC, 2008, Incidence of direct, indirect and cigarette taxes in Egypt, 1997 Lorenz curve appears to dominate conc. curves for direct & indirect taxes  Progressivity Conc. curve for cig. tax intersects Lorenz  no conclusion

“Analyzing Health Equity Using Household Survey Data” Owen O’Donnell, Eddy van Doorslaer, Adam Wagstaff and Magnus Lindelow, The World Bank, Washington DC, 2008, Incidence of social & private insurance, and OOP payments in Egypt, 1997 Lorenz appears to dominate OOP conc. curve  progressivity Lorenz appears dominated by SI conc. curve  regressivity Lorenz and PI conc. curve intersect  no conclusion

“Analyzing Health Equity Using Household Survey Data” Owen O’Donnell, Eddy van Doorslaer, Adam Wagstaff and Magnus Lindelow, The World Bank, Washington DC, 2008, Distributional Incidence of Health Finance in Egypt, 1997 – Quintile shares and dominance tests

“Analyzing Health Equity Using Household Survey Data” Owen O’Donnell, Eddy van Doorslaer, Adam Wagstaff and Magnus Lindelow, The World Bank, Washington DC, 2008, Measuring Progressivity Summary indices of progressivity useful for making comparisons. Kakwani index = 2* area between Conc. curve and Lorenz curve = Concentration Index – Gini. –Min = -2, Max = 1 –Kakwani > 0  progressive –Kakwani = 0  proportional (but can also arise with intersecting curves) –Kakwani < 0  regressive C and Gini can calculated by

“Analyzing Health Equity Using Household Survey Data” Owen O’Donnell, Eddy van Doorslaer, Adam Wagstaff and Magnus Lindelow, The World Bank, Washington DC, 2008, Measures of progressivity of health finance in Egypt, 1997

“Analyzing Health Equity Using Household Survey Data” Owen O’Donnell, Eddy van Doorslaer, Adam Wagstaff and Magnus Lindelow, The World Bank, Washington DC, 2008, Relative progressivity of different source of finance in Egypt, 1997 Tests of Dominance between Concentration Curves for Different Sources of Health Finance

“Analyzing Health Equity Using Household Survey Data” Owen O’Donnell, Eddy van Doorslaer, Adam Wagstaff and Magnus Lindelow, The World Bank, Washington DC, 2008, Measuring progressivity of overall health finance Kakwani index is additively separable So, Kakwani for total health finance can be computed as weighted average of those for each source That is, where s j is the share of total health finance contributed by source j Ideally finance shares calculated from NHA Shares of sources can be inflated to represent those for which the distribution cannot be estimated but is assumed to be distributed similarly Sensitivity analysis should be conducted with respect to the weights

Progressivity of health finance by source and in total in Egypt, 1997

“Analyzing Health Equity Using Household Survey Data” Owen O’Donnell, Eddy van Doorslaer, Adam Wagstaff and Magnus Lindelow, The World Bank, Washington DC, 2008, Health care financing triangle – OECD countries

“Analyzing Health Equity Using Household Survey Data” Owen O’Donnell, Eddy van Doorslaer, Adam Wagstaff and Magnus Lindelow, The World Bank, Washington DC, 2008, Progressivity by source — OECD countries, early 90s

“Analyzing Health Equity Using Household Survey Data” Owen O’Donnell, Eddy van Doorslaer, Adam Wagstaff and Magnus Lindelow, The World Bank, Washington DC, 2008, Overall progressivity — OECD countries, latest year

“Analyzing Health Equity Using Household Survey Data” Owen O’Donnell, Eddy van Doorslaer, Adam Wagstaff and Magnus Lindelow, The World Bank, Washington DC, 2008, Health care financing triangle – Asia

“Analyzing Health Equity Using Household Survey Data” Owen O’Donnell, Eddy van Doorslaer, Adam Wagstaff and Magnus Lindelow, The World Bank, Washington DC, 2008, Inequality and progressivity – total health care payments, Asia