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Anna Zawada a.zawada@esa.com.pl Hanover, 09.02.2012

Quantitative Analysis of Health Equity (on the base of course and w orkshop s, Genewa, 8-12.06.2009). Anna Zawada a.zawada@esa.com.pl Hanover, 09.02.2012. Basics.

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Anna Zawada a.zawada@esa.com.pl Hanover, 09.02.2012

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  1. Quantitative Analysis of Health Equity(on the base of course and workshops,Genewa, 8-12.06.2009) Anna Zawada a.zawada@esa.com.pl Hanover, 09.02.2012

  2. Basics • Equality refers to the description of differences in health observed in population and it’s distribution, the cause may be differences in access • Equity focuses attention on the distribution of resources and other processes that drive a systematic inequality in health (or in its social determinants) between more and less advantaged social groups – a health inequality that is unjust or unfair • vanDoorslaer et al. methodology is based on economic methodology of description of the income distribution in groups ordered by growing income – Lorenz curve, Gini index; mathematic/statistic: linear corelation, linear regression; STATA – programming tool used by academics with shared macros

  3. Lorenz curve, Gini index Lorenz curve describes income distribution in the population: OX axis – cummulated % of population ranked by growing income; OY axis – cummulated % of income in the population group; In economy Lorenz curve always lies under the diagonal (line of eqality) GI=A/(A+B)=2A (as A+B=1/2) 0<GI<1 v.Doorslear, O’Donnell, course materials

  4. Concentration curve, concentration index Concentration curve represents the distribution of the financing/utilization of healthcare variable: OX axis – cummulated % of population ranked by growing income; OY axis – cumulated healthcare variable values (eg. specjalist visits utilization); Concentration curve may lay under or over the line of equality or may cross it CI=A/(A+B)=2A (as A+B=1/2) -1<CI<1 CI<0 when variable is higher amongst poor A B

  5. Financing/utilization of healthcare variables • Financial – spending on health care: spending incorporated in taxes, social/private insurance, out-of-pocket spending, catastrophic payments; health subsidies • Utilization – number of GPs visits, number of specjlists visits, number of dental services, hospitalizations • Health outcomes – children: under-five mortality rate, height or weight in relation to the age and sex (as a measure of malnutrition), immunization; adults: self-assessed health (if expressed in ordering scale – should be converted into binary variable by setting a threshold or to health-related utilities)

  6. Concentration curve (2) CC lying above equality line in case of under-five mortality variable, as in this chart, are „pro poor” (higher under-five mortality in poor people than in rich ones – not beneficiary for low-income groups) v.Doorslear, O’Donnell, course materials

  7. Redistributive effect of healthcare payment • Health care spending may be the cause of health inequalitiesif it increase social disadvantages • A proportional health care payments leave income inequality unaffected and has zero redistributive effect. • Progressive health care payments lower post-payment income inequality, and have a positive or pro-poor redistributive effect • Regressive health care payments leave the post-payment income distribution less equal than the pre-payment one, and have a negative or pro-rich redistributive effect • Kakwani index, which is defined as twice thearea between a CC and the Lorenz curve, can be used as a summarymeasure of progressivity; -2<KI<1; KI is negative (positive) if the CC dominates (is dominated by) the Lorenz curve.

  8. Quantitative Analysis of Health Equity • Course & workshops for PhD students, at Univ. of Geneva, provided by • Prof. Eddy vanDoorslaer, Erasmus Univ., Rotterdam, Netherlands • Prof. Owen O’Donnel, Univ. of Macedonia, Thessaloniki,Greece • Methodology has been developped by ECuity Project team http://www2.eur.nl/bmg/ecuity/ on the base of economic studies on inequities in health care systems in OECD countires (ECuity) as well as in the Asia-Pacific region (EQUITAP) • Course handbook, slides and STATA macros on World Bank website www.worldbank.org/analyzinghealthequity

  9. Sources of data Survey data • European Community Household Panel (ECHP) at Eurostat website • EU Survey on Income and Living Conditions (EU-SILC) • Demographic and Health Surveys (DHS) • World Bank’s Living Standards Measurement Study (LSMS) • Multiple Indicator Cluster Surveys (MICS) by UNICEF • National surveys, eg. Social Diagnosis (Diagnoza społeczna) http://www.diagnoza.com/ Administrative Data Census Data

  10. Thank you for your attention Anna Zawada a.zawada@esa.com.pl

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