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The Equity Gauge: An approach to Monitoring Equity in Health and Health Care in Developing Countries International Meet

The Equity Gauge: An approach to Monitoring Equity in Health and Health Care in Developing Countries International Meeting August 17-20 Tim Evans A world in which any group of individuals defined by age, gender, race-ethnicity, class or residence can achieve its full health potential

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The Equity Gauge: An approach to Monitoring Equity in Health and Health Care in Developing Countries International Meet

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  1. The Equity Gauge: An approach to Monitoring Equity in Health and Health Care in Developing CountriesInternational Meeting August 17-20 Tim Evans

  2. A world in which any group of individuals defined by age, gender, race-ethnicity, class or residence can achieve its full health potential What do we mean by health equity?

  3. ‘health inclusion’: continued improvements in health for all but bringing the bottom up at the same rate or faster than the top ‘tolerable’ vs ‘intolerable’ inequalities: in the context of rapid change What do we mean by health equity?

  4. What are the dimensions of inequity in health? • Equity strata: sex, race, ethnicity, region, education, occupation, place • Dimensions of health status across which inequities exist: risk, disease, death, social consequences of illness • Health care inequities: access, quality & cost of treatment

  5. Health Disparities Between Selected Countries Deaths per 100,00 live births Age

  6. Health Status of Poor Versus Non-poor in Selected Countries (1990)

  7. Gender and Socioeconomic Inequality in CMR, Matlab 1982 Source: Bhuiya et al. 1998

  8. Inverse Care Laws • Rich consume more hospital and public health care than the poor (Hart 1971) • Immunization coverage strongly correlated with socioeconomic status (Gwatkin et al. 1999) • poor with illness don’t access care: 2x more likely to self treat; 10x more likely to do nothing (Uganda, HH Survey, 1994/5). • poor that access health care risk medical impoverishment (Liu and Hsiao, 1997; WB, Voices of the Poor, 2000)

  9. Smoking is more common among the less educated in India(Men, Chennai) Source: Gajalakshmi, CK et al. Patterns of Tobacco Use and Health Consequences, Background Paper for “Curbing the Epidemic: Governments and the Economics of Tobacco Control, World Bank, 1999.

  10. Inverse Care in Public Health

  11. Marginality Very high High Moderate Low Very low Counties by level of marginality, Mexico 1990-96

  12. % 20 100 80 15 60 10 40 5 20 0 0 Very low Low Medium High Very high Distribution of Health Resources, México 1990-96 by level of county marginality Rate per 10,000 population Physicians Beds Hospital deliveries

  13. Benchmarks of Fairness • Evaluating fairness of health systems reform • nine benchmarks covering risks to health such as education, safe water and barriers to access both financial and non-financial etc. • must develop capacity to monitor health status inequities • benchmark encourage “debate” on reform

  14. World Health Report 2000

  15. Equity Gauge: South Africa • Health equity explicit goal of • government policy • Problem: how to monitor progress? • Partnership: parliamentarians, researchers, NGOs • Gauge development - district and province resource allocation, utilisation of health care, health status

  16. What constitutes an equity gauge? 1) Fair distribution: an organizing principle 2) Key health systems stakeholders 3) Community ownership/integration 4) Technical competency: scope/reach, measures - valid, reliable, sustainable 5) Informing decision- making: awareness/demand, accessibility, user-friendliness, timeliness

  17. Central challenges • To identify valid indicators to assess short and longer term change • To integrate policy link from the outset • To ensure that gauges provide voice and visibility to the needs of the vulnerable and marginalized

  18. IMR highest and lowest quintilesRelative inequality/ Absolute InequalityHi:Low Rate Ratio Rate difference Source: DHS data 1992-1997; Pande and Gwatkin 1999

  19. Range of approaches • City or municipality based ‘gauges’ • National systems with broad partnerships • Innovative household-based monitoring mechanisms • Involvement of indigenous groups • Redesign of surveys for equity focus • Resource allocation focus • Broader social determinants focus

  20. What unites these efforts? • the need for greater capacity to monitor and act upon health systems inequities

  21. What led up to this meeting? • Global Health Equity Initiative 1995-2000 (research to reveal inequities within LDCs) • Arlington Health Equity meeting June 1999 (move from research on gaps to monitoring for action) • Puyuhuapi, Chile meeting October 1999 (strengthen country capacity for monitoring) • South Africa- August 2000

  22. Who is here? • Asia: Bangladesh, China, Lao, Philippines, Thailand • Africa: Ethiopia, Kenya, Malawi, Mozambique, South Africa, Uganda, Zambia, Zimbabwe • Latin America: Argentina, Bolivia, Chile, Cuba, Ecuador, Peru

  23. Meeting objectives • Embrace the “common” challenge • Exchange ideas and experiences • Lay foundations for greater competency via three working groups- technical, advocacy and policy; • Identify potential and mechanisms for longer-term collaboration

  24. Vision By the year 2015 every country should have an integrated system for monitoring health system inequities that informs, monitors and evaluates health and other socioeconomic policies --Puyuhuapi Conference position statement

  25. Measurement and Monitoring • Correct the first injustice - making people count - vital registration systems with local ownership. • Regular reporting of inequities - need better measurement tools for policy • Prospective assessment of health system policy -Health equity impact assessments

  26. Reversing the Inverse Care Laws • Equity targets - both outcomes and access, symbolic and practical (Dahlgren and Whitehead, 1997) • Financing reforms - to remove disincentives to access and protect from medical impoverishment • Prevention of health risks that cluster with poverty and are cumulative over time e.g. tobacco • Evidence on what works - both within and beyond the health care sector

  27. Gender shortfall in CMR by SES, Matlab 1982 and 1996

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