www.worldbank.org/analyzinghealthequity

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www.worldbank.org/analyzinghealthequity
Book published by the World Bank in
2008. Presentations accompany the book and are
designed as a course on health equity
analysis. The book contents can be downloaded
from the website above.
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Analyzing Health Equity Using Household Survey
Data

• Lecture 1
• Introduction

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Huge rich-poor inequalities in health outcomes
and health care in Bolivia
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And Bolivia is not an isolated example in Latin
America and the Caribbean.
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Health inequality and inequity

• Rich-poor inequalities in health largely, if not
  entirely, derive from differences in constraints
  (e.g. incomes, time costs, health insurance,
  environment) rather than in preferences.
• Hence they are often considered to represent
  inequities.
• But in high-income countries the poor often use
  more health care and this may not be represent
  inequity.
• Drawing conclusions about health equity involves
  consideration of the causes of health
  inequalities.

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Equity of what?

• Health outcomes, e.g. infant mortality, child
  growth, disability, incidence of illness, general
  health, life expectancy.
• Health care utilisation, e.g. doctor visits,
  inpatient stays, vaccinations, maternity care.
• Subsidies received through use of public health
  care.
• Payments for health care (both direct and
  indirect).

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Equity in relation to what?

• Equity in health, health care and health payments
  could be examined in relation to gender,
  ethnicity, geographic location, education,
  income.
• This course focuses on equity by socioeconomic
  status, usually measured by income, wealth or
  consumption.
• Many of the techniques are applicable to equity
  in relation to other characteristics but they
  often require that individuals can be ranked by
  that characteristic.

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Course objectives

• To provide a step-by-step practical guide to the
  measurement of various aspects of health equity.
• To introduce the relevant theory and literature.
• To provide hands-on experience of computing
  health equity measures using Stata.
• To illustrate the interpretation of results
  through worked examples.
• To stimulate analysis that will facilitate more
  comprehensive monitoring of health equity,
  especially in developing countries.

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Questions addressed by health equity analyses

• Snapshots. Does inequality in child survival
  between the poor and better-off exist? How large
  is it?
• Movies. Is inequality in child survival smaller
  now than in the 1990s?
• Cross-country comparisons. Is inequality in child
  survival larger in Brazil than in Cuba?
• Decompositions. To what extent is inequality in
  child survival explained by inequalities in
  education, health insurance cover, access to
  maternal and child health care, etc?
• Cross-country detective exercises. To what extent
  is greater inequality in child survival in Brazil
  than Cuba explained by greater income inequality,
  given differences in health systems?
• Program impact evaluations. To what extent is
  inequality in child survival reduced by an
  intervention such as a vaccination program,
  expanded health insurance cover or improved water
  supply?

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Ingredients of health equity analysis

• Data usually from a household survey.
• Measurement of the key variables - health/health
  care/health payments and of socioeconomic status.
• Quantitative measures of inequality or inequity.
• Multivariate methods to explain inequality,
  identify its causes and the impact on it of
  interventions

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Course content

• The course is structured around these four
  ingredients, plus applications.
• Part I Data
• data requirements and sources (lecture 2)
• measurement of the key variables child
  survival, anthropometrics, adult health living
  standards (3-6).
• Part II Tools
• measures of socioeconomic inequality in health
  variables (7-9)
• multivariate analysis (10-11)
• decomposition methods (12-13).
• Part III Applications
• to health care utilisation (14-15)
• to health payments (16-19).

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Concentration curves (lecture 7) are central to
the assessment of socioeconomic inequality in
health
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Concentration index (lecture 8) is a tie-breaker,
but rests on certain value judgments
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Multivariate methods

• Estimation and inference with complex survey data
  (lecture 10)
• Nonlinear models for health and medical
  expenditure data (11)
• Explaining differences between groups Oaxaca
  decomposition (12)
• Explaining socioeconomic-related health
  inequality Decomposition of the concentration
  index (13)

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Lecture 14 Who (really) benefits from health
care subsidies? Often the better off!
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Lecture 16 Who (really) pays for health care?
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Lecture 18 Incidence of catastrophic
out-of-pocket payments varies across countries
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Lecture 19 Health care payments and poverty
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Acknowledgements

• Participants in the ECuity and Equitap projects
• The European Commission INCO-DEV programme
  (ICA4-CT-2001-10015) that funded the Equitap
  project.
• The Dutch government for financial support for
  the production and printing of the book and these
  slides through Reaching the Poor II
• Davidson Gwatkin and Abdo Yazbeck for
  encouragement and support during the production
  and market-testing of the technical notes, and
  the production of the volume
• John Didier, Tanya Ringland, Chialing Yang and
  others at the World Bank Institute for managing
  the production and dissemination of the book