Www.worldbank.org/analyzinghealthequity Book published by the World Bank in 2008. Presentations...

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 thewebsite above.

http://www.worldbank.org/analyzinghealthequity

“Analyzing Health Equity Using Household Survey Data” Owen O’Donnell, Eddy van Doorslaer, Adam Wagstaff and Magnus Lindelow, The World Bank, Washington DC, 2008, www.worldbank.org/analyzinghealthequity

Analyzing Health Equity Using Household Survey Data

Lecture 1

Introduction


Huge rich-poor inequalities in health outcomes and health care in Bolivia

0

20

40

60

80

100

120

poorest20%

2ndpoorest

20%

middle20%

secondrichest20%

richest20%

risk

of

new

born

dyin

g b

efo

re

5th

bir

thday (

per

10

00

)

0

10

20

30

40

50

60

70

80

90

100

poorest20%

2ndpoorest

20%

middle20%

secondrichest20%

richest20%

% b

abie

s deliv

ere

d

by a

medic

ally

tra

ined p

ers

on


And Bolivia is not an isolated example in Latin America and the

Caribbean….

0

20

40

60

80

100

120

140

160

180

1 2 3 4 5

Wealth quintile (poorest to richest)

Under

-five

mort

alit

y ra

te

Haiti 1994/95Haiti 2000Guatemala 1998/99Guatemala 1995Nicaragua 1997/98Colombia 1995Paraguay 1990Bolivia 2003Colombia 2000Colombia 2005Dominican Republic 2002Nicaragua 2001Dominican Republic 1996Bolivia 1998Peru 1996Peru 2000Brazil 1996


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.


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).


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.


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.


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?


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


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).


Concentration curves (lecture 7) are central to the assessment of

socioeconomic inequality in health

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

0% 20% 40% 60% 80% 100%

cumul. % pop. (poorest first)

cum

ul. %

under-

five d

eath

s

equality

Haiti 1994/95

Guatemala 1995

Bolivia 2003

Bolivia 1998

Brazil 1996


Concentration index (lecture 8) is a tie-breaker, but rests on certain value

judgments

-0.30 -0.25 -0.20 -0.15 -0.10 -0.05 0.00

Haiti 1994/95Haiti 2000Guatemala 1998/99Guatemala 1995Nicaragua 1997/98Colombia 1995Paraguay 1990Bolivia 2003Colombia 2000Colombia 2005Dominican Republic 2002Nicaragua 2001Dominican Republic 1996Bolivia 1998Peru 1996Peru 2000Brazil 1996

concentration index


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)


Lecture 14: Who (really) benefits from health care subsidies? Often the better off!

0 5 10 15 20 25 30 35 40 45

Nepal

Gansu, China

Heilongjiang, China

India

Indonesia

Vietnam

Bangladesh

Thailand

Sri Lanka

Malaysia

Hong Kong SAR

share of govt. health subsidies accruing to poorest 20%


Lecture 16: Who (really) pays for health care?

-0.1 -0.05 0 0.05 0.1 0.15 0.2 0.25

J apan

Taiwan

Korea Rep.

Kyrgyz Rep.

China

Punjab , India

Nepal

Sri Lanka

Philippines

Hong Kong

Indonesia

Thailand

Bangladesh

Kakwani index of progressivity(+=progressive; -=regressive)


Lecture 18: Incidence of catastrophic out-of-pocket payments varies across

countries

0% 5% 10% 15% 20% 25% 30% 35%

MALAYSIA

TAIWAN

THAILAND

HONG KONG SAR

PHILIPPINES

INDONESIA

SRI LANKA

KOREA REP.

NEPAL

KYRGYZ REP.

INDIA

CHINA

BANGLADESH

VIETNAM

% pop. with out-of-pocket payments exceeding 15% non-food consumption


Lecture 19: Health care payments and poverty

Pre-payment and post-payment consumption, Bangladesh 2000

0

2

4

6

8

10

12

14

16

0 500 1000 1500 2000 2500 3000 3500 4000 4500 5000 5500 6000 6500 7000

HHs ranked by total consumption

HH

con

s as

mul

tiple

of p

ov li

ne P

L

Poverty line Post payment consumption Pre payment consumption


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

Www.worldbank.org/analyzinghealthequity Book published by the World Bank in 2008. Presentations...

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