Exploring Health System and Country Performance on

Improving Health Conditions Around the Globe

Dean T. JamisonUniversity of California, Los Angeles

andFogarty International Center

U.S. National Institutes of Health

1

Overview

1. Institutional Performance (brief)

2. Existing Studies at the Country Level “Good Health at Low Cost” China health finance study

3. Example: Country Performance in Reducing IMR

4. Example: Efficiency of Resource Use in the OECD2

Explaining Performance Variation1. Resource Availability

($$, # of providers, education, experience of provider…)

2. Productivity in Use of Health Resources(greater health impact per unit of resource)

3. Contextual Factors(environmental factors, health status of population, SES of population)

***7

Measuring Performance at Different Levels

Institutional PerformanceHealth outcomes controlling for contextual factors

Institutional ProductivityHealth outcome responsiveness to resource availability controlling for contextual factors

Country PerformanceHealth outcomes controlling for contextual factors

‘Health System Productivity’Health outcome responsiveness to resource availability controlling for contextual factors

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REPORT OF THE CALIFORNIA HOSPITALS OUTCOMES PROJECT

Volume One:Study Overview and Results Summary

May 1996

Pete Wilson, GovernorState of California

Sandra R. Smoley, R.N., SecretaryHealth and Welfare Agency

David Werdegar, MD, MPH, DirectorOffice of Statewide Health Planning and

Development

Prof. Hal Luft, Principal Investigator3

Institutional Performance: AMI of California Hospitals

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New York State Bypass Surgeons, 1991-93

SurgeonObserved

Mortality Rate (%)

Risk-adjusted Mortality Rate (%)

Borja, A.Ferraris, V.Statewide averageBennett, E.

3.773.23

2.851.45

4.212.66

2.851.61

Source: Marshall & Spiegelhalter (2001)

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Infant mortality rate related to income

Source: World Health Report 1999 (WHO)

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Infant mortality rate relative to income, China, 1962-1992

Source: World Health Report 1999 (WHO)

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10

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Disease Control Priorities Project

Working Paper No. 14October 22, 2003

Why Has Infant Mortality Decreased at Such Different Rates in Different Countries?Dean T. JamisonUniversity of California, Los AngelesU.S. National Institutes of Health

Martin E. SandbuColumbia University

Jia WangUniversity of California, Los Angeles

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The Simplest ModelsCommon intercept across countries

1. yit = ao + a1xit + a2t + error term

Country-specific intercept (or fixed effect)

2. yit = aoi + a1xit + a2t + error term

Country-specific intercept and slope

3. yit = aoi + a1xit + a2it

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What Happens When You Take First Differences?Equation 1 or 2 gives:

4. yit+1 – yit = a1(xit+1 – xit) + a2[(t + 1) - t)]

The constant term now effects the growth rate in mortality not the level.

Equation 3 gives:

5. yit+1 – yit = a1xi + a2i

The constant term is now a country-specific growth rate.14

Model of Infant Mortality

LIMRit = 0i + 1i TIMEt + 2 LY5it + 3 FEDUCit + 4 LDOCit + it

LIMR = ln(IMR)

LY5 = ln(Per capita income)

FEDUC = Female education level

LDOC = ln(Doctors per 1,000 population)

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Assessing technical progress

0i = 00 + 01 TROPICSi + 02 COASTALi + 0i

1i = 10 + 11 TROPICSi + 12 COASTALi + 1i

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Definition of terms

0i: Country- specific, unobserved effects on level of IMR

1i: Country-specific, unobserved effects on rate of

technical progress in reducing IMR

Total country-specific effect, 1962- 87 ( IMR as % of predicted), for country i:

100 x exp (0i + 25 1i)

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IMR Relative to Predicted, Low- and Middle-Income Countries

0

50

100

150

200

250

Costa

Rica

Sudan, Z

imbab

we

Venez

uela

Sri Lan

ka, M

alay

sia

Bulgar

ia

Kenya

Bolivia

Sierra

Leo

ne

Lesoth

o, Guin

ea B

issa

u

Indones

ia, T

urkey

The Gam

bia

Bangla

desh

Country

% o

f P

red

icte

d IM

R

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IMR Relative to Predicted, High-Income Countries

0

50

100

150

Country

% o

f Pre

dict

ed IM

R

19

20

21

22

23