public financing of healh in developing countries: a cross-national systematic analysis
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This presentation discusses IHME's research in public financing of health in developing countries, including study design, findings, study limitations, and recommendations for governments and future research.For more information please visit www.healthmetricsandevaluation.orgTRANSCRIPT
UNIVERSITY OF WASHINGTON
Public financing of health in developing countries: a cross-national systematic analysis
Chunling Lu, Matthew Schneider, Paul Gubbins, Katherine Leach-Kemon, Dean Jamison, Christopher Murray
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Outline
Public Financing of Health Matters
Study Design
Findings
Which Part of the Health Sector Do the Funds Come From?
Limitations
Recommendations
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Development assistance for health has increased dramatically.
The vast majority of health expenditure is still financed by developing country governments and households.
Ravishankar et al 2009 The Lancet
Range of macro-economic factors such as GDP, tax base, debt, or debt relief.
Policy choices such as the priority for health relative to other sectors.
Availability of external finance for health.
What Are the Determinants of Public Financing of Health in Developing Countries?
Steadily growing number of individuals who will need ARVs.
New pipeline of technologies for poor countries coming from global health R+D investments.
Healthcare expenditure increases historically at a faster pace than GDP per capita.
Epidemiological transition particularly in urban elites will lead to increased demands for higher cost care.
Demand for Health Services Will Increase
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Outline
Public Financing of Health Matters
Study Design
Findings
Which Part of the Health Sector Do the Funds Come From?
Limitations
Recommendations
Construct complete time series for government health expenditure from own sources for developing countries.
Statistically evaluate the determinants of changes in public health expenditure using time-series cross-sectional methods.
Broad Approach
1) Government Health Expenditure as Agent (GHE-A)
2) Government Health Expenditure as Source (GHE-S)
3) General Government Expenditure (GGE)
4) Gross Domestic Product (GDP)
Some Definitions
1) WHO and IMF request data on GHE-A from countries (Ministries of health and finance respectively).
2) Many countries report budgets and audited financial statements on-line or in national annual publications.
3) Data are very inconsistent – huge variation across countries
4) Many country years are missing – 40% over the last 10 years.
Tracking GHE-A and GHE-S is Not Easy
1) Problem of compositional bias
2) Analyses that do not deal with missing data or use predictions for missing data based on models using other covariates can induce substantial bias. “List-wise deletion is bad”
3) Multiple imputation for time-series cross-sectional data is the standard solution (e.g. Amelia II).
Missing Data in Time-Series Cross-Sectional Datasets
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Statistical Model
We express key quantities of interest as percentage of GDP to avoid exchange rate and GDP deflation issues.
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Outline
Public Financing of Health Matters
Study Design
Findings
Which Part of the Health Sector Do the Funds Come From?
Limitations
Recommendations
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WHO Imputed Datasets Show in Real Dollars GHE-S is Increasing
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IMF Imputed Datasets Show in Real Dollars GHE-S is Increasing
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Decomposing Changes in GHE-S into Changes in GDP, Changes in Size of Government (GGE/GDP) and Changes in Government Commitment to Health (GHE-S/GDP)
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IMF Change in Government Health Expenditure as a share of General Government Expenditure
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WHO Change in Government Health Expenditure as a share of General Government Expenditure
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Development Assistance for Health change in Global Burden ofDisease developing regions in 1999-2002 compared with 2003-2006
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Table 2: Time-series cross-sectional regression results for GHE-S/GDP for countries in GDB developing regions based on the Arellano-Bover/Blundell-Bond model
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Coefficients of Development Assistance for Health to Governments as a proportion of Gross Domestic Product
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Uncorrected Coefficient
Equilibrium Corrected Coefficient
WHO IMFWHO IMFWHO IMF
Coefficients of Development Assistance for Health to Non-Governments as a proportion of Gross Domestic Product
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Uncorrected Coefficient
Equilibrium Corrected Coefficient
Our statistical analysis reports on the average effect of different factors including DAH-G, DAH-N, GGE and GDP on GHE-S in developing, low-income, low-income and lower-middle income and sub-Saharan Africa.
Consideration of maps of trends in GHE-S/GGE indicates within any of these groupings marked heterogeneity across countries.
Some countries receiving large amounts of DAH-G are actually increasing their own health spending even though the average effect is to decrease spending.
Heterogeneous Effects
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Outline
Public Financing of Health Matters
Study Design
Findings
Which Part of the Health Sector Do the Funds Come From?
Limitations
Recommendations
A dollar of DAH leads to a 60 cent decline in MOF funding of government health programs.
Donors monitor carefully that DAH goes to the targeted programs such as HIV, malaria, or tuberculosis.
Decrease in MOF resources must come from other components of the health system.
Is this tertiary care or the district primary health care system? No evidence at present to answer this question.
Impact of sub-additionality may be an important dimension of the positive or negative synergies debate.
Sub-Additionality May Have Magnified Effect on Health Priorities
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Outline
Public Financing of Health Matters
Study Design
Findings
Which Part of the Health Sector Do the Funds Come From?
Limitations
Recommendations
GHE-S is computed in this study by subtracting measured DAH-G from GHE-A.
Systematic errors in the measurement of DAH-G or GHE-A will lead to errors in GHE-S.
We suspect DAH-G is underestimated because some flows to government are not captured in the available project databases leading to an overestimate of GHE-S.
Remaining problems in identifying whether DAH recipient is government or a non-governmental entity. For this reason, included alternative sensitivity analysis in the study.
Data Limitations
We conducted in-country interviews in Malawi and Zambia to validate our findings and explore other factors. More country case assessments were not feasible for this first study.
Our capacity to understand why some countries make policy choices that increase or decrease the additionality coefficient is limited in this cross-national study.
Other Limitations
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Outline
Public Financing of Health Matters
Study Design
Findings
Which Part of the Health Sector Do the Funds Come From?
Limitations
Recommendations
Recommendations
1. Adopt a clear set of reporting standards for government health spending as a source and spending in other health-related sectors.
Debates on public financing of health will continue until the quality of data on how governments spend their own resources on health is dramatically improved.
Improvement will likely require international leadership from organizations such as the IMF, World Bank and WHO and investments in national capacity to report public finance data using common definitions and standards.
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Recommendations
2. Set collaborative targets to maintain or increase GHE-S as a share of GGE.
We believe that a transparent dialogue between the Ministry of Health, Ministry of Finance and donors and the trajectory for development assistance and public financing of health from domestic sources will be beneficial.
Our study is surprising to some because there has not been transparency across development, macro-economic and health actors on what a country can afford to do in the health sector over the medium-term.
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Recommendations
3. Invest in the absorptive capacity of ministries of health.
In settings where DAH-G has increased by percentage points of GDP, the capacity of the MOH to spend more money may be limited.
Helping those Ministries of Health who have limited implementation capacity is a priority.
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Recommendations
4. Careful assessment of the risks and benefits of expanded DAH to non-governmental actors.
The finding that DAH-N is fully additional raises the question of whether this channel should be used more.
Before making such a strong recommendation, we need to study the efficiency of NGOs.
Some argue that NGOs are more expensive and do not reach the rural poor as compared to government while others argue the opposite.
Evidence is very scare on NGO performance; this is an area that requires urgent attention.
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Recommendations
5. The use of global price subsidies or global purchasing of drugs, vaccines, and supplies should be investigated.
Global price subsidies or global purchasing of drugs, vaccines and supplies may not be seen by Ministries of Finance as clearly as direct on-budget support to the MOH.
Our study does not provide direct evidence of this but follow-on studies are warranted.
If this is true, mechanisms like AMfM may be more attractive.
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85% of developing countries are spending more on health from their own sources or DAH-G in the last four years compared to the previous four years.
Coincident with this increase in spending, there are increases in the coverage of some key interventions like bednets and ARVs.
Evidence also accumulating of faster progress on some key health-related MDGs.
A focus on understanding the drivers of public finance for health will be important for sustaining this progress especially in the medium to long-term.
The Big Picture