Economics of Scaling Health Financing

1
Economics of ScalingHealth Financing

• Opportunities and Constraints
• Alexander S. Preker
• Lead Economist
• World Bank
• Accra
• 2008

2
Methodology

• Cross Sectional
• Longitudinal
• Scenarios
• Best Case
• Projection of Current Trends
• Other Intermediate Cases
• Worst Case

3
Assumptions forHealth Expenditure

• GDP Growth (5 to -5 percent annual growth)
• Abuja Target (15 percent increase in public
  spending to 5 percent
• Insurance Effect (25 percent to zero)
• Relative Size of Wage Bill (constant)

4
Estimating Resource EnvelopeMain Data Variables

• Overall level of GDP
• Share of GDP channeled through the public sector
• Share of public sector resources allocated to
  health care
• Share of health expenditure in public sector used
  to pay for health workers
• Share of GDP channeled directly through
  households
• Household spending of health care
• Share of private expenditure on health care
  devoted to health workers

5
Health Expenditure Scenarios

• Worse Case
• Gov. HE Gov. Exp ? -5 between 2005-2015
• Eco. Growth ? -5/year
• Insurance ? 0 of oops
• Status Quo
• Gov. HE Gov. Exp ? ?0
• Eco. Growth ? ?0
• Insurance ? 0 of oops
• Intermediate 1
• Gov. HE Gov. Exp ? 15 in 2015
• Eco. Growth ? -5/year
• Insurance ? 0 of oops

• Intermediate 2
• Gov. HE Gov. Exp ? -5 between 2005-2015
• Eco. Growth ? 5/year
• Insurance ? 30 of oops
• Best Case
• Gov. HE Gov. Exp ? 15 in 2015
• Eco. Growth ? 5/ year
• Insurance ? 60 of oops
• Projection of current trends
• Gov. HE Gov. Exp ? Same trend as between
  1996-2005
• Eco. Growth ? Same trend as between
  1996-2005
• Insurance ? 0 of oops

6
Projected staffing levels in 2015 using different
scenarios
7
Projected staffing levels in 2015 using different
scenarios (millions)
8
TOTAL ECONOMICALLY SUSTAINABLE STAFFING LEVEL
(per 1000 population)
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Training Recurrent and Capital Costs
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Assumptions forTraining Costs

• Training Costs Fall on Education Sector
• Drop out Rate 30 Percent
• Brain Drain
• 30 percent MDs
• 10 percent Nurses

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Cost of Training per Categories of Health Workers
and Total Expenditures on Tertiary Education in
the Projection of Past Trends Scenario (2006 USD
millions)
12
Cost of Training per Categories of Health Workers
and Total Expenditures on Tertiary Education in
the Projection of Past Trends Scenario (2006 USD
millions)
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GDP Growth
1.Zimbabwe 2.Seychelles 3.Cote dIvoire 4.Burundi
5.Lesotho 6.Swaziland 7.CAR 8.Gabon 9.Malawi 10.Ca
meroon 11.Kenya 12.Togo 13.Comoros 14.Guinea 15.Sa
o Tome Pr. 16.Guinea Bissau 17.Namibia 18.Botswa
na 19.Benin 20.Niger 21.Mauritius 22.Madagascar 23
.Burkina-Faso
24.Eritrea 25.South Africa 26.Gambia 27.Rwanda 28.
Zambia 29.Liberia 30.Mauritania 31.Mali 32.Cape
Verde 33.Uganda 34.Chad 35.Ghana 36.Senegal 37.CDR
38.Nigeria 39.Tanzania 40.Sierra
Leone 41.Mozambique 42.Sudan 43.Ethiopia 44.Congo
45.Angola
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Changes in GDP Growth
1.Liberia 2.Seychelles 3.Guinea-Bissau 4.Botswana
5.Benin 6.Cameroon 7.Mauritania 8.Cape
Verde 9.Rwanda 10.Gambia 11.Swaziland 12.Madagasca
r 13.Lesotho 14.CAR 15.Uganda 16.Sao Tome
Pr. 17.Namibia 18.Gabon 19.Mauritius 20.South
Africa 21.Zimbabwe 22.Comoros 23.Malawi

• 24.Congo
• 25.Guinea
• 26.Sudan
• 27.Zambia
• 28.Burundi
• 29.Tanzania
• 30.Ghana
• 31.Mali
• 32.Kenya
• 33.Nigeria
• 34.Cote dIvoire
• 35.Burkina-Faso
• 36.Senegal
• 37.Ethiopia
• 38.Togo
• 39.Sierra Leone
• 40.Mozambique
• 41.Niger
• 42.Chad

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Share of Government Spendingon Health Care
1.Burundi 2.Nigeria 3.Guinea 4.Eritrea 5.Congo 6.G
hana 7.Cote dIvoire 8.Angola 9.Mauritania 10.Gamb
ia 11.Guinea-Bissau 12.Togo 13.Equatorial
Guinea 14.Sudan 15.CDR 16.Niger 17.Senegal 18.Ken
ya 19.Comoros 20.Sierra Leone 21.Mozambique 22.Mau
ritius
23.Ethiopia 24.Tanzania 25.Chad 26.Madagascar 27.C
ape Verde 28.Uganda 29.Seychelles 30.Benin 31.CAR
32.South Africa 33.Swaziland 34.Zambia 35.Cameroon
36.Sao Tome Pr. 37.Mali 38.Lesotho 39.Botswana
40.Namibia 41.Gabon 42.Burkina-Faso 43.Rwanda 44.
Liberia 45.Malawi
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There are Problems with Donor Funding
Predictability and Longevity of ODA Must Be
Improved

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ConclusionsFinancial Implication of Scaling Up

• Cost of Hiring Additional Staff
• Cost of Educating of Health Workers
• Cost of Expanding Training Capacity