How does health insurance mechanisms and HIV interact: Overview of country experience

Erik Lamontagne, Ole Doetinchem, Robert GreenerSystems Integration, UNAIDS

Geneva

Bridging the Divide: Interdisciplinary Partnerships for HIV and Health SystemsVienna, Austria, 16-17 July 2010

From universal access to universal coverage

Coverage of AIDS services

Different types of mechanisms

private health insurance social health insurance public tax-funded provision

The review of country experiences

•Questionnaire on country situation: how is the overall health insurance and how HIV is eventually integrated •Excellent response rate (65/71) countries•Country analysed in terms of their vulnerability•Vulnerability level: incorporates proxy measures of

– Poverty rate– Extend of the informal economy(see World Social Security Report 2010)

Country characteristics

Classification using vulnerability index is coherent with usual characteristics

No clear trend of HIV prevalence Among vulnerability groups of countries

Government health expenditure

Health insurance coverage

Blue: % country including health insuranceGreen: proportion of providing ART coverageOrange: proportion of SHI providing PMTCT

The case of Ghana

The case of South Africa

Lessons to draw (1)

• Introducing health insurance is not an automatic recipe for increasing revenue collection for health or HIV

• Integrating HIV services in SHI: more challenging for low income countries ( f(prevalence) )

• Not a fatality: Ghana, South Africa and Rwanda

• Countries that choose to include HIV services in SHI are mainly those already having a functioning health insurance system in place.

Lessons to draw (2)

• The review shows that including HIV = essentially a political decision

• Possibility to progressively increase coverage (pop, cost, services)

• External aid, incl. HIV financing can support (and subsidise) progressive integration of HIV in SHI

Thank you

contact: Erik Lamontagne: lamontagnee@unaids.orgGeneva, UNAIDS

AnnexeEconomic share of government

Angola

Comoros

Botswana

South Africa

Mauritius

Namibia

Tanzania

Swaziland

MalawiKenya

Mozambique

Lesotho

Zimbabwe

Zambia

UgandaRwanda

DR CongoEthiopia

DjiboutiGambia

Gabon

Nigeria

Niger

Senegal

Mali

Congo

Côte d'Ivoire

Burkina Faso

Ghana

Madagascar

TogoCameroon

Central African Republic

Sierra LeoneGuinea-Bissau

Chad

Guinea

Burundi BeninMauritania

R2 = 0.1757

0%

10%

20%

30%

40%

50%

$100 $1,000 $10,000GNI per capita $US

Gov

ernm

ent r

even

ue a

s %

of G

NI

Health expenditures and GDP

1

2

3

4

5

6

7

8

9

4 5 6 7 8 9 10 11 12

Log GDP/capita

Log

Hea

lth E

xpen

ditu

res/

capi

ta

(most of ) Sub Saharan Africa

Van der Gaag et al, Economics Reference Group, Dec 2009

Projection of health funding

•GDP per capita is an almost perfect predictor of health expenditure per capita•The estimated income elasticity is higher than zero and close to or even higher than one.•This implies that health is regarded more as a “luxury good” than as a necessity (by the aggregate populations of most countries)

•Based on projections of health funding to 2030, Van der Gaag et al (2009) concludes that:

– over time (relatively fast growing) middle income countries may have sufficient funding…

– …but (relatively slow growing) low income countries will need significant financial support for years to come.