OCTOBER 4 T H , 2012

LAURENCE LANNES LSE, AFRICAN DEVELOPMENT BANK

PBF & EQUITY WORKING GROUP OF THE COMMUNITY OF PRACTICE ON PBF IN

AFRICA

Benefit Incidence Analysis: a powerful tool to assess the efficiency

of public spending on health

Outline of the presentation

1. Why conducting a BIA?2. Methodology3. Case study on Rwanda4. What does BIA tell us for policy reform?5. BIA and PBF?

1. Why conducting a BIA?

Characteristics of health financing analysis

In general, the analysis of health financing in developing countries focuses on: Absolute resources spent in the health system Relative contributions from the different stakeholders

A country is considered to perform better than another if: It has higher per capita spending on health in absolute terms The share of private out-of-pocket expenditures in total health expenditure is lower

more equitable

Limitation of such analysis: Aggregates do not provide information on what is actually done with these extra $ per

capita. Some questions remain unanswered such as:

do the poor benefit from public health resources? Do government’s subsidies primarily flow to facilities that the poor use the most?

A tool is needed to capture the equity impact of health spending

Equity in health care spending

Available tools don’t look at equity in health care spending National Health Accounts, Public Expenditure Review

No information on ultimate beneficiaries from public resources No information on priority areas

Benefit incidence analysis Uses existing tools (NHA, PER, households surveys) to see who actually benefits

from resources spent in the health system Assesses the efficiency of public health spending Compares public health spending with the needs of the most vulnerable

Powerful policy and advocacy tool Highlights weaknesses in the allocation of public resources Reports progress achieved in terms of equity Can demonstrate country’s efforts to reach the poor

BIA will show whose welfare is affected by the government’s subsidization of health care

Evidence from the developing world

Asia and Pacific: EQUITAP project (O’Donnell et al., 2007). Pro-rich distribution of health care resources in most of the countries

under study. Pro-poor distribution is easier to reach in richer countries (O’Donnell

et al., 2007).

Large study on 56 developing countries worldwide (Davoodi, Tiongson, & Asawanuchi, 2003). Health spending is generally pro-rich, particularly in sub-Saharan

Africa. The poor benefit more from spending on primary health care than on

hospitals. Even at the first level of care, public spending is not pro-poor.

Limited evidence, BIAs are not systematically conducted

2. Methodology

What is a benefit incidence analysis?

BIA describes distribution of public spending on health care across population ordered by: Living standards

With ordinal measure (wealth index): determine whether distribution is pro-poor or pro-rich

With a cardinal measure (income): establish extent to which public spending is pro-poor

Other socioeconomic characteristics Geographic characteristics

BIA determines who receives how much of public spending

Three steps of BIA (O’Donnell et al., 2008).

1. Estimate distribution of utilisation of public health services by socio-economic groups

2. Weight each individual use of service by the unit cost of the public subsidy for a given service

3. Assess the distribution of subsidies against a target distribution

Data requirements

Financial data from PER and/or NHA

Household level data from health or socioeconomic survey

Health care utilization and socio-economic status for the same observations

Focus on: Public care only Subsidies from the state-controlled budget only

Disaggregation by (at least) Hospital inpatient care Hospital outpatient care Non-hospital care (visits to doctor, health centre, polyclinic, antenatal)

NB: USING 2005 DATA (PRIOR TO THE INTRODUCTION OF PBF)

3. Case study on Rwanda

Background

57% of the population lives below the poverty line 92% of the poor live in rural areas 73% of the capital city’s (Kigali) population belongs to the richest quintile

Rwanda is halfway in its decade of health financing reforms National policy for community-based health insurance launched in 2005 (44% of the

population covered). Performance-Based Financing (PBF) still at the pilot phase in three areas of the

country. The national-scale up of PBF started in 2006.

Three levels of health care delivery in Rwanda Health center: basic primary health care such as curative, preventive, promotional,

and rehabilitation services. They also provide inpatient care for medical observation. District hospital: are in charge of patients referred by health centers. They provide

curative and rehabilitative care as well as support to preventive and promotional activities.

National referral hospitals including two national referral facilities, one private not-for-profit hospital and one neuro-psychiatric hospital

Data

Public Expenditure Review (2005) Financial data on the public subsidy Count data on the number of visits at health facilities

by levels of care.

Second household living conditions survey (Enquête Intégrale sur les Conditions de vie des Ménages or EICV2) Data on services’ utilization by wealth quintiles

Utilization of health care services

Poorest use less public health care services than the richest, both for inpatient and outpatient care at health center and district hospital levels.

The poor primarily seek care at the health center level which may be both related to their needs and their poor access to referral facilities.

Richest are more likely to seek care at the hospital level, despite the higher cost of services

0%10%20%30%40%50%60%70%80%90%

100%

outpatient care inpatient care outpatient care inpatient care

Health Center District HospitalDis

trib

utio

n of

pub

lic h

ealth

car

e ut

iliza

tion

Poorest quintile Quintile 2 Quintile 3 Quintile 4 Richest quintile Source: EICV2

Revenues of health facilities

Public subsidies encompass government’s and donors’ subsidies.

79% of the total public subsidies flow to national referral hospitals; the remainder is equally distributed between district hospitals (10%) and health centers (11%).

 In US$ Health Center

District Hospital

National referral Hospital

Delivery of Health services

2,669,219 875,894 4,563,678

Drugs 2,568,085 594,163 Financial operations

610,417 462,328

Government Subsidies

93,910 198,656 5,930,795

NGO and donors subsidies

1,123,311 895,760 2,638,518

Total 7,064,943 3,026,801 13,132,991       Of which public subsidies

1,217,222 1,094,416 8,569,313

Public subsidy (US$ per capita) 0.14 0.12 0.97

Source: PER

Estimate public subsidy unit cost

Public subsidy’s unit cost = public subsidy/ # of outpatient and inpatient visits at each level.  Health center District Hospital Referral Hospital

  Outpatient visits

Inpatient visits

Outpatient visits

Inpatient visits

Outpatient visits

Inpatient visits

Public subsidies (US$)

1,016,380 200,842 454,183 640,233 2,228,021 6,341,292

Total utilization

4,871,668 348,343 479,002 152,510 189,726 25,317

Unit cost (US$)

0.21 0.58 0.95 4.20 11.74 250.48

Concentration curve (1)

1. Plot concentration curves for the cumulative proportion of the public subsidy at different levels of care against the cumulative proportion of the population.

Graphical representation of the concentration of the public subsidy Identify and compare inequalities.

2. Compare curves to the 45-degree line of equality and to the Lorenz curve.

If the concentration curve is above the 45-degree line, the distribution is concentrated among the poor. If the concentration curve is above the Lorenz curve, it is inequality reducing.

3. Dominance tests complement this analysis by testing whether the concentration curves are statistically different from the 45-degree line of equality or the Lorenz curve

See: O’Donnell, van Doorslaer, Wagstaff, & Lindelow, 2008.

Concentration curve (2)

Interpretation of the curves

All concentration curves lie below the 45-degree line of equality Public subsidy favors the rich Differences related to the levels of care:

the concentration curve for outpatient care at health center is the closest to the line of equality

The public subsidy for outpatient care at health center is less unequal than that of the higher levels.

The concentration curves are above the Lorenz curve The poor receive more than their income share. The final income (after receiving the subsidy) is more evenly

distributed than pre-subsidy income.

Concentration Indexes

1. Compute concentration indexes Twice the area between the concentration curve and the line of

equality. Summary measure of the absolute progressivity of the subsidy.

0 = absence of consumption-related inequality, Negative = the public subsidy is pro-poor Positive = the public subsidy is pro-rich.  

2. Compute Kakwani indexes Similar to concentration indexes but for income-related data. Twice the area between the public subsidy concentration curve and

the Lorenz curve. Negative = the subsidy is inequality reducing

See: O’Donnell, van Doorslaer, Wagstaff, & Lindelow, 2008

  Health center District hospital

National referral hospital

 Cumulative shares Outpatient Inpatient Outpatient Inpatient Outpatient Inpatient

- Test of dominance against 45o line

- - - - - -

- Test of dominance against Lorenz curve

+ + + + + +

Concentration Index 0.0795 0.253 0.4185 0.253 0.4185 0.253

Kakwani Index -0.434 -0.26 -0.095 -0.26 -0.095 -0.26

Interpretation of indexes

Dominance tests confirm comments on the concentration curves The 45-degree line dominates the concentration curves (negative sign). The health subsidy in Rwanda is therefore pro-rich The poorest quintile does not benefit from its population share of the

public subsidy contrary to the richest quintile. This is confirmed by the positive sign of the concentration indexes

The poor receive more public subsidy than their income share Concentration curves dominate the Lorenz curve (positive sign) Subsidy is inequality reducing or weakly progressive as it closes the

relative gap in welfare between the rich and the poor. Kakwani index is negative at all levels, both for outpatient and

inpatient care.

In sum…

The public subsidy in Rwanda is pro-rich Regressive

The poor receive less public subsidy than their population share Inequality reducing

The poor receive more public subsidy than their consumption share The public subsidy therefore contributes to reduce the gap between the poor

and the rich.

 Bias towards tertiary hospitals

Capture more than three quarters of the total public subsidy to the health sector.

Most health problems can be treated at the lowest level of care Population seeks more care at primary health care facility

Questions the efficiency of current public spending on health

4. What does BIA tell us for policy reform?

What can we do to improve the benefit incidence of the public subsidy?

1. Allocate public subsidies according to the needs of the population

More public subsidies targeted towards primary health care services to cater for the major morbidity causes

More public subsidies on prevention rather than treatment

2. Target subsidies to high impact interventions Maternal and child health services Preventive care

3. Target the poor Subsidize the premium for health insurance and of co-payments for poorest

groups Conditional cash transfers

4. Design strategies for behavioral change

Limitations

Of the Rwanda case study Rwanda is evolving rapidly

Need to conduct the same analysis with more recent data New health financing innovations

Fiscal decentralization National scaling-up of PBF Expansion of community-based health insurance

Of Benefit Incidence Analyses Powerful tool to highlight problems Tool which does not provide solutions Complementary analyses needed to understand:

The current allocation pattern Households’ behavior Efficiency of concurrent targeting strategies

5. BIA and PBF?

PBF could improve the benefit incidence of the public subsidy for the poor By targeting high impact intervention By targeting lower levels of care By addressing the needs of the population

But, there is a significant risk that PBF increases inequalities If equity is not explicitly considered in the design of the

PBF scheme, facilities will focus on the easier to reach Equity should be included in the design of performance

indicators

Useful references on BIAs

Castro-Leal, F., Dayton, J., Demery, Y., & Mehra, K. (2000). Public spending on health care in Africa: do the poor benefit? Bulletin of the World Health Organization, 78(1), 66-74.

Davoodi, H., Tiongson, E., & Asawanuchi, S. (2003). How useful are benefit incidence analyses of public education and health spending. Washington, D.C.: International Monetary fund.

O’Donnell, O., Van Doorslaer, E., Rannan-Eliya, R., Aparnaa, S., Adhikari, S. R., Harbianto, D., et al. (2007). The incidence of public spending on healthcare: comparative evidence from Asia. World Bank Economic Review, 21(1), 93-123.

O’Donnell, O., van Doorslaer, E., Wagstaff, A., & Lindelow, M. (2008). Analyzing health equity using household survey data: a guide to techniques and their implementation. Washington, D.C.: World Bank.