OCTOBER 4 TH, 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. Methodology 3. Case study on Rwanda 4. 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 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 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$Health Center District Hospital National referral Hospital Delivery of Health services 2,669,219875,8944,563,678 Drugs2,568,085594,163 Financial operations 610,417462,328 Government Subsidies 93,910198,6565,930,795 NGO and donors subsidies 1,123,311895,7602,638,518 Total7,064,9433,026,80113,132,991 Of which public subsidies 1,217,2221,094,4168,569,313 Public subsidy (US$ per capita) Source: PER

Estimate public subsidy unit cost Public subsidy’s unit cost = public subsidy/ # of outpatient and inpatient visits at each level. Health centerDistrict HospitalReferral Hospital Outpatient visits Inpatient visits Outpatient visits Inpatient visits Outpatient visits Inpatient visits Public subsidies (US$) 1,016,380200,842454,183640,2332,228,0216,341,292 Total utilization 4,871,668348,343479,002152,510189,72625,317 Unit cost (US$)

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 centerDistrict hospital National referral hospital Cumulative shares OutpatientInpatientOutpatientInpatientOutpatientInpatient - Test of dominance against 45 o line Test of dominance against Lorenz curve Concentration Index Kakwani Index

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), 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), 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.