Can Combining Performance-Based Financing With Equity Measures Result in Greater Equity in Utilization of Maternal Care Services? Evidence From Burkina Faso.

Takondwa Mwase,Stephan Brenner,Manuela De Allegri,Hervé Hien,Michael Hillebrecht,Serge M.A Somda,Saidou Hamadou,Julia Lohmann

doi:10.34172/ijhpm.2020.121

Abstract

Background: As countries reform health financing systems towards universal health coverage, increasing concerns emerge on the need to ensure inclusion of the most vulnerable segments of society, working to counteract existing inequities in service coverage. To this end, selected countries in sub-Saharan Africa have decided to couple performance-based financing (PBF) with demand-side equity measures. Still, evidence on the equity impacts of these more complex PBF models is largely lacking. We aimed at filling this gap in knowledge by assessing the equity impact of PBF combined with equity measures on utilization of maternal health services in Burkina Faso. Methods: Our study took place in 24 districts in rural Burkina Faso. We implemented an experimental design (clusterrandomized trial) nested within a quasi-experimental one (pre- and post-test design with independent controls). Our analysis relied on self-reported data on pregnancy history from 9999 (baseline) and 11 010 (endline) women of reproductive age (15-49 years) on use of maternal healthcare and reproductive health services, and estimated effects using a difference-in-differences (DID) approach, purposely focused on identifying program effects among the poorest wealth quintile. Results: PBF improved the utilization of few selected maternal health services compared to status quo service provision. These benefits, however, were not accrued by the poorest 20%, but rather by the other quintiles. PBF combined with equity measures did not produce better or more equitable results than standard PBF, with specific differences only on selected outcomes. Conclusion: Our findings challenge the notion that implementing equity measures alongside PBF is sufficient to produce an equitable distribution in program benefits and point at the need to identify more innovative and contextsensitive measures to ensure adequate access to care for the poorest. Our findings also highlight the importance of considering changing policy environments and the need to assess interferences across policies.

Highlights

There is a growing concern that health inequalities related to social determinants of health are responsible for the slow progress witnessed in health and healthcare at global, regional and country levels, potentially jeopardizing opportunities to achieve the health related Sustainable Development Goals (SDGs).[1]
Our study evaluates an “equity-conscious” performance-based financing (PBF) design, which was recently implemented in Burkina Faso and which was piloted with 3 different equity measures
Significant differences between PBF and control group existed in baseline values for a number of outcome variables: ANC4+ visits, HIV testing in pregnancy, facilitybased delivery, PNC1+ visit and PNC3+ visits (Table 4)

Summary

Introduction

There is a growing concern that health inequalities related to social determinants of health are responsible for the slow progress witnessed in health and healthcare at global, regional and country levels, potentially jeopardizing opportunities to achieve the health related Sustainable Development Goals (SDGs).[1] As countries embark on health financing and service delivery reforms, often targeting women and children first, monitoring health and healthcare inequalities remains an essential element of tracking progress towards the SDG 3 target of achieving universal health coverage by 2030, ensuring that no one is left behind.[2] Monitoring is even more urgent and important in low- and middle-income countries (LMICs) because, despite the recent progress made in curbing maternal and child deaths, serious inequities in maternal and child health persist, especially in sub-Saharan Africa.[3] Exacerbating the situation, LMICs face huge coverage gaps, health system inefficiencies, and insufficient quality of service delivery.[4]. While some studies suggest pro-least poor effects,[8,9] others find evidence for the opposite[10] or distributional-neutral effects.[11,12] Given the mixed evidence, an increasing number of authors advocate the introduction of PBF designs deliberately aimed at spreading program benefits more evenly across wealth groups.[8,11,12] to date limited evidence is available.[13]

Methods

Results

Discussion

Conclusion