Email updates

Keep up to date with the latest news and content from BMC Health Services Research and BioMed Central.

Open Access Highly Accessed Study protocol

Design of an impact evaluation using a mixed methods model – an explanatory assessment of the effects of results-based financing mechanisms on maternal healthcare services in Malawi

Stephan Brenner1, Adamson S Muula2, Paul Jacob Robyn3, Till Bärnighausen45, Malabika Sarker1, Don P Mathanga2, Thomas Bossert4 and Manuela De Allegri1*

Author Affiliations

1 Institute of Public Health, Ruprecht-Karls-University, Heidelberg, Germany

2 Department of Community Health, University of Malawi, College of Medicine, Blantyre, Malawi

3 The World Bank, Washington, DC, USA

4 Department of Global Health and Population, Harvard School of Public Health, Boston, Massachusetts, United States of America

5 Wellcome Trust Africa Centre for Health and Population Studies, University of KwaZulu-Natal, Mtubatuba, South Africa

For all author emails, please log on.

BMC Health Services Research 2014, 14:180  doi:10.1186/1472-6963-14-180

Published: 22 April 2014

Abstract

Background

In this article we present a study design to evaluate the causal impact of providing supply-side performance-based financing incentives in combination with a demand-side cash transfer component on equitable access to and quality of maternal and neonatal healthcare services. This intervention is introduced to selected emergency obstetric care facilities and catchment area populations in four districts in Malawi. We here describe and discuss our study protocol with regard to the research aims, the local implementation context, and our rationale for selecting a mixed methods explanatory design with a quasi-experimental quantitative component.

Design

The quantitative research component consists of a controlled pre- and post-test design with multiple post-test measurements. This allows us to quantitatively measure ‘equitable access to healthcare services’ at the community level and ‘healthcare quality’ at the health facility level. Guided by a theoretical framework of causal relationships, we determined a number of input, process, and output indicators to evaluate both intended and unintended effects of the intervention. Overall causal impact estimates will result from a difference-in-difference analysis comparing selected indicators across intervention and control facilities/catchment populations over time.

To further explain heterogeneity of quantitatively observed effects and to understand the experiential dimensions of financial incentives on clients and providers, we designed a qualitative component in line with the overall explanatory mixed methods approach. This component consists of in-depth interviews and focus group discussions with providers, service user, non-users, and policy stakeholders. In this explanatory design comprehensive understanding of expected and unexpected effects of the intervention on both access and quality will emerge through careful triangulation at two levels: across multiple quantitative elements and across quantitative and qualitative elements.

Discussion

Combining a traditional quasi-experimental controlled pre- and post-test design with an explanatory mixed methods model permits an additional assessment of organizational and behavioral changes affecting complex processes. Through this impact evaluation approach, our design will not only create robust evidence measures for the outcome of interest, but also generate insights on how and why the investigated interventions produce certain intended and unintended effects and allows for a more in-depth evaluation approach.

Keywords:
Mixed methods; Impact evaluation; Performance-based incentives; Study design