Step-wedge cluster-randomised community-based trials: An application to the study of the impact of community health insurance

Manuela De Allegri¹ , Subhash Pokhrel² , Heiko Becher¹ , Hengjin Dong¹ , Ulrich Mansmann³ , Bocar Kouyaté⁴^,6 , Gisela Kynast-Wolf¹ , Adjima Gbangou⁵^,6 , Mamadou Sanon⁶ , John Bridges⁷ and Rainer Sauerborn¹

¹Department of Tropical Hygiene and Public Health, University of Heidelberg, Germany

²Health Economics Research Group (HERG), Brunel University, UK

³Institute for Medical Informatics, Biometrics, and Epidemiology, University of Munich, Germany

⁴Centre National de Recherche et de Formation sur le Paludisme, Ouagadougou, Burkina Faso

⁵Direction des Etudes et de la Planification, Ministère de la Santé, Ouagadougou, Burkina Faso

⁶Centre de Recherche en Santé de Nouna, Nouna, Burkina Faso

⁷Bloomberg School of Public Health, Johns Hopkins University, USA

author email corresponding author email

Health Research Policy and Systems 2008, 6:10doi:10.1186/1478-4505-6-10


Published:	22 October 2008

Abstract

Background

We describe a step-wedge cluster-randomised community-based trial which has been conducted since 2003 to accompany the implementation of a community health insurance (CHI) scheme in West Africa. The trial aims at overcoming the paucity of evidence-based information on the impact of CHI. Impact is defined in terms of changes in health service utilisation and household protection against the cost of illness. Our exclusive focus on the description and discussion of the methods is justified by the fact that the study relies on a methodology previously applied in the field of disease control, but never in the field of health financing.

Methods

First, we clarify how clusters were defined both in respect of statistical considerations and of local geographical and socio-cultural concerns. Second, we illustrate how households within clusters were sampled. Third, we expound the data collection process and the survey instruments. Finally, we outline the statistical tools to be applied to estimate the impact of CHI.

Conclusion

We discuss all design choices both in relation to methodological considerations and to specific ethical and organisational concerns faced in the field. On the basis of the appraisal of our experience, we postulate that conducting relatively sophisticated trials (such as our step-wedge cluster-randomised community-based trial) aimed at generating sound public health evidence, is both feasible and valuable also in low income settings. Our work shows that if accurately designed in conjunction with local health authorities, such trials have the potential to generate sound scientific evidence and do not hinder, but at times even facilitate, the implementation of complex health interventions such as CHI.