Illness reporting and demand for medical care in rural Burkina Faso

This is the post-print version of the final paper published in Social Science & Medicine. The published article is available from the link below. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. Copyright @ 2010 Elsevier B.V.The issue of illness reporting in modelling demand for health care in low- and middle-income countries can be handled according to either of two conceptually-different constructs: (a) considering illness reporting behaviour as endogenous to demand; or (b) considering demand itself as the outcome of a sample selection phenomenon. In this paper, we take the second viewpoint and estimate the demand for medical care with an estimator that uses Heckman-type. Empirical estimates based on household survey data from rural Burkina Faso suggest that there are some implications of illness reporting behaviour for modelling the demand for medical care.German Science Foundatio

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

This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.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