Using multi-country household surveys to understand who provides reproductive and maternal health services in low and middle-income countries: a critical appraisal of the Demographic and Health Surveys
Footman, K; Benova, L; Goodman, C; Macleod, D; Lynch, CA; Penn-Kekana, L; Campbell, OM; (2015) Using multi-country household surveys to understand who provides reproductive and maternal health services in low and middle-income countries: a critical appraisal of the Demographic and Health Surveys. Tropical Medicine & International Health. ISSN 1360-2276 DOI: 10.1111/tmi.12471
The Demographic and Health Surveys (DHS) are a vital data resource for cross-country comparative analyses. This paper is part of a set of analyses assessing the types of providers being used for reproductive and maternal health care across 57 countries. Here, we examine some of the challenges encountered using DHS data for this purpose, present the provider classification we used, and provide recommendations to enable more detailed and accurate cross-country comparisons of healthcare provision. We used the most recent DHS surveys between 2000 and 2012; 57 countries had data on family planning and delivery care providers and 47 countries had data on antenatal care. Every possible response option across the 57 countries was listed and categorised. We then developed a classification to group provider response-options according to two key dimensions: clinical nature and profit motive. We classified the different types of maternal and reproductive health care providers, and the individuals providing care. Documented challenges encountered during this process were limitations inherent in household survey data based on respondents’ self-report; conflation of response options in the questionnaire or at the data processing stage; category errors of the place versus professional for delivery; inability to determine whether care received at home is from the public or private sector; a large number of negligible response options; inconsistencies in coding and analysis of datasets; and use of inconsistent headings. To improve clarity we recommend addressing issues such as conflation of response options, data on public versus private provider, inconsistent coding, and obtaining metadata. More systematic and standardized collection of data would aid international comparisons of progress towards improved financial protection, and allow us to better characterise the incentives and commercial nature of different providers.