Non-Preferred Contraceptive Method Use in Low-Resourced Settings: Exploring Inappropriate Medical Contraindications and Person-Centered Care
Summary
Family planning prevents unwanted pregnancy and reduces maternal and child mortality in low-resourced settings; however, women in these settings encounter unnecessary medical barriers to contraceptive care. Inappropriate medical contraindications (IMCs) occur when providers deny eligible women their preferred contraceptive method without an evidence-based medical rationale. This medical barrier to family planning use is difficult to identify using traditional survey methods and has been understudied for the last 20 years. Our previous research suggests non-preferred method use is one indicator of IMCs, as 55% of non-preferred method users reported a "medical reason" for nonuse. Further, qualitative data on medical reasons for non-use revealed IMC application by providers. Non-preferred method use is undesirable, as it can lead to dissatisfaction, discontinuation, and unplanned pregnancies. Identifying interventions that effectively reduce non-preferred method use and IMCs is an important contribution to global public health. The long-term objective of this research is to identify effective and scalable interventions for reducing medical barriers to contraceptive care for women living in low-resource settings. This project will 1) estimate the impact of two social accountability interventions on non-preferred method use at the population level; 2) determine the frequency and elucidate the nature of non-preferred method use due to IMCs using innovative mystery client data collected among 137 public-sector Kenyan facilities, and 3) use qualitative methods to investigate provider perspectives on non-preferred method use and IMCs to explore key factors. We hypothesize that social accountability interventions, in which community oversight motivates providers to improve their performance, could increase patient-centeredness of care and therefore reduce non-preferred method use. To test this hypothesis, Aim 1 will use difference-in-difference methods to analyze pre- and post-intervention data from a randomized controlled trial assessing two social accountability interventions in Kisumu, Kenya. Aim 2 will use mixed methods to analyze mystery client data collected from all public facilities in Kisumu, Kenya. Aim 3 proposes in-depth interviews with family planning providers in Kisumu, where the applicant will build a new skill standardized vignettes to understand and contextualize provider decision-making around IMCs. These data collection methods will overcome major methodological challenges that have prevented research into IMCs in the past 20 years. Results will contribute important new information for improving contraceptive care in low-resource settings.