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Bridging the gap with a gender lens: How two implementation research datasets were repurposed to inform health policy reform in Kenya
Policies as they are written often mask the power relations behind their creation (Hull, 2008). As a result, not only are policies that appear neat on the page frequently messy in their implementation on the ground, but the messiness of implementation, and implementation science, often brings these...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7646722/ https://www.ncbi.nlm.nih.gov/pubmed/33156938 http://dx.doi.org/10.1093/heapol/czaa117 |
Sumario: | Policies as they are written often mask the power relations behind their creation (Hull, 2008). As a result, not only are policies that appear neat on the page frequently messy in their implementation on the ground, but the messiness of implementation, and implementation science, often brings these hidden power relations to light. In this paper, we examine the process by which different data sources were generated within a programme meant to increase access to quality private healthcare for the poorest populations in Kenya, how these sources were brought and analyzed together to examine gender bias in the large-scale rollout of Kenya’s National Hospital Insurance Fund (NHIF) beyond public hospitals and civil service employees, and how these findings ultimately were developed in real time to feed into the NHIF reform process. We point to the ways in which data generated for implementation science purposes and without a specific focus on gender were analyzed with a policy implementation analysis lens to look at gender issues at the policy level, and pay particular attention to the role that the ongoing close partnership between the evaluators and implementers played in allowing the teams to develop and turn findings around on short timelines. In conclusion, we discuss possibilities for programme evaluators and implementers to generate new data and feed routine monitoring data into policy reform processes to create a health policy environment that serves patients more effectively and equitably. Implementation science is generally focused on programmatic improvement; the experiences in Kenya make clear that it can, and should, also be considered for policy improvement. |
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