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Policy Translation Tools and Products

When we ask if a certain policy works, we often mean to ask if the policy works in a specific context and setting. Unfortunately, health policy has an attribution problem. Multiple factors influence how health systems affect health outcomes, and these factors interact in confusing and often contradictory ways. Worse yet, relatively few studies explore how policies lead to outcomes within a specific country. As a result, policymakers, advocates, and researchers struggle to assess which reforms are most effective for achieving Universal Health Coverage (UHC).

found that one of the most common reforms, premium-based health insurance, is “unlikely to be the most efficient or equitable means of financing health services in sub-Saharan African countries.” found little evidence of impact for various UHC-related policy reforms, such as insurance coverage expansion, user-fee exemptions, private sector contracting, and performance-based financing. Reasons varied from an inability to isolate effects from causes to differences in expert opinions and mixed study results. Worse, reforms often skew the health system more to the wealthy, urban, employed, and educated by violating some of the five unacceptable tradeoffs identified by

Often these problems are ones of contextualization: evidence of impact in one country did not ensure that the reform would work elsewhere. For example, performance-based financing (PBF) reforms in Rwanda showed significant improvements in treatment quality and utilization, especially for maternal health interventions of a similar intervention in Cameroon showed little impact on maternal and child health indicators, likely due to the low-user-fee environment in Rwanda and the high-user-fee one in Cameroon.

So, what can be done to address these evaluation challenges? Here at RTI, researchers from across the institute came together to conduct literature reviews identifying data sources, evaluation options, and methodological issues for evaluating health policy in low- and middle-income countries. For a description of our methods and more in-depth findings