{ "background": "Evaluating the adoption of community health centre systems is critical for health policy in Kenya, yet robust causal evidence is often lacking. Quasi-experimental designs offer a viable alternative to randomised trials for assessing real-world implementation, but their methodological application and rigour in this context have not been systematically appraised. ", "purpose and objectives": "This systematic review aims to identify, synthesise, and critically evaluate the application of quasi-experimental methodologies used to measure adoption rates of community health centre systems in Kenya, assessing their design strengths, limitations, and inferential validity. ", "methodology": "A systematic search of multiple academic databases was conducted following PRISMA guidelines. Studies employing quasi-experimental designs to evaluate adoption were included. Data were extracted on design type, identification strategies, outcome measures, and statistical approaches. Study quality was assessed using an adapted risk-of-bias tool for quasi-experimental research. ", "findings": "Of the 27 included studies, difference-in-differences was the predominant design (63%). A key methodological finding was the frequent omission of parallel trends testing, undermining causal claims. The pooled analysis indicated that interventions incorporating financial incentives were associated with a higher mean adoption rate (22 percentage points, 95% CI: 18 to 26) compared to those without, estimated using a random-effects meta-regression model: yi = \0 + \1 xi + ui + \, where uᵢ represents study-level heterogeneity. ", "conclusion": "Quasi-experimental evaluations are increasingly used but often exhibit significant methodological shortcomings that compromise the robustness of evidence on system adoption. More rigorous application and reporting of key design assumptions are required. ", "recommendations": "Future evaluations should pre-specify identification strategies, routinely test critical assumptions like parallel trends, and employ robustness checks with clustered standard errors. Funders should mandate methodological protocols to enhance evidence quality. ", "key words": "quasi-experimental design, health systems research, adoption, implementation science
Wanjiku Mwangi (Sun,) studied this question.