This article focuses on the methodological evaluation of district hospitals in Kenya, with a particular emphasis on assessing adoption rates. A multilevel regression analysis approach was employed, considering both hospital-level and district-level variables to understand the impact on adoption rates. Data were collected from a comprehensive survey conducted in over 50 district hospitals across Kenya. The multilevel regression analysis revealed that factors such as funding availability (proportion: 32%) and staff training programmes (direction: positive effect) significantly influence the adoption rate of new medical technologies. These findings provide insights into the operational challenges faced by district hospitals in implementing modern healthcare practices. The study concludes with a comprehensive understanding of the factors driving the adoption rates within Kenyan district hospitals, offering evidence-based recommendations for policy makers and healthcare administrators to enhance system efficiency and quality of care. Based on the findings, it is recommended that policymakers prioritise investment in funding and staff training programmes to boost the adoption rate of new medical technologies. Additionally, there should be a focus on improving infrastructure and technological resources at district hospitals. district hospitals, multilevel regression analysis, adoption rates, healthcare practices, Kenya Treatment effect was estimated with logit (pᵢ) =₀+^ Xᵢ, and uncertainty reported using confidence-interval based inference.
Mutua et al. (2015) studied this question.