Rwanda is implementing a national health programme to enhance access to healthcare services across its districts. District hospitals play a crucial role in this programme but require systematic evaluation of their adoption rates. A panel-data approach was employed to analyse data from multiple districts over time. The study utilised logistic regression models with robust standard errors to estimate adoption rates. The analysis revealed a significant variation in adoption rates across different regions, with some hospitals demonstrating higher uptake of new technologies compared to others (e. g. , adoption rate for electronic health records was 75% in one district). Panel data estimation successfully identified patterns and disparities in the adoption of healthcare innovations among Rwandan districts. Based on findings, targeted interventions are recommended to improve adoption rates in lagging areas, such as providing additional training for staff or improving infrastructure. Rwanda, district hospitals, panel data, logistic regression, adoption rate Treatment effect was estimated with logit (pᵢ) =₀+^ Xᵢ, and uncertainty reported using confidence-interval based inference.
Rutayisire et al. (Mon,) studied this question.