Rwanda's district hospitals have faced challenges in adopting new healthcare technologies and practices. A time-series forecasting model was employed to predict adoption rates based on historical data from to. The model included statistical analysis for robustness and uncertainty quantification. The forecast indicated an increasing trend in adoption rates, with a predicted growth of 20% by the end of compared to the baseline rate. This study validates the effectiveness of time-series forecasting models in assessing healthcare technology adoption within district hospitals. Policy-makers should consider implementing these models to better forecast and plan for future technology integration into Rwanda's healthcare system. time-series analysis, healthcare technology adoption, district hospitals, Rwanda Treatment effect was estimated with logit (pᵢ) =₀+^ Xᵢ, and uncertainty reported using confidence-interval based inference.
Ruganwa et al. (Thu,) studied this question.
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