What question did this study set out to answer?

This research aims to evaluate the effectiveness and adoption rates of community health centres in Rwanda using time-series forecasting.

February 22, 2026Open Access

Evaluation of Community Health Centre Systems in Rwanda through Time-Series Forecasting Models for Adoption Rate Measurement

Puntos clave

This research aims to evaluate the effectiveness and adoption rates of community health centres in Rwanda using time-series forecasting.
Conducted a time-series analysis with a mixed-effects model.
Incorporated data from multiple community health centres across various regions.
Estimated treatment effect using a logit model.
Predicted a 15% increase in CHC adoption over the next five years.
Confidence interval for the prediction is ±3 percentage points.
Confirmed the effectiveness of time-series forecasting for measuring adoption rates.

Resumen

Community health centres (CHCs) play a crucial role in healthcare delivery across Rwanda, yet their effectiveness and adoption rates vary over time. A time-series analysis was conducted with a Mixed-effects model for predicting future adoption rates, incorporating data from multiple CHCs across different regions. The mixed-effects model predicted an increase in CHC adoption by 15% over the next five years, with a confidence interval of ±3 percentage points. The study confirmed that time-series forecasting can be effectively used to measure and predict adoption rates for community health centres in Rwanda. Policy makers should consider these forecasts to plan future resource allocation and infrastructure development for CHCs. Treatment effect was estimated with logit (pᵢ) =₀+^ Xᵢ, and uncertainty reported using confidence-interval based inference.

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