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March 17, 20260 citationsOpen Access

Time-Series Forecasting Model Evaluation of Community Health Centre Systems in Rwanda: A Cost-Effectiveness Analysis

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KBKizito Byaruhanga

Key Points

  • This research aims to develop a robust time-series forecasting model to evaluate cost-effectiveness in Rwandan community health centres.
  • Utilized a mixed-methods design including surveys and interviews.
  • Formulated and assessed a time-series forecasting model.
  • Established verifiable assumptions and reproducible analytical methods.
  • Estimated treatment effect using a logit model.
  • Demonstrated bounded error under perturbation conditions.
  • Achieved a convergent estimation process that links proposed metrics to observed outcomes.
  • Findings support transparency and informed decision-making for stakeholders.

Abstract

This study addresses a current research gap in Medicine concerning Methodological evaluation of community health centres systems in Rwanda: time-series forecasting model for measuring cost-effectiveness in Rwanda. The objective is to formulate a rigorous model, state verifiable assumptions, and derive results with direct analytical or practical implications. A mixed-methods design was used, combining survey and interview data collected over the study period. The results establish bounded error under perturbation, a convergent estimation process under stated assumptions, and a stable link between the proposed metric and observed outcomes. The findings provide a reproducible analytical basis for subsequent theoretical and applied extensions. Stakeholders should prioritise inclusive, locally grounded strategies and improve data transparency. Methodological evaluation of community health centres systems in Rwanda: time-series forecasting model for measuring cost-effectiveness, Rwanda, Africa, Medicine, original research This work contributes a formal specification, transparent assumptions, and mathematically interpretable claims. Treatment effect was estimated with logit (pᵢ) =₀+^ Xᵢ, and uncertainty reported using confidence-interval based inference.

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Cite This Study

Kizito Byaruhanga (2014) studied this question.

synapsesocial.com/papers/69b8f13ddeb47d591b8c62cfhttps://doi.org/10.5281/zenodo.19025996
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