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March 17, 20260 citationsOpen Access

Time-Series Forecasting Model for Evaluating Cost-Effectiveness of Community Health Centres in Kenya

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JKJosphat Gitonga KibetMMMwangi Wangari MuiruriEMEphraim Ochieng Musila

Key Points

  • The aim is to develop a time-series forecasting model to evaluate the cost-effectiveness of community health centres in Kenya.
  • Utilized a mixed-methods design combining survey and interview data.
  • Formulated a rigorous forecasting model with verifiable assumptions.
  • Analyzed data to establish a bound error under perturbation.
  • Demonstrated a stable link between the proposed metric and observed outcomes.
  • Estimated treatment effects using a logit model.
  • Provided a reproducible analytical basis for future extensions.

Abstract

This study addresses a current research gap in Medicine concerning Methodological evaluation of community health centres systems in Kenya: time-series forecasting model for measuring cost-effectiveness in Kenya. 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 Kenya: time-series forecasting model for measuring cost-effectiveness, Kenya, 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

Kibet et al. (2014) studied this question.

synapsesocial.com/papers/69b8f162deb47d591b8c653ehttps://doi.org/10.5281/zenodo.19032569
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