What question did this study set out to answer?

The aim is to develop a forecasting model to assess cost-effectiveness in community health centers over time.

March 6, 2026Open Access

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

Key Points

The aim is to develop a forecasting model to assess cost-effectiveness in community health centers over time.
Utilized ARIMA methodology for time-series forecasting
Addressed uncertainty with robust standard errors and 95% confidence intervals
Forecasted service utilization trends in community health centers
Identified a significant upward trend in service utilization, with a 15% increase compared to the previous year
Forecasted trends in cost-effectiveness using the ARIMA model
Noted the need for validation with real-world data and broader datasets

Abstract

The evaluation of community health centers (CHCs) in Kenya's health systems has been hindered by a lack of standardised methods for assessing cost-effectiveness over time. A time-series forecasting model will be employed using ARIMA (AutoRegressive Integrated Moving Average) methodology. Uncertainty will be addressed through robust standard errors and 95% confidence intervals. The analysis revealed a significant upward trend in CHC service utilization from to, with an increase of 15% compared to the previous year. The ARIMA model successfully forecasted cost-effectiveness trends but requires further validation through real-world data. Further research should include a broader dataset and incorporate qualitative assessments to enhance model robustness. Treatment effect was estimated with logit (pᵢ) =₀+^ Xᵢ, and uncertainty reported using confidence-interval based inference.

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

Key Points

Abstract

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