A Systematic Review of Methodological Approaches for Cost-Effectiveness Forecasting in Kenyan Community Health Centre Systems: 2000–2026

{ "background": "Community health centres are a cornerstone of primary healthcare delivery in Kenya, yet long-term financial sustainability remains a critical challenge. Robust forecasting of their cost-effectiveness is essential for strategic resource allocation and policy planning, but the methodological rigour of existing approaches is unclear.", "purpose and objectives": "This systematic review aims to critically evaluate the methodological approaches used for cost-effectiveness forecasting in Kenyan community health centre systems, identifying prevalent models, their technical specifications, and key methodological gaps.", "methodology": "A systematic search of peer-reviewed literature and grey literature was conducted following PRISMA guidelines. Studies employing quantitative forecasting models for cost-effectiveness or economic evaluation were included. Data were extracted on model structure, variables, validation techniques, and uncertainty handling. Quality assessment used a bespoke tool for forecasting studies.", "findings": "Of the 27 included studies, a dominant theme was the reliance on deterministic Markov cohort models (63%), with few incorporating stochastic elements or advanced time-series techniques. A key concrete result is that only 22% of models reported using robust standard errors or bootstrapping to account for parameter uncertainty in their forecasts. The autoregressive integrated moving average (ARIMA) model, when used, was typically specified as \Δᵈ yt = c + \φ1 \Δᵈ yt-1 + ... + \ \Δᵈ yt-p + \θ1 \εt-1 + ... + \ \εt-q + \, but often without adequate diagnostic testing.", "conclusion": "Methodological approaches for cost-effectiveness forecasting in this context are heterogeneous and frequently lack sophistication in handling uncertainty and temporal dynamics, potentially compromising the reliability of long-term projections.", "recommendations": "Future research should prioritise the adoption and validation of stochastic models, integrate high-frequency routine health system data, and adhere to formal forecasting evaluation protocols to improve predictive performance and policy utility.", "key words": "economic evaluation, health