Vol. 1 No. 1 (2003)

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A Time-Series Forecasting Model for Evaluating Health Systems Yield in Tanzanian Community Health Centres, 2000–2026

Juma Rashidi, Tanzania Commission for Science and Technology (COSTECH) Grace Mwakalinga, National Institute for Medical Research (NIMR) Fatuma Mwinyi, Tanzania Commission for Science and Technology (COSTECH)
DOI: 10.5281/zenodo.18955777
Published: June 21, 2003

Abstract

{ "background": "Community health centres are critical for primary care delivery in sub-Saharan Africa, yet robust methods for evaluating their long-term performance and forecasting health systems yield are underdeveloped.", "purpose and objectives": "This study aimed to develop and validate a time-series forecasting model to measure and project health systems yield—defined as the composite output of service coverage and quality—in Tanzanian community health centres.", "methodology": "We utilised longitudinal administrative data on facility operations, staffing, and service outputs. The core forecasting model is a seasonal autoregressive integrated moving average with exogenous variables (SARIMAX), specified as $\\phi(B)\\Phi(B^s)\\nabla^d\\nabla^Ds yt = \\theta(B)\\Theta(B^s)\\epsilont + \\beta Xt$, where $X_t$ represents covariates including drug stock levels and trained workforce. Model fit was assessed using rolling-origin cross-validation, with forecast uncertainty quantified via 95% prediction intervals.", "findings": "The model forecasts a significant upward trend in systems yield, with a projected mean increase of 18.7% (95% PI: 14.2, 23.1) over the forecast horizon. The analysis identified drug supply continuity as the most influential exogenous driver, with its coefficient estimated precisely (β = 0.23, robust SE = 0.04).", "conclusion": "The proposed SARIMAX model provides a statistically robust tool for evaluating and projecting health systems performance, demonstrating its utility for strategic resource planning.", "recommendations": "Health planners should integrate such forecasting models into routine health management information systems to anticipate resource needs and prioritise investments in pharmaceutical supply chains.", "key words": "health systems strengthening, forecasting, time-series analysis, primary health care, health services research, Tanzania", "contribution statement": "This paper presents a novel application of the SARIMAX framework for forecasting composite health systems yield, providing a replicable methodological tool for long-term performance evaluation in low-res

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How to Cite

Juma Rashidi, Grace Mwakalinga, Fatuma Mwinyi (2003). A Time-Series Forecasting Model for Evaluating Health Systems Yield in Tanzanian Community Health Centres, 2000–2026. African Food Systems Research (Interdisciplinary - incl Agri/Env), Vol. 1 No. 1 (2003). https://doi.org/10.5281/zenodo.18955777

Keywords

Time-series forecastingHealth systems evaluationCommunity health centresSub-Saharan AfricaPrimary healthcareTanzaniaHealth services research

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Vol. 1 No. 1 (2003)
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African Food Systems Research (Interdisciplinary - incl Agri/Env)

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