A Methodological Evaluation and Time-Series Forecasting Model for Risk Reduction in Rwandan Community Health Centre Systems

July 20, 2000Open Access

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Key Points

The aim is to develop and evaluate a time-series forecasting model for predicting risk in community health centres in Rwanda.
Conducted an intervention study using longitudinal data from health centres.
Analyzed stock-outs, patient attendance, and referral rates.
Utilized an ARIMAX model to assess risk factors.
Used rolling-origin forecast evaluation to assess model performance.
The ARIMAX(2,1,1) model reduced forecast errors for medicine stock-outs by 34%.
Community health worker deployment density significantly predicted reduced operational risk.
Model demonstrated superior accuracy compared to other forecasting benchmarks.

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Intervention study develops a time-series forecasting model to predict risk in community health centres, suggesting enhanced operational stability.

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Mukamana et al. (2000) studied this question.

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