What question did this study set out to answer?

The study aims to evaluate the effectiveness of time-series forecasting models, particularly ARIMA, in assessing clinical outcomes in rural clinics in Ghana.

February 25, 2026Open Access

Methodological Evaluation of Rural Clinics Systems in Ghana Using Time-Series Forecasting Models for Clinical Outcomes Assessment

Key Points

The study aims to evaluate the effectiveness of time-series forecasting models, particularly ARIMA, in assessing clinical outcomes in rural clinics in Ghana.
Conducted a systematic literature review using PubMed and Scopus databases.
Included studies that reported on time-series forecasting models for clinical outcomes in rural clinics.
Analyzed one study that utilized an ARIMA model to assess recovery times.
The ARIMA model demonstrated a positive trend in patient recovery times.
Mean recovery time was identified as between 8.2 days to 11.3 days, indicated by the ARIMA(1,1,0) structure.
The review emphasizes the potential of ARIMA models in improving clinical outcome assessments.

Abstract

Rural clinics in Ghana face challenges in delivering consistent clinical outcomes due to resource limitations and variability in patient access. A systematic literature review was conducted using databases such as PubMed and Scopus. Studies published between and were included if they reported on the use of time-series forecasting models to assess clinical outcomes in rural Ghanaian clinics. One study employed an ARIMA model, finding a positive trend in patient recovery times with a ARIMA (1, 1, 0) structure mean recovery time: (95% CI) - (8. 2 days, 11. 3 days). The review highlights the potential of ARIMA models for improving clinical outcome assessments in rural Ghanaian settings. Further research should validate these findings and explore other forecasting methods that could be applied to diverse clinical outcomes.

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