Methodological Evaluation of District Hospitals Systems in Ghana Using Time-Series Forecasting Models for Reliability Measurement

Ghana's healthcare system faces challenges in managing district hospitals' operations efficiently. Time-series forecasting models were applied to historical data from Ghanaian district hospitals. The Box-Jenkins ARIMA model was used, with uncertainty quantified through robust standard errors. The forecast accuracy suggests a potential need for resource reallocation in certain wards within the system (e.g., a 15% variance between actual and predicted patient admissions). Time-series forecasting models can be effective tools for assessing district hospital system reliability, with specific insights into ward-level performance. Investigate targeted interventions where forecasted discrepancies are significant to improve system efficiency. forecasting, time series, ARIMA, healthcare systems, Ghana Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.