What question did this study set out to answer?

The study aims to evaluate the methodologies for assessing district hospital performance in Tanzania, focusing on yield improvement through forecasting.

February 26, 2026Open Access

Methodological Evaluation of District Hospitals Systems in Tanzania using Time-Series Forecasting Models for Yield Improvement Analysis

SKSembene KigutuiCatholic University of Health and Allied Sciences KMKibuzi MwakyakwairuCatholic University of Health and Allied Sciences

Key Points

The study aims to evaluate the methodologies for assessing district hospital performance in Tanzania, focusing on yield improvement through forecasting.
Conducted a comprehensive literature review to identify relevant methodologies for hospital performance assessment.
Utilized time-series forecasting models, specifically ARIMA, to predict future yield based on historical data.
Analyzed the predictive accuracy of models using out-of-sample R² values.
ARIMA models demonstrated significant predictive accuracy with an out-of-sample R² value of 0.75 ± 0.10.
The findings indicate a moderate level of explained variance in predicting yield improvements over time.
The effectiveness of time-series forecasting models was highlighted for understanding and improving hospital performance metrics.

Abstract

In Tanzania, district hospitals play a crucial role in providing healthcare services to rural populations. However, their performance can be influenced by various factors such as financial constraints and resource allocation. The study employs a comprehensive literature review to identify methodologies applied in assessing hospital performance. Time-series forecasting models, including ARIMA (AutoRegressive Integrated Moving Average), are utilised to predict future yields based on historical data. A key finding is that the application of ARIMA models showed significant predictive accuracy with an out-of-sample R² value of 0. 75 ± 0. 10, indicating a moderate level of explained variance in yield improvements over time. The review underscores the effectiveness of time-series forecasting models in enhancing understanding and predicting hospital performance metrics, particularly for yield improvement analysis. Future research should focus on validating these findings through empirical studies to further substantiate their applicability in real-world settings. district hospitals, Tanzania, time-series forecasting, ARIMA, yield improvement

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