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March 14, 20260 citationsOpen Access

Methodological Evaluation and Time-Series Forecasting of Rural Clinics in Senegal: A Model for Measuring Clinical Outcomes

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MSMamadou Sall

Key Points

  • To evaluate the performance of rural clinics in Senegal and forecast clinical outcomes.
  • Utilized mixed-methods including surveys and observational data collection.
  • Applied time-series analysis with ARIMA models for forecasting.
  • Estimated treatment effects using logistic regression technique.
  • Preliminary ARIMA model indicates a positive trend in patient recovery rates over five years.
  • High variability in recovery rates observed across different clinics.

Abstract

Rural clinics in Senegal face challenges in delivering consistent clinical outcomes due to resource limitations and varying service quality. The study will employ mixed-methods including surveys, observational data collection, and statistical modelling. A time-series analysis with ARIMA (AutoRegressive Integrated Moving Average) models will be applied to forecast future clinical performance. A preliminary ARIMA model suggests a positive trend in patient recovery rates over the past five years, but variability remains high across different clinics. This study provides foundational insights for enhancing rural clinic effectiveness and supports targeted interventions based on identified trends. Implementing continuous quality improvement programmes and leveraging digital health tools can mitigate observed variations. Treatment effect was estimated with logit (pᵢ) =₀+^ Xᵢ, and uncertainty reported using confidence-interval based inference.

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Cite This Study

Mamadou Sall (2013) studied this question.

synapsesocial.com/papers/69b4ba2618185d8a39802c64https://doi.org/10.5281/zenodo.18986922
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