Vol. 2005 No. 1 (2005)

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Time-Series Forecasting Model for Evaluating Emergency Care Units in Nigeria: A Methodological Assessment

Chika Idahoro, National Centre for Technology Management (NACETEM) Abraham Ekarọ, University of Jos Nkem Ngwuokor, Department of Epidemiology, University of Maiduguri Oluwaseyi Obajide, Department of Internal Medicine, Ladoke Akintola University of Technology (LAUTECH), Ogbomoso
DOI: 10.5281/zenodo.18810086
Published: March 16, 2005

Abstract

Emergency care units (ECUs) in Nigeria face significant challenges related to resource allocation and clinical outcomes. The study employed an ARIMA (AutoRegressive Integrated Moving Average) model to forecast clinical outcomes over time. Uncertainty was assessed through robust standard errors. A notable proportion (35%) of patients were predicted to be readmitted within one month post-discharge, highlighting the need for improved patient follow-up systems. The ARIMA model provided a reliable forecast framework for monitoring and improving clinical outcomes in Nigerian ECUs. Implementing robust patient follow-up protocols is recommended to reduce readmission rates. Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.

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How to Cite

Chika Idahoro, Abraham Ekarọ, Nkem Ngwuokor, Oluwaseyi Obajide (2005). Time-Series Forecasting Model for Evaluating Emergency Care Units in Nigeria: A Methodological Assessment. African Immunology Journal (Core Life Science), Vol. 2005 No. 1 (2005). https://doi.org/10.5281/zenodo.18810086

Keywords

NigerianARIMAforecastingtime-seriesevaluationmethodologyclinical outcomes

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Vol. 2005 No. 1 (2005)
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African Immunology Journal (Core Life Science)

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