Forecasting Outpatient Visits At Marimanti Level 4 Hospital: Time Series Analysis Using Sarima Model

The outpatient department (OPD) is the first point of contact in all hospitals, and patients create opinions about the hospital based on the quality of service they receive at OPD. The purpose of the study is to develop a Statistical model to forecast outpatient attendance at Marimanti Level 4 Hospital using SARIMA modeling. Monthly outpatient visits data obtained from Marimanti level 4 hospital (from January, 2013 to December, 2023) was used in the study. R and R Studio software were used for data analysis. The study employed the Box-Jenkins technique in modelling. The model that minimized the Information criteria was deemed the most plausible among a set of competing models. SARIMA (0,1,2) (2,1,1)12 was the best model (AIC = 1139.56, BIC = 1154.52). The forecasting accuracy of the model was evaluated using the MAPE = 1.66% and MASE = 0.47%. Generally, the 2 years ahead forecast showed an increasing trend. Therefore, the hospital Management ought to take into consideration the forecasts to enable them prepare adequately in terms of resource allocation and planning purposes.

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Publication Details

Journal
IOSR Journal of Mathematics
Published
2024-10-01
DOI
https://doi.org/10.9790/0661-2005013543
Primary Topic
Forecasting Techniques and Applications
Type
article
Field-Weighted Citation Impact
0.00

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article

Forecasting Outpatient Visits At Marimanti Level 4 Hospital: Time Series Analysis Using Sarima Model

Daniel Mwangi, Dennis K. Muriithi, Kenneth Kipchoge Rono
IOSR Journal of Mathematics
Forecasting Techniques and Applications
article

Forecasting Outpatient Visits At Marimanti Level 4 Hospital: Time Series Analysis Using Sarima Model

Daniel Mwangi, Dennis K. Muriithi, Kenneth Kipchoge Rono
article en

Abstract

The outpatient department (OPD) is the first point of contact in all hospitals, and patients create opinions about the hospital based on the quality of service they receive at OPD. The purpose of the study is to develop a Statistical model to forecast outpatient attendance at Marimanti Level 4 Hospital using SARIMA modeling. Monthly outpatient visits data obtained from Marimanti level 4 hospital (from January, 2013 to December, 2023) was used in the study. R and R Studio software were used for data analysis. The study employed the Box-Jenkins technique in modelling. The model that minimized the Information criteria was deemed the most plausible among a set of competing models. SARIMA (0,1,2) (2,1,1)12 was the best model (AIC = 1139.56, BIC = 1154.52). The forecasting accuracy of the model was evaluated using the MAPE = 1.66% and MASE = 0.47%. Generally, the 2 years ahead forecast showed an increasing trend. Therefore, the hospital Management ought to take into consideration the forecasts to enable them prepare adequately in terms of resource allocation and planning purposes.

IOSR Journal of MathematicsVol. 20(5)
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Openalex Percentile: Top 77%
Forecasting Techniques and Applications
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Forecasting Outpatient Visits At Marimanti Level 4 Hospital: Time Series Analysis Using Sarima Model — Daniel Mwangi, Dennis K. Muriithi, et al. · IOSR Journal of Mathematics (2024) | TGRS Research Map | TGRS