Prediction of women and Children's hospital outpatient numbers based on the autoregressive integrated moving average model
Objective: To evaluate the predictive value of the autoregressive integrated moving average (ARIMA) product seasonal model for the daily outpatient volume of paediatric internal medicine departments in hospitals. Methods: The daily outpatient volume of paediatric internal medicine recorded by the ho...
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| Format: | Article |
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Elsevier
2023-04-01
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| Series: | Heliyon |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2405844023020522 |
| _version_ | 1797837033621684224 |
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| author | Yan Lin Chaomin Wan Sha Li Shina Xie Yujing Gan YuanHu Lu |
| author_facet | Yan Lin Chaomin Wan Sha Li Shina Xie Yujing Gan YuanHu Lu |
| author_sort | Yan Lin |
| collection | DOAJ |
| description | Objective: To evaluate the predictive value of the autoregressive integrated moving average (ARIMA) product seasonal model for the daily outpatient volume of paediatric internal medicine departments in hospitals. Methods: The daily outpatient volume of paediatric internal medicine recorded by the hospital information system of the Chengdu Women's and Children's Central Hospital from 1 January 2011 to 31 December 2020 was collected. Using the data from 1 January 2011 to 31 December 2019, the seasonal summation ARIMA model of the time product was established by fitting the tseries program in the R-3.6.3 software. The monthly outpatient volume from January to December 2020 was predicted, and the prediction effect was evaluated according to the mean absolute percentage error (MAPE) between the predicted value and the actual value. Results: The outpatient volume of paediatric internal medicine in the hospital from 2011 to 2019 showed an upward trend, with obvious seasonal fluctuations. The optimal model was the ARIMA model ([3,4], 1,2) × (1,1,0) 12, with an Akaike information criterion of 3116.656 and a Bayesian information criterion of 3217.412. The model's residual was a white noise sequence (x2 = 7.56, P = 0.819), and the MAPE between the predicted value and the actual value of the model was 9.56%. Within a 95% confidence interval of the predicted value, the prediction accuracy of the model was high. Conclusion: The ARIMA multiplicative seasonal model established in this study is suitable for the short-term prediction of the outpatient volume. |
| first_indexed | 2024-04-09T15:19:24Z |
| format | Article |
| id | doaj.art-7fe9ec15f1884a67afe9320f05795e6b |
| institution | Directory Open Access Journal |
| issn | 2405-8440 |
| language | English |
| last_indexed | 2024-04-09T15:19:24Z |
| publishDate | 2023-04-01 |
| publisher | Elsevier |
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| series | Heliyon |
| spelling | doaj.art-7fe9ec15f1884a67afe9320f05795e6b2023-04-29T14:51:16ZengElsevierHeliyon2405-84402023-04-0194e14845Prediction of women and Children's hospital outpatient numbers based on the autoregressive integrated moving average modelYan Lin0Chaomin Wan1Sha Li2Shina Xie3Yujing Gan4YuanHu Lu5Outpatient Department, Chengdu Women's and Children's Central Hospital, School of Medicine, University of Electronic Science and Technology of China, Chengdu 610091, ChinaDepartment of Paediatrics, West China Second Hospital, Sichuan University, No. 20, 3rd Section of Renmin South Road, Chengdu 610041, PR China; Key Laboratory of Birth Defects and Related Diseases of Women and Children (Sichuan University), Ministry of Education, Chengdu 610041, PR China; Corresponding author. Department of Paediatrics, West China Second Hospital, Sichuan University, No. 20, 3rd section of Renmin South Road, Chengdu 610041, PR China.Department of Pediatric Rheumatology, Chengdu Women's and Children's Central Hospital, School of Medicine, University of Electronic Science and Technology of China, Chengdu 610091, ChinaSichaun Development Big Data Industry Investment Co., Ltd., Chengdu 610041, ChinaSichuan Development Holding Co., LTD Full-time Director, Chengdu 610041, ChinaDepartment of Information, Chengdu Women's and Children's Central Hospital, School of Medicine, University of Electronic Science and Technology of China, Chengdu 610091, ChinaObjective: To evaluate the predictive value of the autoregressive integrated moving average (ARIMA) product seasonal model for the daily outpatient volume of paediatric internal medicine departments in hospitals. Methods: The daily outpatient volume of paediatric internal medicine recorded by the hospital information system of the Chengdu Women's and Children's Central Hospital from 1 January 2011 to 31 December 2020 was collected. Using the data from 1 January 2011 to 31 December 2019, the seasonal summation ARIMA model of the time product was established by fitting the tseries program in the R-3.6.3 software. The monthly outpatient volume from January to December 2020 was predicted, and the prediction effect was evaluated according to the mean absolute percentage error (MAPE) between the predicted value and the actual value. Results: The outpatient volume of paediatric internal medicine in the hospital from 2011 to 2019 showed an upward trend, with obvious seasonal fluctuations. The optimal model was the ARIMA model ([3,4], 1,2) × (1,1,0) 12, with an Akaike information criterion of 3116.656 and a Bayesian information criterion of 3217.412. The model's residual was a white noise sequence (x2 = 7.56, P = 0.819), and the MAPE between the predicted value and the actual value of the model was 9.56%. Within a 95% confidence interval of the predicted value, the prediction accuracy of the model was high. Conclusion: The ARIMA multiplicative seasonal model established in this study is suitable for the short-term prediction of the outpatient volume.http://www.sciencedirect.com/science/article/pii/S2405844023020522ARIMA modelEffect evaluationForecastMonthly outpatient volumePaediatric internal medicine |
| spellingShingle | Yan Lin Chaomin Wan Sha Li Shina Xie Yujing Gan YuanHu Lu Prediction of women and Children's hospital outpatient numbers based on the autoregressive integrated moving average model Heliyon ARIMA model Effect evaluation Forecast Monthly outpatient volume Paediatric internal medicine |
| title | Prediction of women and Children's hospital outpatient numbers based on the autoregressive integrated moving average model |
| title_full | Prediction of women and Children's hospital outpatient numbers based on the autoregressive integrated moving average model |
| title_fullStr | Prediction of women and Children's hospital outpatient numbers based on the autoregressive integrated moving average model |
| title_full_unstemmed | Prediction of women and Children's hospital outpatient numbers based on the autoregressive integrated moving average model |
| title_short | Prediction of women and Children's hospital outpatient numbers based on the autoregressive integrated moving average model |
| title_sort | prediction of women and children s hospital outpatient numbers based on the autoregressive integrated moving average model |
| topic | ARIMA model Effect evaluation Forecast Monthly outpatient volume Paediatric internal medicine |
| url | http://www.sciencedirect.com/science/article/pii/S2405844023020522 |
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