COVID-19'UN BİR DEVLET HASTANESİ ACİL SERVİSİ ÜZERİNDEKİ ETKİSİNİN TAHMİNİ ÜZERİNE BİR ÇALIŞMA

Year 2022, Volume: 9 Issue: 2, 1239 - 1258, 29.07.2022

Fatma Gül Altın , Şeyma Çelik Eroğlu

https://doi.org/10.30798/makuiibf.1033816

Abstract

COVID-19 pandemisi, 2020 yılının ilk çeyreğinden bu yana tüm dünyada insan hayatını ciddi şekilde tehdit etmektedir. Hastaneler bu tehdide karşı ön saflarda savaşmaktadır. Bu çalışmanın amacı, bir devlet hastanesinin aylık acil servis hasta sayısının tahmin edilmesidir. Özellikle COVID-19 pandemisinin acil servis hasta sayısı üzerindeki etkisi incelenmiştir. Analizlerde Ocak 2012- Haziran 2021 (114 ay) dönemine ait veri seti kullanılırken, Box-Jenkins (B-J) ve Gri Tahminleme yaklaşımları için iki farklı veri seti oluşturulmuştur. Daha sonra SARIMA modeli, GM (1,1) ve TGM kullanılarak aylık acil servis hasta sayıları tahmin edilmiştir. Analizlerde SARIMA modeli ile hastanenin acil hasta sayısının uzun dönem trendi incelenirken, GM(1,1) ve TGM ile özellikle COVID-19 dönemine odaklanılmıştır. Elde edilen bulgular, değerlendirme kriterleri açısından en başarılı sonuçlara TGM'nin sahip olduğunu göstermektedir.

Keywords

COVID-19, Acil Servis, SARIMA, GM(1,1), TGM

A STUDY ON FORECASTING THE IMPACT OF COVID-19 ON EMERGENCY SERVICE IN A PUBLIC HOSPITAL

Abstract

The COVID-19 pandemic has seriously threatened human life all over the world since the first quarter of 2020. Hospitals have fought on the frontlines against this threat. The aim of this study is to predict the number of monthly emergency service patients for a public hospital. In particular, the impact of the COVID-19 pandemic on the number of emergency service patients was examined. While the data set for the period January 2012- June 2021 (114 months) is used in the analyses, two different data sets were created for the Box- Jenkins (B-J) and Gray Prediction approaches. Then, the number of monthly emergency service patients was predicted using the SARIMA model, GM (1,1) and TGM. In the analyses, while examining the long-term trend of the number emergency services patients’ using the SARIMA model, GM (1,1) and TGM were used to focus on the COVID-19 period. The findings suggest that the TGM has the most successful results in terms of evaluation criteria.

Keywords

COVID-19, Emergency Service, SARIMA, GM(1,1), TGM

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