Covid-19 Pandemisi ile Sağlık Bilişimi Yardım Masası İş Yükü Arasındaki İlişki

Year 2023, , 855 - 878, 18.09.2023

Mustafa Mahir Ülgü

https://doi.org/10.26745/ahbvuibfd.1315343

Abstract

Covid-19 pandemisinde mevcut bilgi sistemlerinin ne kadar etkilendiğini somutlaştırabilmek ve getirdiği iş yükünü değerlendirebilmek için e-Devlet hizmeti tanımına göre iki grup ele alınmıştır. Birinci grupta Devletten Vatandaşa (G2C) kategorisindeki Merkezi Hekim Randevu Sistemi (MHRS) ve e-Nabız Kişisel Sağlık Kaydı Sistemi (e-Nabız) seçilmiştir. İkinci grupta Devletten Devlete (G2G) kategorisinde bulunan Elektronik Posta Sistemi (e-Posta) ve Elektronik Belge Yönetim Sistemi (EBYS) seçilmiştir.
Veriler, pandemi öncesi (1 Mart 2018 – 28 Şubat 2020) ve pandemi dönemi (1 Nisan 2020- 31 Mart 2022) olmak üzere toplam 48 aylık dönem üzerinden değerlendirilmiştir. Son kullanıcı sayılarındaki her bir aylık dönem sonu son kullanıcı sayılarındaki değişim, bu değişime bağlı olarak mevcut Yardım Masası Sistemi (YMS)’ye ulaşan başvuru sayılarındaki değişim, bu değişimlerin Covid-19 PCR test sayılarına göre test sonuçlarındaki pozitiflik oranı ile etkileşimi analiz edilmiştir. YMS’ye e-Nabız, MHRS ve EBYS hakkında gelen talep sayıları medyanı bakımından pandemi dönemi öncesi ile pandemi dönemi arasında istatistiksel olarak anlamlı bir fark bulunmamış (p>0,05), e-posta için anlamlı bir farklılık bulunmuştur (p>0,05), pandemi döneminde gelen talep sayısı anlamlı derecede daha yüksektir.
YMS’ye gelen e-Nabız, e-Posta ve EBYS hakkındaki talep sayıları ile Covid-19 test sonucu pozitiflik oranı ve dönem içerisinde gelen yeni kullanıcı sayısı arasında istatistiksel olarak anlamlı bir ilişki bulunmamakta iken (p>0,05), toplam kullanıcı sayısı arasında pozitif yönde anlamlı bir ilişki bulunmaktadır. Bu analizde Mann Whitney U testi kullanılmıştır.
MHRS talep sayısı ile Covid-19 test sonucu pozitiflik oranı arasında istatistiksel olarak anlamlı bir ilişki bulunmamakta (p>0,05) iken, dönem içerisinde gelen yeni kullanıcı sayısı ve dönem sonu toplam kullanıcı sayıları arasında istatistiksel olarak anlamlı bir ilişki bulunmuştur. Bu analizde Spearman korelasyon testi kullanılmıştır.

Keywords

Covid-19, Bilgi Sistemi, Yardım Masası

Thanks

Her bakımdan zor olan akademik yayımcılık çalışmalarına gönüllülük esaslı katıldığınız, ilgi ve önerileriniz için şimdiden teşekkür ederim

The Relationship Between the Covid-19 Pandemic and the Health Informatics Help Desk Workload

Abstract

In order to embody how the existing information systems were affected by the COVID-19 pandemic and to evaluate the workload it brought; two groups were discussed in terms of the definition of e-Government service. In the first group, the Central Doctor Appointment System (CDAS) and e-Nabız Personal Health Record System in the category of Government to Citizen (G2C) are selected. In the second group, Electronic Mail System (e-Mail) and Electronic Document Management System (EDMS), which are in the Government to Government (G2G) category, are selected.
The data are evaluated over a total of 48 months, including the pre-pandemic (1 March 2018 – 28 February 2020) and the pandemic period (1 April 2020 - 31 March 2022). The monthly variation in the number of end users and the variation in the number of applications submitted to the current Help Desk System (HDS) with regard to this change, and the interaction of these changes with the rate of positive COVID-19 PCR test results are analyzed. There was no statistically significant difference between the pre-pandemic period and the pandemic period in terms of the median number of requests about e-Nabız, CDAS, and EDMS to HDS (p>0.05), a significant difference was found for e-Mail (p>0,05), the number of requests received during the pandemic period is significantly higher.
While there is no statistically significant relationship between the number of requests for e-Nabız, e-Mail, and EDMS submitted to HDS and the rate of COVID-19 PCR positive test results and the number of new users in the period (p>0.05), there is a positive significant relationship between the total number of users. Mann Whitney U Test was used in this analysis.
While there is no statistically significant relationship between the number of CDAS requests and the COVID-19 test result positivity rate (p>0.05), a statistically significant relationship is found between the number of new users during the period and the total number of users at the end of the period. Spearman Correlation Test was used in this analysis.

Keywords

COVİD-19, Information System, Help Desk

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