Mohamed Mahmoud, Fatimetou Zahra and Mohamadali, Noor Azizah (2021) Usage of Predictive Analytics during COVID-19 Pandemic to Support Administrative Decision Making in Health Care. International Journal of Science and Research (IJSR), 10 (1). pp. 889-896. ISSN 2319-7064
PDF
Restricted to Repository staff only Download (340kB) | Request a copy |
Abstract
During the COVID-19 pandemic many researches have been done about the use of predictive analytic systems (PA) to take administrative decisions based on meaningful information and to help in limiting the spread of the virus and to manage hospitals resources to be able to treat the huge number of patients who increase rapidly every day. Research has shown that the usage of PA during COVID-19 pandemic has help in predicting some key indicators for decision making such as the beds allocation, residence time, rate of renewal, maximum daily rate of change. And, it helped the health care provider or hospital management to understand the short-term future demand for the healthcare equipment demand like medicine, ICU, ventilator, and also can get a clear understanding of managing the number of nurses and doctors. The usage of PA during covid-19 pandemic has proved its benefits that it can be widely used in healthcare due to its ability to support the decision making and its usage is not restricted to medical use and decision making.
Item Type: | Article (Journal) |
---|---|
Uncontrolled Keywords: | Predictive analytics, healthcare, decision making, COVID-19 |
Subjects: | T Technology > T Technology (General) T Technology > T Technology (General) > T10.5 Communication of technical information |
Kulliyyahs/Centres/Divisions/Institutes (Can select more than one option. Press CONTROL button): | Kulliyyah of Information and Communication Technology > Department of Information System Kulliyyah of Information and Communication Technology > Department of Information System |
Depositing User: | Mrs Noor Azizah Mohamadali |
Date Deposited: | 31 May 2021 09:17 |
Last Modified: | 31 May 2021 09:17 |
URI: | http://irep.iium.edu.my/id/eprint/90048 |
Actions (login required)
View Item |