Usage of Predictive Analytics during COVID-19 Pandemic to Support Administrative Decision Making in Health Care
International Journal of Science and Research (IJSR)

International Journal of Science and Research (IJSR)
www.ijsr.net | Open Access | Fully Refereed | Peer Reviewed International Journal

ISSN: 2319-7064

Research Paper | Information Technology | Malaysia | Volume 10 Issue 1, January 2021

Usage of Predictive Analytics during COVID-19 Pandemic to Support Administrative Decision Making in Health Care

Fatimetou Zahra Mohamed Mahmoud, Noor Azizah Mohamadali

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.

Keywords: Predictive analytics, healthcare, decision making, COVID-19

Edition: Volume 10 Issue 1, January 2021

Pages: 889 - 896

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How to Cite this Article?

Fatimetou Zahra Mohamed Mahmoud, Noor Azizah Mohamadali, "Usage of Predictive Analytics during COVID-19 Pandemic to Support Administrative Decision Making in Health Care", International Journal of Science and Research (IJSR), https://www.ijsr.net/search_index_results_paperid.php?id=SR21111151424, Volume 10 Issue 1, January 2021, 889 - 896

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