Big Data Analytics in Patient Care During Coronavirus Disease 2019 (COVID-19) Pandemic: A Systematic Review - Andy Andy; Salsabilla Maula Zalfa El-Hamzah; Jadeny Sinatra (Universitas Muhammadiyah Yogyakarta, 2022)
The latest advancements in the field of computational techniques and big data analytics (BDA) are very helpful in dealing with the spread of coronavirus disease 2019 (COVID-19). The objective of this study was to systematically review BDA applications that have been implemented in patient care and the challenges during COVID-19 pandemic. We conducted a literature search in PubMed, Science Direct, Clinical Key, EBSCO, ProQuest, Cochrane Central, Wiley’s Library, and Springer to identify relevant articles published from 2020 to 2022. Studies were included if they reported BDA applications that had been implemented in real-life patient care during COVID-19 pandemic. We identified 14 relevant studies that reported the implementation and evaluation of BDA applications in patient care during COVID-19 pandemic, of which ten adopted an observational design and four adopted an experimental design. The BDA applications targeted various tasks, such as estimate or predict risk score (n=4), diagnosis (n=6), and healthcare decision making (n=4). Regarding the challenges faced, we identified four issues of BDA during COVID-19, such as data governance, economic challenges, big data technology challenges, and security and privacy issues. This review indicates applications of BDA have tremendous potential to bring a lot of advantages, especially in combatting COVID-19 pandemic, despite insufficient evidence to advocate the routine use of patient care BDA.