Meisam Dastani1, Alireza Atarodi2. 1. Social Determinants of Health Research Center, Gonabad University of Medical Sciences, Gonabad, Iran. 2. Department of Knowledge and Information Science, Paramedical College and Social Development & Health Promotion Research Center,, Gonabad University of Medical Sciences, Gonabad, Iran.
Abstract
Background: Due to the prevalence of the COVID-19 epidemic in all countries of the world, the need to apply health information technology is of great importance. hence, the study has identified the role of health information technology during the period of the COVID-19 epidemic. Methods: The present research is a review study by employing text mining techniques. Therefore, 941 published documents related to health information technology's role during the COVID-19 epidemic were extracted by keyword searching in the Web of Science database. In order to analyze the data and implement the text mining and topic modeling algorithms, Python programming language was applied. Results: The results indicated that the highest number of publications related to the role of health information technology in the period of the COVID-19 epidemic was respectively on the following topics: "Models and smart systems," "Telemedicine," "Health care," "Health information technology," "Evidence-based medicine," "Big data and Statistic analysis." Conclusion: Health information technology has been extensively used during the COVID-19 epidemic. Therefore, different communities can apply these technologies, considering the conditions and facilities to manage the COVID-19 epidemic better. This is an Open Access article. Authors own copyright of their articles appearing in the Journal of Public Health Informatics. Readers may copy articles without permission of the copyright owner(s), as long as the author and OJPHI are acknowledged in the copy and the copy is used for educational, not-for-profit purposes.
Background: Due to the prevalence of the COVID-19 epidemic in all countries of the world, the need to apply health information technology is of great importance. hence, the study has identified the role of health information technology during the period of the COVID-19 epidemic. Methods: The present research is a review study by employing text mining techniques. Therefore, 941 published documents related to health information technology's role during the COVID-19 epidemic were extracted by keyword searching in the Web of Science database. In order to analyze the data and implement the text mining and topic modeling algorithms, Python programming language was applied. Results: The results indicated that the highest number of publications related to the role of health information technology in the period of the COVID-19 epidemic was respectively on the following topics: "Models and smart systems," "Telemedicine," "Health care," "Health information technology," "Evidence-based medicine," "Big data and Statistic analysis." Conclusion: Health information technology has been extensively used during the COVID-19 epidemic. Therefore, different communities can apply these technologies, considering the conditions and facilities to manage the COVID-19 epidemic better. This is an Open Access article. Authors own copyright of their articles appearing in the Journal of Public Health Informatics. Readers may copy articles without permission of the copyright owner(s), as long as the author and OJPHI are acknowledged in the copy and the copy is used for educational, not-for-profit purposes.
Entities:
Keywords:
COVID-19; HIT; Health information technology; Text Mining; Topic modeling
Authors: I Sim; P Gorman; R A Greenes; R B Haynes; B Kaplan; H Lehmann; P C Tang Journal: J Am Med Inform Assoc Date: 2001 Nov-Dec Impact factor: 4.497
Authors: Sanjay Sood; Victor Mbarika; Shakhina Jugoo; Reena Dookhy; Charles R Doarn; Nupur Prakash; Ronald C Merrell Journal: Telemed J E Health Date: 2007-10 Impact factor: 3.536
Authors: Felicitas Stoll; Antje Blank; Gerd Mikus; David Czock; Kathrin I Foerster; Simon Hermann; Katja Häußler; Amin Muhareb; Simone Hummler; Johanna Weiss; Jürgen Burhenne; Walter E Haefeli Journal: Trials Date: 2020-06-29 Impact factor: 2.279