The Potential of Big Data Research in HealthCare for Medical Doctors’ Learning

Abstract

The main goal of this article is to identify the main dimensions of a model proposal for increasing the potential of big data research in Healthcare for medical doctors’ (MDs’) learning, which appears as a major issue in continuous medical education and learning. The paper employs a systematic literature review of main scientific databases (PubMed and Google Scholar), using the VOSviewer software tool, which enables the visualization of scientific landscapes. The analysis includes a co-authorship data analysis as well as the co-occurrence of terms and keywords. The results lead to the construction of the learning model proposed, which includes four health big data key areas for MDs’ learning: 1) data transformation is related to the learning that occurs through medical systems; 2) health intelligence includes the learning regarding health innovation based on predictions and forecasting processes; 3) data leveraging regards the learning about patient information; and 4) the learning process is related to clinical decision-making, focused on disease diagnosis and methods to improve treatments. Practical models gathered from the scientific databases can boost the learning process and revolutionise the medical industry, as they store the most recent knowledge and innovative research.

Contributors

Manuel Au-Yong-Oliveira:

ORCID: http://orcid.org/0000-0002-2154-6171

[e-mail]

Antonio Pesqueira: [e-mail]

Maria José Sousa: [e-mail]

Francesca Dal Mas: [e-mail]

Mohammad Soliman: [e-mail]

Journal

Journal ID (nlm-ta): J Med Syst

Journal ID (iso-abbrev): J Med Syst

Title: Journal of Medical Systems

Publisher: Springer US (New York )

ISSN (Print): 0148-5598

ISSN (Electronic): 1573-689X

Publication date (Electronic): 7 January 2021

Publication date (Print): 2021

Volume: 45

Issue: 1

Affiliations

[1 ]GRID grid.7311.4, ISNI 0000000123236065, INESC TEC, GOVCOPP, Department of Economics, Management, Industrial Engineering and Tourism, , University of Aveiro, ; Aveiro, Portugal

[2 ]GRID grid.481585.5, ISNI 0000 0004 0392 8189, Bavarian Nordic A/S, ; Hellerup, Denmark

[3 ]GRID grid.45349.3f, ISNI 0000 0001 2220 8863, ISCTE Instituto Universitário de Lisboa, ; Lisbon, Portugal

[4 ]GRID grid.36511.30, ISNI 0000 0004 0420 4262, Lincoln International Business School, , University of Lincoln, ; Lincoln, UK

[5 ]University of Technology and Applied Sciences, Salalah CAS, Salalah, Oman

[6 ]GRID grid.411170.2, ISNI 0000 0004 0412 4537, Faculty of Tourism & Hotels, , Fayoum University, ; Fayoum, Egypt

Article

Publisher ID: 1691

DOI: 10.1007/s10916-020-01691-7

PMC ID: 7787883

SO-VID: 6071ec2c-5ad7-497f-a02c-69bf527d88ca

Copyright statement: © The Author(s), under exclusive licence to Springer Science+Business Media, LLC part of Springer Nature 2021

License:

This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.

Categories

Subject: Education & Training

Custom metadata

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