Integrating Social Determinants of Health to Precision Medicine through Digital Transformation: An Exploratory Roadmap

Ik-Whan G. Kwon, Sung-Ho Kim and David Martin
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Ik-Whan G. Kwon: The Center for Supply Chain Excellence, Saint Louis University, Saint Louis, MO 63108, USA
Sung-Ho Kim: Department of Health Administration, Yonsei University, Seoul 03722, Korea
David Martin: The Ancell School of Business, Western Connecticut State University, Danbury, CT 06810, USA

IJERPH, 2021, vol. 18, issue 9, 1-8

Abstract: The COVID-19 pandemic has altered healthcare delivery platforms from traditional face-to-face formats to online care through digital tools. The healthcare industry saw a rapid adoption of digital collaborative tools to provide care to patients, regardless of where patients or clinicians were located, while mitigating the risk of exposure to the coronavirus. Information technologies now allow healthcare providers to continue a high level of care for their patients through virtual visits, and to collaborate with other providers in the networks. Population health can be improved by social determinants of health and precision medicine working together. However, these two health-enhancing constructs work independently, resulting in suboptimal health results. This paper argues that artificial intelligence can provide clinical–community linkage that enhances overall population health. An exploratory roadmap is proposed.

Keywords: social determinants of health; precision medicine; AI; machine learning; digital transformation; population health; clinical–community linkages; digital divide; digital literacy (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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