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

• Main Authors: Ik-Whan G. Kwon, Sung-Ho Kim, David Martin
• Format: Article
• Language: English
• Published: MDPI AG 2021-05-01
• Series: International Journal of Environmental Research and Public Health
• Subjects: social determinants of health; precision medicine; AI; machine learning; digital transformation; population health
• Online Access: https://www.mdpi.com/1660-4601/18/9/5018

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.