In:
JMIR Medical Informatics, JMIR Publications Inc., Vol. 8, No. 9 ( 2020-9-8), p. e18084-
Abstract:
In an era of accelerated health information technology capability, health care organizations increasingly use digital data to predict outcomes such as emergency department use, hospitalizations, and health care costs. This trend occurs alongside a growing recognition that social and behavioral determinants of health (SBDH) influence health and medical care use. Consequently, health providers and insurers are starting to incorporate new SBDH data sources into a wide range of health care prediction models, although existing models that use SBDH variables have not been shown to improve health care predictions more than models that use exclusively clinical variables. In this viewpoint, we review the rationale behind the push to integrate SBDH data into health care predictive models and explore the technical, strategic, and ethical challenges faced as this process unfolds across the United States. We also offer several recommendations to overcome these challenges to reach the promise of SBDH predictive analytics to improve health and reduce health care disparities.
Type of Medium:
Online Resource
ISSN:
2291-9694
Language:
English
Publisher:
JMIR Publications Inc.
Publication Date:
2020
detail.hit.zdb_id:
2798261-0
