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Including Social and Behavioral Determinants in Predictive Models: Trends, Challenges, and Opportunities

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 deter...

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Detalles Bibliográficos
Autores principales: Tan, Marissa, Hatef, Elham, Taghipour, Delaram, Vyas, Kinjel, Kharrazi, Hadi, Gottlieb, Laura, Weiner, Jonathan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: JMIR Publications 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7509627/
https://www.ncbi.nlm.nih.gov/pubmed/32897240
http://dx.doi.org/10.2196/18084
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author Tan, Marissa
Hatef, Elham
Taghipour, Delaram
Vyas, Kinjel
Kharrazi, Hadi
Gottlieb, Laura
Weiner, Jonathan
author_facet Tan, Marissa
Hatef, Elham
Taghipour, Delaram
Vyas, Kinjel
Kharrazi, Hadi
Gottlieb, Laura
Weiner, Jonathan
author_sort Tan, Marissa
collection PubMed
description 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.
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spelling pubmed-75096272020-10-05 Including Social and Behavioral Determinants in Predictive Models: Trends, Challenges, and Opportunities Tan, Marissa Hatef, Elham Taghipour, Delaram Vyas, Kinjel Kharrazi, Hadi Gottlieb, Laura Weiner, Jonathan JMIR Med Inform Viewpoint 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. JMIR Publications 2020-09-08 /pmc/articles/PMC7509627/ /pubmed/32897240 http://dx.doi.org/10.2196/18084 Text en ©Marissa Tan, Elham Hatef, Delaram Taghipour, Kinjel Vyas, Hadi Kharrazi, Laura Gottlieb, Jonathan Weiner. Originally published in JMIR Medical Informatics (http://medinform.jmir.org), 08.09.2020. https://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR Medical Informatics, is properly cited. The complete bibliographic information, a link to the original publication on http://medinform.jmir.org/, as well as this copyright and license information must be included.
spellingShingle Viewpoint
Tan, Marissa
Hatef, Elham
Taghipour, Delaram
Vyas, Kinjel
Kharrazi, Hadi
Gottlieb, Laura
Weiner, Jonathan
Including Social and Behavioral Determinants in Predictive Models: Trends, Challenges, and Opportunities
title Including Social and Behavioral Determinants in Predictive Models: Trends, Challenges, and Opportunities
title_full Including Social and Behavioral Determinants in Predictive Models: Trends, Challenges, and Opportunities
title_fullStr Including Social and Behavioral Determinants in Predictive Models: Trends, Challenges, and Opportunities
title_full_unstemmed Including Social and Behavioral Determinants in Predictive Models: Trends, Challenges, and Opportunities
title_short Including Social and Behavioral Determinants in Predictive Models: Trends, Challenges, and Opportunities
title_sort including social and behavioral determinants in predictive models: trends, challenges, and opportunities
topic Viewpoint
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7509627/
https://www.ncbi.nlm.nih.gov/pubmed/32897240
http://dx.doi.org/10.2196/18084
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