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

Marissa Tan1, Elham Hatef1,2,3, Delaram Taghipour1

  • 1General Preventive Medicine Residency Program, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States.

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Summary
This summary is machine-generated.

Health organizations use digital data to predict patient outcomes. Integrating social and behavioral determinants of health (SBDH) data presents challenges but offers potential to improve health equity.

Keywords:
health care disparitiesinformation technologypopulation healthsocial determinants of health

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Area of Science:

  • Health Informatics
  • Public Health
  • Health Services Research

Background:

  • Healthcare organizations increasingly leverage digital data for predictive analytics.
  • Growing evidence highlights the impact of social and behavioral determinants of health (SBDH) on health outcomes and healthcare utilization.
  • There's a trend towards incorporating SBDH data into health prediction models.

Purpose of the Study:

  • To review the rationale for integrating SBDH data into healthcare predictive models.
  • To explore the technical, strategic, and ethical challenges associated with this integration.
  • To offer recommendations for overcoming these challenges and realizing the potential of SBDH predictive analytics.

Main Methods:

  • This viewpoint synthesizes current trends and challenges in health informatics.
  • It reviews existing literature and expert perspectives on SBDH data integration.
  • It discusses the implications for healthcare prediction and health equity.

Main Results:

  • Current SBDH-inclusive models have not consistently demonstrated improved predictive accuracy over clinical-only models.
  • Significant technical, strategic, and ethical hurdles impede the effective use of SBDH data.
  • The potential benefits of SBDH predictive analytics for improving health and reducing disparities remain largely unrealized.

Conclusions:

  • Integrating SBDH data into healthcare predictive models is complex.
  • Addressing the identified challenges is crucial for harnessing SBDH analytics to enhance patient care and promote health equity.
  • Further research and strategic planning are needed to optimize the use of SBDH data in healthcare.