JMIR Publications

ABSTRACT

In an era of accelerating health information technology capability, healthcare organizations increasingly use digital data to predict outcomes such as emergency department use, hospitalizations, and healthcare costs. This trend occurs alongside a growing recognition that social and behavioral determinants of health (SBDH) influence health and medical care use. Not surprisingly, health providers and insurers are starting to incorporate new SBDH data sources into a wide range of healthcare prediction models. In this article, we review the rationale behind the push to integrate SBDH data into healthcare predictive models. We also explore the technical, strategic, and ethical challenges faced as this process unfolds across the nation. We then offer several recommendations to overcome these challenges in order to reach the promise of SBDH predictive analytics to improve health and decrease healthcare disparities.