Study: Social determinants of health data don't enhance predictive models for social service referrals

Integrating social determinants of health data into predictive models doesn't always improve their ability to identify patients in need of social services, according to a study published in the Journal of the American Medical Informatics Association.

For the study, a team of researchers from Indianapolis-based Indiana University developed two decision models to predict whether patients at an unidentified safety-net hospital would need social service referrals, such as mental health, dietitian or social work services. One decision model used clinical data, while the other used clinical data alongside community-level socioeconomic and public health data.

The researchers found both models were able to successfully predict a patient's need for social service referrals with "considerable accuracy."

"While the use of [social determinants of health] did not result in significant performance improvements, our approach represents a novel and important application of risk predictive modeling," the study authors concluded.

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