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

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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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