How Mount Sinai is using AI to unlock social determinant data in the EHR

By now everyone knows how critical social determinants are to population health and chronic care management. But what’s not so obvious is how to make use of that valuable information, especially given most health systems’ reliance on structured electronic health record data for their analytics projects.

Indeed, the challenge of documenting social data in the EHR – and then extracting it for analytics – is one of the main impediments to more progress on that front, said Dr. Jacob Reider, former chief medical officer and deputy national coordinator at ONC – and now CEO of Troy, New York-based Alliance for Better Health, where he’s devoting himself to removing those and other barriers.

“In the medical universe we had ICD, and SNOMED-CT that we would use to capture information,” he explained in a recent Q&A with Healthcare IT News. “We had a reasonably good way of representing the fact that a patient had diabetes, using a certain coding system.”

On the other hand, “we don’t have a very good consistent, predictable, repeatable mechanism for expressing that somebody has food insecurity needs,” he explained. “Or is a domestic violence victim. Or has a behavior health challenge that makes it difficult to leave the house. Or that they have transportation challenges. We don’t have good ways of representing those things.”