Precision Social Medicine: Bridging the Gap Between Social Care and Health Systems Integration

Health systems serving children have increasingly invested in social care initiatives, yet these programs frequently demonstrate inconsistent effectiveness and face challenges in sustainability and scalability. Precision social medicine (PSM) offers a framework for addressing this gap by leveraging artificial intelligence (AI)/machine learning (ML) models to match social care interventions to patients' clinical and social context. This article presents a practical, 3-step approach for operationalizing PSM within health systems serving children. These steps are to (1) codefine precision in social care with patients and frontline staff, (2) translate that definition into an AI/ML-informed strategy for identifying risk and assigning services, and (3) test the approach in workflows before it impacts care. We highlight integrating such a framework using pediatric asthma as a case example, tailored for the pediatric hospitalist managing the transition from hospital to home.