Dynamic Risk Stratification: Incorporating SDoH, Engagement, & Adherence Data to Predict Holistic and Rising Risk

SDoH Iceberg

In a value-based payment system, payers and at-risk providers utilize risk stratification tools to predict future care demand and cost. Yet, mainstream approaches rely primarily on claims data and medical/condition risk to assess health needs, neglecting other critical data sources.

This paper examines the importance of Social Determinants of Health (SDoH) and adherence/engagement data in generating a more holistic and accurate prediction of actual patient/member risk. It describes methodologies for sourcing both kinds of data, and how such insights can guide decisions around marketing, engagement, care management, and interventions and programs that effectively address social barriers to health even for patients who lack claims history. With this approach, healthcare organizations can develop a more nuanced understanding of patients and populations, and develop offerings that generate better outcomes, lower costs, and higher returns on care management and SDoH investments.

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