Introduction
In today’s evolving healthcare ecosystem, understanding a patient’s environment is just as vital as knowing their biology. Real-world evidence (RWE) has played an important role in shaping outcomes and informing clinical and commercial strategies. However, RWE data—often derived from claims or Electronic Health Records (EHRs)—is inherently retrospective and limited in context. Real-time Social Determinants of Health (SDoH) data, particularly when patient-reported, provides a dynamic, forward-looking view of the barriers and conditions influencing care. This white paper explores the distinct advantages of real-time SDoH data over traditional RWE, with examples and messaging frameworks for use across clinical research, market access, and patient support.
1. Timeliness and Responsiveness
RWE, often derived from historical claims or clinical interactions, offers insight into past healthcare utilization but lacks immediacy. Real-time SDoH data captures the current realities patients face—today’s transportation barrier, this week’s food insecurity, or ongoing medication affordability challenges.
“Knowing a patient missed their follow-up due to transportation issues in the past month (RWE) is informative. But knowing they’re going to be unable to reach their provider this week is actionable. Real-time SDoH data gives clinicians the chance to intervene before care gaps widen.”
2. Patient-Reported and Contextualized
Traditional RWE reflects system interactions—what’s billed, coded, or documented. It misses the nuanced, subjective experience of patients. Real-time SDoH data is often collected directly from individuals, revealing socioeconomic stressors, psychosocial barriers, and life conditions that influence health behavior and decisions.
“Claims data may show non-adherence, but it won’t tell you why. Real-time patient reports reveal if it’s due to food insecurity, job loss, or caregiver burden—unlocking the ‘why’ behind the outcome.”
3. Enhanced Equity and Inclusion
RWE tends to overrepresent those with frequent healthcare interactions and underrepresent marginalized or underserved groups. Real-time SDoH collection—
particularly through mobile platforms—enables researchers and clinicians to intentionally include diverse, at-risk populations and address inequities in access and outcomes.
“To address disparities, you must see them. Real-time SDoH data surfaces the lived experiences of underserved groups, enabling pharma, payers, and providers to build interventions that close equity gaps.”
4. Precision Risk Stratification
Traditional RWE is retrospective and often tied to costly utilization events. It may miss early risk indicators. Real-time SDoH enhances predictive models by incorporating upstream factors—economic stress, transportation gaps, housing insecurity—enabling proactive outreach and preventive care.
“EHRs tell you who was hospitalized. Real-time SDoH tells you who’s at risk of being hospitalized next month. This is the difference between retrospective analytics and proactive population health.”
5. Real-World Impact Evaluation
Where RWE often measures outcomes post-intervention, real-time SDoH data allows for adaptive monitoring of social and behavioral shifts as they happen. This is especially valuable in clinical trials, health plan pilots, or public health programs needing rapid feedback loops.
“You don’t need to wait six months to assess program impact. With real-time SDoH inputs, we can monitor how quality of life, financial stress, or support needs change week to week—enabling rapid iteration.”
Conclusion
Real-time SDoH data is a necessary evolution in the shift toward person-centered care. It bridges the gap between clinical insight and lived experience, enabling timely, context-aware interventions. For researchers, life sciences teams, and value-based care organizations, combining real-time SDoH with traditional RWE delivers a fuller, fairer, and more actionable understanding of patient needs.