Are You Missing Hidden Risk in Your Population Health Strategy?

Your EHR system only shows part of the picture. To truly improve health outcomes and deliver more cost-effective care, healthcare providers need to account for what happens outside the clinic walls—social conditions, environmental risks, and behavioral patterns that shape long-term health.

That’s where external data comes in.

By integrating third-party data into your population health strategy, you can predict risks earlier, allocate resources smarter, and improve outcomes across entire communities.

Why External Data Powers Smarter Population Health

✅ Identify at-risk groups using environmental and social determinant data
✅ Improve care management and patient engagement across underserved populations
✅ Target interventions more efficiently to reduce readmissions and chronic care costs
✅ Monitor health trends using real-time sentiment and behavioral signals

How It Works

🔹 Train predictive models on both clinical and non-clinical factors
🔹 Use cluster analysis to segment high-risk patients based on shared social and behavioral traits
🔹 Apply time-series analysis to forecast disease events and demand spikes
🔹 Analyze social media with NLP to understand public health sentiment and concerns

Real-World Impact: Scaling with Real-World Data

Cerner’s population health platform integrates public health, genetic, and wearable device data across 100+ U.S. health systems. Their real-world dataset spans over 100 million patients—helping predict disease outbreaks and optimize chronic care programs at scale.

📩 Want to boost your population health outcomes with better data? Talk to Blue Street Data about unlocking external sources that give you the full picture.

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