The Data is Flowing: How to Turn the New Interoperability Rules into a Risk Adjustment Superpower

For years, the biggest challenge in risk adjustment was data scarcity. Critical patient information was locked away in siloed systems, trapped in faxes, or simply unavailable. Thanks to new federal interoperability rules taking full effect, that era is officially over. The challenge of 2025 and beyond is no longer data scarcity; it's data overload.

Patient data is now flowing from other health systems, specialists, and hospitals like never before. While this presents an incredible opportunity to build a truly complete patient picture, it also creates a massive new problem: how do you drink from the firehose without drowning?

A folder full of a thousand new PDFs for your coding team isn't insight—it's noise. The key isn't just to receive more data, but to have the right technology to instantly tame the data chaos and unify these fragmented records.

From a Puzzle to a Panorama

The new wave of interoperable data means that for any given patient, you might now have:

• Primary care notes from your own EHR.
• A hospital discharge summary from a recent admission.
• Consult notes from three different specialists, all in different formats.
• A year's worth of lab results from an external provider.

Manually piecing this together is impossible at scale. But for an AI platform designed for this reality, it's the key to unlocking a panoramic view of patient health. This is the critical first step. Before any analysis can happen, you need an intelligent engine that can ingest, digitize, and unify every piece of structured and unstructured data into a single, coherent patient story.

Finding the Signal in the Noise

Once the data is unified, the real work begins. With a complete, longitudinal record, a clinically-trained AI can connect dots that would be invisible to even the most diligent human reviewer.

Imagine the platform automatically analyzing a newly received cardiologist's report alongside your PCP's notes and a recent medication list. It can instantly identify the specific clinical indicators—like a low ejection fraction—that support a more accurate, high-value cardiovascular HCC. This is how you can go beyond diabetes to uncover complex cardiovascular codes that were previously missed.

This is the superpower that interoperability promises. It’s the ability to see everything, understand the connections, and present a clear, evidence-backed opportunity to your expert coders. The AI does the exhaustive work of finding the signal in the noise, allowing your team to focus on validation.

The future of risk adjustment belongs to the organizations that can master this new data-rich environment. The interoperability rules have opened the floodgates; an AI-powered platform is what turns that flood into a strategic river of revenue and insight.

*Don't just receive data—master it. Schedule a demo to see how MedChartScan can turn interoperability into your competitive advantage._