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Health Information Technology and Healthcare Information System

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Related Experiment Videos

An Artificial Intelligence Oracle for Proactive Population Health Quality Improvement.

Hannah Ratcliffe¹, John Morgan^2,3, Melissa Jacobs⁴

¹Vice President of Care Model and Quality, Waymark, San Francisco, CA, USA.

NEJM Catalyst Innovations in Care Delivery

|July 8, 2026

Summary

This summary is machine-generated.

An artificial intelligence (AI) oracle analyzes clinical notes to identify patient safety risks and preventive care opportunities. This AI system enhances care management for vulnerable populations, improving outpatient safety and fostering a learning health system.

Related Experiment Videos

Area of Science:

Health Informatics
Artificial Intelligence in Healthcare
Community Health

Background:

Patients with complex health needs experience vulnerability between clinical visits, risking unobserved health escalations.
Community-based care management programs aim to mitigate these risks for vulnerable populations, particularly those in Medicaid.
Processing unstructured clinical notes from field teams presents a significant data management challenge for care programs.

Purpose of the Study:

To develop and implement a scalable artificial intelligence (AI) system to analyze unstructured clinical encounter notes.
To proactively identify urgent safety red flags and preventive care opportunities within patient data.
To foster a learning health system by providing strengths-based feedback and transforming care models.

Main Methods:

Development and phased implementation of an AI oracle system for continuous analysis of daily encounter notes.
Integration of the AI oracle with care teams' messaging systems for real-time, actionable alerts.
Iterative refinement of AI prompts based on clinical leadership review to enhance alert accuracy.

Main Results:

The AI oracle successfully synthesizes diverse data streams (observations, pharmacy data, risk scores, HADT feeds) to reveal complex patient risks.
Actionable true-positive rate for safety alerts improved from 68% to over 95% within 12 weeks.
The system transformed a reactive care model into a proactive, learning health system.

Conclusions:

The AI oracle offers a scalable solution for improving outpatient safety among vulnerable populations.
Continuous analysis of clinical notes via AI can mitigate risks and enhance preventive care delivery.
AI integration acts as a digital coach, supporting care teams and optimizing patient outcomes.