Framework for Continuous Governance of EHR-Embedded AI Agent Hyperscribe
A comprehensive framework for the evaluation and governance of clinical AI systems has been introduced, combining rubric validation, real-time feedback during deployment, monitoring of technical performance, and cost analysis with controlled testing. This was applied to Hyperscribe, an agent within EHR that transforms ambient audio into organized chart updates. A group of twenty clinicians developed 1,646 validated rubrics for 823 cases. Seven iterations of Hyperscribe underwent assessment through controlled experiments, with median scores rising from 84% to 95%. Over a three-month period, an analysis of 107 live feedback entries revealed a shift in feedback composition from 79% error reports and 14% positive notes to 30% errors and 45% positives, highlighting the importance of ongoing governance rather than one-time evaluations.
Key facts
- Framework integrates rubric validation, live deployment feedback, technical performance monitoring, and cost tracking.
- Controlled experimentation gates system changes before deployment.
- Applied to Hyperscribe, an EHR-embedded agent for ambient audio to structured chart updates.
- Twenty clinicians authored 1,646 validated rubrics across 823 cases.
- Seven Hyperscribe versions evaluated through controlled experiments.
- Median scores improved from 84% to 95%.
- 107 live feedback entries analyzed over three months.
- Feedback composition shifted from 79% errors and 14% positive to 30% errors and 45% positive.
Entities
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