End-to-End Evaluation and Governance of an EHR-Embedded AI Agent for Clinicians
Clinical AI systems require not just point-in-time evaluation but continuous governance: the ongoing practice of monitoring, evaluating, iterating, and re-evaluating performance throughout deployment. We present an end-to-end framework of governance that integrates rubric validation, live deployment feedback, technical performance monitoring, and cost tracking, with controlled experimentation gating system changes before deployment. Applied to Hyperscribe, an EHR-embedded agent that converts amb
Record details
Published: 30 April 2026
Source: arXiv
Category: Research
Topics: Regulation · Privacy · Healthcare · Agents & autonomy
Retrieved: 14 July 2026
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ethics.ai (30 April 2026), “End-to-End Evaluation and Governance of an EHR-Embedded AI Agent for Clinicians,” evidence record 5190, https://ethics.ai/record/5190 (originally published by arXiv).
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