AI Copilots for Clinical Documentation to Reduce Physician Burnout
DOI:
https://doi.org/10.56472/WCAI25-115Keywords:
Physician burnout, clinical documentation, large language models (LLMs), artificial intelligence (AI) scribes, speech-to-text, edge-cloud hybrid deployment, EHR integration, evaluation metrics, security, compliance, medical informaticsAbstract
Clinical documentation has become a principal contributor to physician burnout, with research showing that doctors devote more than a third, and sometimes over half, of their professional time to electronic health record (EHR) tasks and associated administrative responsibilities. This paper delves into the deployment of AI Copilot systems based on large language models (LLMs), capable of transforming voice or shorthand physician notes into structured, standards-compliant documentation. The analysis emphasizes edge/cloud hybrid deployment architectures, security and regulatory compliance, integration strategies, and system evaluation metrics. By grounding its exploration in real-world outcomes and consensus guidelines, this paper proposes a comprehensive framework for designing, deploying, and evaluating AI Copilots that reduce documentation burden and physician burnout while preserving clinical safety, accuracy, and trustworthiness
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