Charting the ethical landscape of generative AI-augmented clinical documentation

Area of Science:

• Medical Informatics
• Artificial Intelligence in Healthcare
• Clinical Documentation

Background:

• Generative artificial intelligence (AI) chatbots, like ChatGPT, present novel clinical applications.
• Their use in clinical documentation is largely underexplored, despite potential to alleviate administrative burdens.

Purpose of the Study:

• To review the potential applications of generative AI chatbots in clinical documentation (e.g., note-writing, handoffs, prior authorizations).
• To examine the ethical considerations associated with AI-generated clinical documentation.

Main Methods:

• Literature review of generative AI applications in clinical settings.
• Analysis of ethical implications, including bias, patient autonomy, and accountability.

Main Results:

• AI can standardize documentation but may embed biases, impacting vulnerable populations and clinical judgment.
• Potential to transform clinician-patient relationships by reducing administrative tasks and enhancing shared decision-making.
• Algorithmic opacity raises concerns regarding error accountability.

Conclusions:

• Proposes strategies: patient notification, mandatory clinician review, and transparency measures (legislation, error reporting).
• Emphasizes equitable deployment through representative data, stakeholder engagement, cultural sensitivity, and enhanced medical education.