Leveraging Generative AI for Clinical Documentation and Patient Interaction

Abstract

Generative AI systems, capable of producing coherent, contextually relevant text, images, and other media from prompt inputs, have become increasingly accessible. The potential for Generative AI to improve patient care and clinician efficiency has generated considerable interest in the healthcare sector, focusing on the enhancement of clinical documentation and patient engagement processes. The use of Generative AI in these domains is discussed with a focus on the underlying technology, implementation considerations for healthcare organizations, and case studies demonstrating the effectiveness of Generative AI in real-world deployments. Automated generation of clinical notes based on free-text summaries, unstructured summaries of patient examinations and assessments, or conversational inputs is explored, along with the code-based structuring of free-text notes and the application of standardization templates to ensure compliance. The generation of patient education materials appropriate for health literacy levels and cultural backgrounds, the scheduling of appointments, and the triaging of patient queries using Generative AI are also covered. Ethical considerations especially with respect to data governance and the potential for biased, adversarial, or inaccurate output are flagged throughout, along with the importance of establishing and maintaining high-quality workflows for the use of Generative AI services.

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