Intelligent Clinical Documentation: Harnessing Generative AI for Patient-Centric Clinical Note Generation

Anjanava Biswas, Wrick Talukdar·May 28, 2024

Summary

This paper explores the application of generative AI, particularly NLP and ASR, in automating clinical documentation through SOAP and BIRP note generation. Studies have shown promise in transcribing patient-clinician interactions and using advanced prompting for draft notes, aiming to reduce documentation time, improve quality, and promote patient-centered care. However, ethical considerations, such as maintaining confidentiality and addressing model biases, are crucial. Initial results have highlighted accuracy and reliability issues, necessitating further research and refinement before widespread adoption in healthcare. Research has also examined the use of AI models like Whisper, GPT-3.5, and alternatives for diarization and utterance classification, with varying degrees of success. The paper delves into the challenges and improvements in note generation, including the use of few-shot learning, structured prompts, and the selection of appropriate models like GPT-4 for better performance. While AI holds potential, ongoing efforts address concerns related to data quality, human oversight, and regulatory compliance to ensure responsible implementation in the healthcare sector.

Key findings

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