AI in medical transcription and documentation: improving clinician efficiency

Author(s)	Srinivasa Kalyan Vangibhurathachhi
Country	United States
Abstract	Healthcare providers spend twice as much time on documentation as direct patient care, contributing to widespread physician burnout affecting 54% of US physicians and labour shortages within the healthcare sector. This article examines AI-powered solutions, including voice recognition and natural language processing, that can revolutionise medical documentation. Medical AI technologies like Dragon Medical One, Amazon Transcribe Medical, and Suki AI are already demonstrating significant potential for reducing documentation burden as well as improving accuracy across hospital, primary care, and telemedicine settings. Despite the obvious benefits, implementation faces challenges including privacy concerns, algorithmic bias, and clinician resistance. With proper attention to transparency, bias mitigation, and regulatory compliance, AI documentation systems can transform healthcare efficiency while preserving essential human-centred care.
Field	Engineering
Published In	Volume 6, Issue 10, October 2025
Published On	2025-10-21
Cite This	AI in medical transcription and documentation: improving clinician efficiency - Srinivasa Kalyan Vangibhurathachhi - IJLRP Volume 6, Issue 10, October 2025. DOI 10.70528/IJLRP.v6.i10.1792
DOI	https://doi.org/10.70528/IJLRP.v6.i10.1792
Short DOI	https://doi.org/g97gjs

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