Toward Automated Clinical Transcriptions
This addresses physician burnout and care quality issues in healthcare, but it is incremental as it builds on existing speech-to-text and diarization methods.
The paper tackles the problem of high healthcare costs and adverse outcomes from administrative documentation by introducing a secure system for automated clinical transcriptions, achieving promising results on over 40 hours of simulated conversations.
Administrative documentation is a major driver of rising healthcare costs and is linked to adverse outcomes, including physician burnout and diminished quality of care. This paper introduces a secure system that applies recent advancements in speech-to-text transcription and speaker-labeling (diarization) to patient-provider conversations. This system is optimized to produce accurate transcriptions and highlight potential errors to promote rapid human verification, further reducing the necessary manual effort. Applied to over 40 hours of simulated conversations, this system offers a promising foundation for automating clinical transcriptions.