Objectives: We describe an automated transcription system that addresses many documentation problems and fits within scheduled clinical hours.
Materials and methods: During visits, the provider listens to the patient while maintaining eye contact and making brief notes on paper. Immediately after the visit conclusion and before the next, the provider makes a short voice recording on a smartphone which is transmitted to the system. The system uses a public domain general language model, and a hypertuned provider-specific language model that is iteratively refined as each produced note is edited by the physician, followed by final automated processing steps to add any templated text to the note.
Results: The provider leaves the clinic having completed all voice files, median duration 3.4 minutes. Created notes are formatted as preferred and are a median of 363 words (range 125-1175).
Discussion: This approach permits documentation to occur almost entirely within scheduled clinic hours, without copy-forward errors, and without interference with patient-provider interaction.
Conclusion: Though no documentation method is likely to appeal to all, this approach may appeal to many physicians and avoid many current problems with documentation.
Keywords: documentation; electronic health records; physicians.
© The Author(s) 2023. Published by Oxford University Press on behalf of the American Medical Informatics Association.