An automated medical scribe for documenting clinical encounters

Gregory Finley, Erik Edwards, Amanda Robinson, Michael Brenndoerfer, Najmeh Sadoughi, James Fone, Nico Axtmann, Mark Miller, David Suendermann-Oeft

Abstract
A medical scribe is a clinical professional who charts patient–physician encounters in real time, relieving physicians of most of their administrative burden and substantially increasing productivity and job satisfaction. We present a complete implementation of an automated medical scribe. Our system can serve either as a scalable, standardized, and economical alternative to human scribes; or as an assistive tool for them, providing a first draft of a report along with a convenient means to modify it. This solution is, to our knowledge, the first automated scribe ever presented and relies upon multiple speech and language technologies, including speaker diarization, medical speech recognition, knowledge extraction, and natural language generation.
Anthology ID:
N18-5003
Volume:
Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Demonstrations
Month:
June
Year:
2018
Address:
New Orleans, Louisiana
Editors:
Yang Liu, Tim Paek, Manasi Patwardhan
Venue:
NAACL
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
11–15
Language:
URL:
https://aclanthology.org/N18-5003
DOI:
10.18653/v1/N18-5003
Bibkey:
Cite (ACL):
Gregory Finley, Erik Edwards, Amanda Robinson, Michael Brenndoerfer, Najmeh Sadoughi, James Fone, Nico Axtmann, Mark Miller, and David Suendermann-Oeft. 2018. An automated medical scribe for documenting clinical encounters. In Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Demonstrations, pages 11–15, New Orleans, Louisiana. Association for Computational Linguistics.
Cite (Informal):
An automated medical scribe for documenting clinical encounters (Finley et al., NAACL 2018)
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PDF:
https://preview.aclanthology.org/nschneid-patch-4/N18-5003.pdf
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