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User-driven development of a medical note generation system

Knoll, Tom, Moramarco, Francesco, Korfiatis, Alex Papadopoulos, Young, Rachel, Ruffini, Claudia, Perera, Mark, Perstl, Christian, Reiter, Ehud, Belz, Anya orcid logoORCID: 0000-0002-0552-8096 and Savkov, Aleksandar orcid logoORCID: 0009-0009-6831-5563 (2022) User-driven development of a medical note generation system. In: 20th Annual Conference of the North American Chapter of the Association for Computational Linguistics (NAACL'22), 10-15 July 2022, Seattle, Washington, USA.

Abstract
A growing body of work uses Natural Language Processing (NLP) methods to automatically generate medical notes from audio recordings of doctor-patient consultations. However, there are very few studies on how such systems could be used in clinical practice, how clinicians would adjust to using them, or how system design should be influenced by such considerations. In this paper, we present three rounds of user studies, carried out in the context of developing a medical note generation system. We present, analyse and discuss the participating clinicians’ impressions and views of how the system ought to be adapted to be of value to them. Next, we describe a three-week test run of the system in a live telehealth clinical practice. Major findings include (i) the emergence of five different note-taking behaviours; (ii) the importance of the system generating notes in real time during the consultation; and (iii) the identification of a number of clinical use cases that could prove challenging for automatic note generation systems.
Metadata
Item Type:Conference or Workshop Item (Paper)
Event Type:Conference
Refereed:Yes
Subjects:Computer Science > Computational linguistics
DCU Faculties and Centres:DCU Faculties and Schools > Faculty of Engineering and Computing > School of Computing
Research Initiatives and Centres > ADAPT
Published in: Carpuat, Marine, de Marneffe, Marie-Catherine and Meza Ruiz, Ivan Vladimir, (eds.) Proceedings of the 20th Annual Conference of the North American Chapter of the Association for Computational Linguistics (NAACL'22). . Association for Computational Linguistics (ACL).
Publisher:Association for Computational Linguistics (ACL)
Copyright Information:© 2022 ACL
ID Code:28646
Deposited On:05 Jul 2023 15:46 by Anya Belz . Last Modified 06 Jul 2023 12:17
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