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Identifying relevant information in medical conversations to summarize a clinician-patient encounter.

Authors :
Quiroz JC
Laranjo L
Kocaballi AB
Briatore A
Berkovsky S
Rezazadegan D
Coiera E
Source :
Health informatics journal [Health Informatics J] 2020 Dec; Vol. 26 (4), pp. 2906-2914. Date of Electronic Publication: 2020 Aug 29.
Publication Year :
2020

Abstract

To inform the development of automated summarization of clinical conversations, this study sought to estimate the proportion of doctor-patient communication in general practice (GP) consultations used for generating a consultation summary. Two researchers with a medical degree read the transcripts of 44 GP consultations and highlighted the phrases to be used for generating a summary of the consultation. For all consultations, less than 20% of all words in the transcripts were needed for inclusion in the summary. On average, 9.1% of all words in the transcripts, 26.6% of all medical terms, and 27.3% of all speaker turns were highlighted. The results indicate that communication content used for generating a consultation summary makes up a small portion of GP consultations, and automated summarization solutions-such as digital scribes-must focus on identifying the 20% relevant information for automatically generating consultation summaries.

Details

Language :
English
ISSN :
1741-2811
Volume :
26
Issue :
4
Database :
MEDLINE
Journal :
Health informatics journal
Publication Type :
Academic Journal
Accession number :
32865113
Full Text :
https://doi.org/10.1177/1460458220951719