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

Authors :
Quiroz, Juan C
Laranjo, Liliana
Kocaballi, Ahmet Baki
Briatore, Agustina
Berkovsky, Shlomo
Rezazadegan, Dana
Coiera, Enrico
Source :
Health Informatics Journal. Dec2020, Vol. 26 Issue 4, p2906-2914. 9p.
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. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
14604582
Volume :
26
Issue :
4
Database :
Academic Search Index
Journal :
Health Informatics Journal
Publication Type :
Academic Journal
Accession number :
147644444
Full Text :
https://doi.org/10.1177/1460458220951719