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

• Published in: Health informatics journal Vol. 26; no. 4; pp. 2906 - 2914
• Main Authors: Quiroz, Juan C, Laranjo, Liliana, Kocaballi, Ahmet Baki, Briatore, Agustina, Berkovsky, Shlomo, Rezazadegan, Dana, Coiera, Enrico
• Format: Journal Article
• Language: English
• Published: London, England SAGE Publications 01-12-2020; SAGE PUBLICATIONS, INC
• Subjects: Automation; Physician patient relationships; Verbal communication; Automatic summarization; Pareto principle; clinical conversations; digital scribe; natural language processing; GP consultation
• ISSN: 1460-4582; 1741-2811
• DOI: 10.1177/1460458220951719

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.