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A Metadata Extraction Approach for Clinical Case Reports to Enable Advanced Understanding of Biomedical Concepts
Published on: September 20, 2018
Identifying relevant information in medical conversations to summarize a clinician-patient encounter
Juan C Quiroz, Liliana Laranjo, Ahmet Baki Kocaballi1
1Australian Institute of Health Innovation, Macquarie University, Australia.
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.
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