Generating SOAP Notes from Doctor-Patient Conversations Using Modular Summarization Techniques

Kundan Krishna, Sopan Khosla, Jeffrey Bigham, Zachary C. Lipton


Abstract
Following each patient visit, physicians draft long semi-structured clinical summaries called SOAP notes. While invaluable to clinicians and researchers, creating digital SOAP notes is burdensome, contributing to physician burnout. In this paper, we introduce the first complete pipelines to leverage deep summarization models to generate these notes based on transcripts of conversations between physicians and patients. After exploring a spectrum of methods across the extractive-abstractive spectrum, we propose Cluster2Sent, an algorithm that (i) extracts important utterances relevant to each summary section; (ii) clusters together related utterances; and then (iii) generates one summary sentence per cluster. Cluster2Sent outperforms its purely abstractive counterpart by 8 ROUGE-1 points, and produces significantly more factual and coherent sentences as assessed by expert human evaluators. For reproducibility, we demonstrate similar benefits on the publicly available AMI dataset. Our results speak to the benefits of structuring summaries into sections and annotating supporting evidence when constructing summarization corpora.
Anthology ID:
2021.acl-long.384
Volume:
Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 1: Long Papers)
Month:
August
Year:
2021
Address:
Online
Editors:
Chengqing Zong, Fei Xia, Wenjie Li, Roberto Navigli
Venues:
ACL | IJCNLP
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
4958–4972
Language:
URL:
https://aclanthology.org/2021.acl-long.384
DOI:
10.18653/v1/2021.acl-long.384
Bibkey:
Cite (ACL):
Kundan Krishna, Sopan Khosla, Jeffrey Bigham, and Zachary C. Lipton. 2021. Generating SOAP Notes from Doctor-Patient Conversations Using Modular Summarization Techniques. In Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 1: Long Papers), pages 4958–4972, Online. Association for Computational Linguistics.
Cite (Informal):
Generating SOAP Notes from Doctor-Patient Conversations Using Modular Summarization Techniques (Krishna et al., ACL-IJCNLP 2021)
Copy Citation:
PDF:
https://aclanthology.org/2021.acl-long.384.pdf
Video:
 https://aclanthology.org/2021.acl-long.384.mp4