From Conversation to Standardized Terminology: An <scp>LLM</scp> ‐ <scp>RAG</scp> Approach for Automated Health Problem Identification in Home Healthcare
Automating health problem identification from clinical conversations can improve documentation accuracy, reduce burden, and ensure alignment with standardized frameworks like the Omaha System, enhancing care quality and continuity in home healthcare.
Authors
- Jiyoun Song (ORCID: https://orcid.org/0000-0003-0362-0670)
- Maxim Topaz (ORCID: https://orcid.org/0000-0002-2358-9837)
- Pallavi Gupta (ORCID: https://orcid.org/0000-0002-1588-7113)
- Maryam Zolnoori (ORCID: https://orcid.org/0000-0003-4484-2990)
- Zhihong Zhang (ORCID: https://orcid.org/0000-0002-9948-8936)
Institutions
- Columbia University Irving Medical Center (US)
- Data & Society Research Institute (US)
- Columbia University (US)
- University of Pennsylvania (US)
Publication Details
- Journal
- Journal of Nursing Scholarship
- Published
- 2025-08-10
- DOI
- https://doi.org/10.1111/jnu.70039
- Citations
- 2
- Primary Topic
- Biomedical Text Mining and Ontologies
- Type
- article
- Field-Weighted Citation Impact
- 1.61
Funders
- National Institutes of Health
- National Heart, Lung, and Blood Institute