Harnessing Natural Language Processing to Identify Documentation of Serious Illness Communication for Patients With Decompensated Cirrhosis
NLP is more efficient and as accurate as manual chart review for identifying SIC documentation in the EHR for patients with DC and can be used at scale for quality improvement initiatives and clinical trials.
Authors
- Nneka N. Ufere (ORCID: https://orcid.org/0000-0001-8255-9374)
- Lauren Nephew (ORCID: https://orcid.org/0000-0003-0837-0746)
- Brigitte N. Durieux (ORCID: https://orcid.org/0000-0001-6036-1420)
- Patricia D. Jones (ORCID: https://orcid.org/0000-0003-4189-6731)
- Charlotta Lindvall (ORCID: https://orcid.org/0000-0003-2090-2039)
- Teresa Indriolo
- Joanna Paladino (ORCID: https://orcid.org/0000-0001-9324-1943)
- Angelo E. Volandes
- Areej El‐Jawahri (ORCID: https://orcid.org/0000-0002-3556-1495)
- Kate Sciacca
- Lauren E. Smith (ORCID: https://orcid.org/0000-0001-7666-4792)
- Enya Zhu (ORCID: https://orcid.org/0009-0000-2816-374X)
- A. Liu (ORCID: https://orcid.org/0000-0001-5664-7127)
- Grace Bizup
Institutions
- Brigham and Women's Hospital (US)
- University of Miami (US)
- Duke University (US)
- Palo Alto University (US)
- Massachusetts General Hospital (US)
- Dana-Farber Cancer Institute (US)
- Dartmouth Psychiatric Research Center (US)
- Stanford Medicine (US)
- Indiana University School of Medicine
- Indiana University – Purdue University Indianapolis (US)
- Stanford University (US)
Publication Details
- Journal
- The American Journal of Gastroenterology
- Published
- 2025-11-14
- DOI
- https://doi.org/10.14309/ajg.0000000000003830
- Primary Topic
- Health Literacy and Information Accessibility
- Type
- article
- Field-Weighted Citation Impact
- 0.00