Performance of an Intelligent Messaging Tool for Clinical Communications
This quality improvement study found that SMT reliably categorized patient messages to support improvements in the timely processing of high-acuity messages. The findings suggest that the SMT's practical applicability underscores its relevance to organizations aiming to leverage natural language processing to address message management challenges.
Authors
- Khang Sinh Nguyen (ORCID: https://orcid.org/0000-0001-5171-4140)
- Tianyuan Shao
- Ramez Ethnasios
- S. Lee
- Ronil Synghal
- Kien La
- Ferdinand Justus
- Mason T. Kellogg
- Brett Anwar
- Orlando Lara
- Dinh Nguyen
- Caleb Wang
- Leon Chan
Institutions
- Colorado Permanente Medical Group (US)
Publication Details
- Journal
- JAMA Network Open
- Published
- 2026-01-15
- DOI
- https://doi.org/10.1001/jamanetworkopen.2025.53174
- Primary Topic
- Electronic Health Records Systems
- Type
- article
- Field-Weighted Citation Impact
- 0.00