AI news ·
Abridge partners with NEJM and JAMA Network to expand clinical decision support tool
Abridge is adding New England Journal of Medicine and JAMA Network content to its clinical decision support tool, giving clinicians access to peer-reviewed research during patient care. All answers include source attribution to help verify accuracy.
Abridge Expands AI Clinical Decision Support With Medical Journal Partnerships
Abridge is integrating content from the New England Journal of Medicine and the JAMA Network into its clinical decision support tool, the AI scribe company announced Wednesday. The partnerships will allow clinicians to access peer-reviewed research directly within the platform when searching for medical information or asking questions about patient care.
The tool works before, during, and after patient visits. Providers can query the AI to prepare for appointments, chat with it during visits using patient clinical notes, or consult it afterward. All information delivered to clinicians includes source attribution, showing where answers came from.
"The clinician is in control and is the decision maker, but the access to that information is now presented in a more meaningful and impactful way," said Matt Troup, clinical strategy principal at Abridge.
Growing AI Adoption in Clinical Settings
The move reflects broader physician adoption of AI tools. A Doximity survey published last month found that 35% of physicians use AI to look up recent research for care delivery and decision-making. Nearly 30% use voice-based documentation tools that record clinician-patient conversations and draft clinical notes.
Abridge has offered clinical decision support capabilities for two to three months using content from Wolters Kluwer's UpToDate database. Content from NEJM and JAMA will roll out in the coming months.
About Abridge
Founded in 2018, Abridge works with 250 health systems including Kaiser Permanente, UPMC, and Northwell Health. The company raised two nine-digit funding rounds last year.
Troup said the source attribution serves as a safety measure against hallucinations or misleading information, building clinician trust in the system. The approach keeps clinicians in control of clinical decisions while improving access to current medical evidence.
For healthcare professionals looking to understand how AI for Healthcare is transforming clinical workflows, these tools represent a shift toward evidence-based decision support integrated directly into patient care.