LLM-generated serious illness summaries for cancer patients getting hospitalized
Official title: Better Real-time Information on Documentation of Goals of Care for Engagement in Serious Illness Communication (BRIDGE-SIC)
Run by Dana-Farber Cancer Institute · NCT07735442 · Data updated 2026-11-12
This trial tests whether sending an AI-generated serious-illness summary to a patient’s clinicians at hospital admission helps reduce hospital days for adults with solid tumors.
Quick facts
| Study type | Interventional |
|---|---|
| Ages | 18 Years and up |
| Sex | All |
| Enrollment | 600 (estimated) |
| Sponsor | Dana-Farber Cancer Institute Academic / other |
| Drugs / interventions | chemotherapy |
| Locations | 2 sites (Boston, Massachusetts and 1 other locations) |
| Status | Recruiting |
| Started | August 4, 2026 |
| Main results expected | June 30, 2027 |
| Study ends | June 30, 2028 |
| Registry record updated | August 26, 2026 |
| Trial ID | NCT07735442 on ClinicalTrials.gov |
Is this trial a fit for you?
✓Likely a good fit
Adults (18+) with solid tumor cancers admitted to BWH, who have a Dana-Farber Medical Record Number and a predicted 90-day mortality risk of 25% or higher, and admission timing within a defined weekday window.
✕Probably not a fit
Patients with elective admissions or those not meeting the mortality-risk threshold may not benefit from this intervention.
A plain-English reading of the study's rules. Only the study team can confirm whether you qualify.
What this trial studies
This pragmatic, randomized trial enrolls up to 600 adults with solid tumors admitted to Brigham and Women’s Hospital, using a 1:1 randomization to receive a large language model generated SIC summary sent to their care teams or standard care. The primary outcome is days in the hospital over the next 90 days. Enrollment relies on real-time identification and a waiver of consent due to minimal risk. The intervention aims to incorporate patient preferences into care plans by prompting clinicians to reflect these wishes in treatment decisions.
Why it matters
Potential benefit: If successful, patients may experience shorter hospital stays and care aligned with their stated preferences.
How similar studies have gone: Prior work with structured clinician prompts and decision-support tools has shown potential for affecting care planning, though use of AI-generated SIC summaries in this exact setting is exploratory.
Who can join: the full rules
Show full inclusion / exclusion criteria
Inclusion Criteria: * DFCI Patients, defined as patients who have a DFCI medical record number. * Admitted to an inpatient solid tumor medical oncology service at BWH (including beds that are considered to be DFCI beds within BWH) * Age ≥ 18 years * Mortality prediction ≥ 25% * Admitted on a Sunday after 4pm through Friday at 4pm. These time restrictions are necessary for the workflow of this pragmatic pilot trial, as the intervention requires a staff member to send intervention emails during the work week but within \<= approximately 18 hours of admission. Accordingly, we will not enroll patients during holiday time periods (e.g., for a Monday holiday, enrollment would start on Monday at 4pm instead of Sunday at 4pm) or on days where staff absences (e.g., illness) preclude enrollment. Exclusion Criteria: • Patients with elective inpatient admissions (typically for planned administration of chemotherapy or other treatments)
Where it's running
-
Brigham and Women's Hospital
Boston, Massachusetts, United States Recruiting -
Dana Farber Cancer Institute
Boston, Massachusetts, United States Recruiting
Study contacts
- Principal investigator: Alexi Wright, MD,MPH — Dana-Farber Cancer Institute
- Study coordinator: Alexi A Wright, MD, MPH
- Email: alexi_wright@dfci.harvard.edu
- Phone: 6176322334
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How to take part
- Review the eligibility criteria above with your treating physician.
- Check the official listing on ClinicalTrials.gov for the latest contact details and recruitment status.
- Contact the study coordinator or principal investigator to ask for pre-screening. Pre-screening is free and never obligates you to enroll.