NCT07147023

Brief Summary

The goal of this study is to test the accuracy of Large Language Model-generated serious illness communication (SIC) summaries, the feasibility of delivering the SIC summaries, and to collect perspectives on the SIC summaries from clinicians and participants with cancer. Large Language Models (LLMs) are artificial intelligence programs that can perform various natural language processing tasks.

Trial Health

75
On Track

Trial Health Score

Automated assessment based on enrollment pace, timeline, and geographic reach

Enrollment
60

participants targeted

Target at P25-P50 for not_applicable

Timeline
3mo left

Started Sep 2025

Geographic Reach
1 country

2 active sites

Status
active not recruiting

Health score is calculated from publicly available data and should be used for screening purposes only.

Trial Relationships

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Study Timeline

Key milestones and dates

Study Progress80%
Sep 2025Oct 2026

First Submitted

Initial submission to the registry

August 21, 2025

Completed
7 days until next milestone

First Posted

Study publicly available on registry

August 28, 2025

Completed
18 days until next milestone

Study Start

First participant enrolled

September 15, 2025

Completed
7 months until next milestone

Primary Completion

Last participant's last visit for primary outcome

April 15, 2026

Completed
7 months until next milestone

Study Completion

Last participant's last visit for all outcomes

October 31, 2026

Expected
Last Updated

April 28, 2026

Status Verified

April 1, 2026

Enrollment Period

7 months

First QC Date

August 21, 2025

Last Update Submit

April 27, 2026

Conditions

Keywords

Advanced CancerCancerSerious IllnessEnd of Life Care

Outcome Measures

Primary Outcomes (1)

  • Serious Illness Conversation (SIC) summary accuracy

    Primary outcome: We will assess SIC summary accuracy by reviewing the source documentation for each bullet point of the 5 domains of the SIC summary. The RA will read each bullet point, read the source note for the date cited in the summary and indicate with a 1 (supported) or 0 (not supported) whether the documentation supports the summarized point. If a summarized point is scored as 0, the MPIs will independently review the item and assign a 1 or 0 to indicate whether the unsupported summary could negatively impact patient care. SIC summary accuracy will be determined at the patient level as the proportion of bullet points supported by underlying documentation divided by the total number of bullet points (i.e., a score from 0 to 1). We will determine the average SIC accuracy score across all patients for the study. We will also report the percent of LLM-SIC summary statements that are unsupported and clinically significant and provide qualitative descriptions of these instances.

    1 week

Secondary Outcomes (4)

  • Feasibility (successful delivery of the intervention)

    1 week

  • Clinician Perspectives of Clinical Utility

    1 week

  • Participant Perspectives on Inpatient and Outpatient Clinician Understanding of their Care Preferences and Acceptability of SIC Summaries

    1 week

  • New Documentation of SIC

    1 week

Other Outcomes (6)

  • Length of hospitalization

    1 week

  • Days in the hospital

    90 days

  • Number of hospitalizations

    90 days

  • +3 more other outcomes

Study Arms (2)

Group A: LLM-Generated SIC Summary Email

EXPERIMENTAL

45 participants will be randomized. Participants will have the option of completing a one-time in-person interview with study staff on their perceptions of SIC and the acceptability of LLM-generated summaries of SIC.

Other: LLM SIC Summary Email

Group B: Usual Care

NO INTERVENTION

15 participants will be randomized and will receive standard oncology care. Participants will have the option of completing a one-time in-person interview with study staff on their perceptions of SIC and the acceptability of LLM-generated summaries of SIC.

Interventions

A Large Language Model-based platform is integrated with the Health Vision Platform, a HIPAA-compliant, electronic health record data management system. Real-time summaries of prior SIC with be sent to clinicians caring for participants in the intervention arm. An email will be sent to the inpatient attending and responding clinician encouraging the team to review the SIC summary, discuss care preferences with the patient and ensure care is aligned with preferences and goals. If no SIC documentation is found, the email will instead encourage the outpatient oncologist to share information regarding undocumented SICs that may have occurred, as well as prompt inpatient and outpatient teams to engage the patient in SIC. For patients with no SIC documentation who are still admitted 72 hours later, the RA will send an additional email prompting SIC or asking the clinician to indicate that an SIC is not appropriate. Patients will also receive standard of care.

Group A: LLM-Generated SIC Summary Email

Eligibility Criteria

Age18 Years+
Sexall
Healthy VolunteersNo
Age GroupsAdult (18-64), Older Adult (65+)

You may qualify if:

  • Dana-Farber Cancer Institute participants
  • Admission 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 ≥ 40%
  • Admitted on a Sunday after 4pm, Monday or Tuesday before 4pm. These time restrictions are necessary for the workflow of this pragmatic pilot trial, as an individual will need to send out the intervention emails and interview patients approximately 48-72 hours after admission, both of which need to occur during the work week.

You may not qualify if:

  • Patients with elective inpatient admissions (typically for chemotherapy or other treatments)
  • The clinician fills one of the following roles for the enrolled patient:
  • inpatient attending on the medical oncology team
  • outpatient Dana-Farber medical oncologist

Contact the study team to confirm eligibility.

Sponsors & Collaborators

Study Sites (2)

Brigham and Women's Hospital

Boston, Massachusetts, 02115, United States

Location

Dana-Farber Cancer Institute

Boston, Massachusetts, 02115, United States

Location

MeSH Terms

Conditions

NeoplasmsDeath

Condition Hierarchy (Ancestors)

Pathologic ProcessesPathological Conditions, Signs and Symptoms

Study Officials

  • Christopher Manz, MD

    Dana-Farber Cancer Institute

    PRINCIPAL INVESTIGATOR

Study Design

Study Type
interventional
Phase
not applicable
Allocation
RANDOMIZED
Masking
NONE
Purpose
OTHER
Intervention Model
PARALLEL
Sponsor Type
OTHER
Responsible Party
PRINCIPAL INVESTIGATOR
PI Title
Principal Investigator

Study Record Dates

First Submitted

August 21, 2025

First Posted

August 28, 2025

Study Start

September 15, 2025

Primary Completion

April 15, 2026

Study Completion (Estimated)

October 31, 2026

Last Updated

April 28, 2026

Record last verified: 2026-04

Data Sharing

IPD Sharing
Will share

The Dana-Farber / Harvard Cancer Center encourages and supports the responsible and ethical sharing of data from clinical trials. De-identified participant data from the final research dataset used in the published manuscript may only be shared under the terms of a Data Use Agreement. Requests may be directed to: \[contact information for Sponsor Investigator or designee\]. The protocol and statistical analysis plan will be made available on Clinicaltrials.gov only as required by federal regulation or as a condition of awards and agreements supporting the research.

Shared Documents
STUDY PROTOCOL, SAP
Time Frame
Data can be shared no earlier than 1 year following the date of publication
Access Criteria
Contact the Belfer Office for Dana-Farber Innovations (BODFI) at innovation@dfci.harvard.edu

Locations