Point-of-Care AI Assistance and Critical Care Outcomes: A Randomized Trial

NCT07293078 | Not Yet Recruiting Phase 1

• 2 other identifiers: POC-AI-ICU-001IRB#2025-067
• Study Type: interventional
• Target: 1,000
• Locations: 1 country
• Sites: 1

Brief Summary

This is a prospective, unmasked, randomized, multicenter clinical trial evaluating the impact of point-of-care large language model (LLM)-based decision support on diagnostic accuracy and clinical outcomes in adult medical intensive care unit (MICU) patients. Consecutive adult ICU admissions at participating community hospitals (initially MetroWest Medical Center and St. Vincent Hospital) will be screened for eligibility. Eligible patients will be randomized 1:1 to standard care or an AI-assisted group. In both arms, initial evaluation and management will follow usual practice. For patients randomized to AI assistance, de-identified admission data (history and physical, labs, imaging reports, and other relevant documentation) will be formatted and submitted to a state-of-the-art LLM (ChatGPT-5) at the time of admission. The AI-generated differential diagnosis and therapeutic recommendations will be provided to the admitting team for consideration. For the standard care arm, LLM output will be generated but not shared with clinicians. After discharge, a masked chart review will determine the "ground truth" primary diagnosis and extract outcomes including: Primary Outcome - a composite of medical errors (from time of ICU admission through day 7 of ICU stay, or ICU discharge, whichever comes first); Secondary Outcomes - 90-day mortality, ICU and hospital length of stay, and ventilator-free days.

Conditions

Critical Illness; Sepsis; Acute Respiratory Failure (ARF); Multi-organ Failure; Acute Kidney Injury; Delirium Confusional State; Shock

Keywords

Critical Care; Intensive Care Unit; Large Language Model; Artificial Intelligence; Diagnostic Accuracy; Clinical Decision Support; Critical Care Outcomes; Sepsis; Shock; Acute Respiratory Failure; Multiorgan Failure

Outcome Measures

Primary Outcomes (1)

• Composite of Medical Errors

  Proportion of patients with at least one clinically important diagnostic or therapeutic error identified by masked chart review (e.g., missed or delayed critical diagnosis, major guideline-discordant therapy with potential for harm).

  From the time of ICU admission through day 7 of ICU stay or ICU discharge, whichever comes first.

Secondary Outcomes (4)

• 90-day All-Cause Mortality

  90 days from ICU admission.

• ICU Length of Stay

  From ICU admission to ICU discharge (up to 90 days).

• Ventilator-Free Days

  Up to 28 days after ICU admission.

• Hospital Length of Stay

  From hospital admission to hospital discharge (up to 90 days).

Study Arms (2)

Standard Care

NO INTERVENTION

Patients receive usual ICU care per local practice. De-identified admission data may be processed and submitted to the LLM for research purposes, but AI output is not shared with treating clinicians and does not influence real-time management.

AI-Assisted Care

OTHER

Patients receive standard ICU care plus point-of-care LLM-based decision support at admission. De-identified admission data are formatted and submitted to an LLM (ChatGPT-5). The model returns a primary diagnosis, ranked differential diagnosis list, suggested additional information, and prioritized therapeutic recommendations. This output is provided to the admitting team for consideration in ongoing management.

Other: Point-of-care large language model decision support (ChatGPT-5)

Interventions

Point-of-care large language model decision support (ChatGPT-5) OTHER

Use of a large language model (ChatGPT-5) to analyze de-identified ICU admission data (history, physical examination, laboratory results, imaging reports, and other documentation) at the time of admission. The model generates diagnostic and therapeutic recommendations that are shared with clinicians in the AI-assisted arm only.

AI-Assisted Care

Eligibility Criteria

• Age: 18 Years+
• Sex: all
• Healthy Volunteers: No
• Age Groups: Adult (18-64), Older Adult (65+)

You may qualify if:

• Adult patients (≥ 18 years) admitted to the medical intensive care unit (MICU) at participating hospitals.
• Direct admissions from the emergency department or transfers from medical wards to the MICU.
• Critically ill patients meeting local ICU admission criteria.

You may not qualify if:

• Transfers to the MICU from outside hospitals, operating room, or post-anesthesia care unit.
• Age \< 18 years.
• Incomplete or missing essential clinical information at admission (e.g., key labs or documentation not yet available).
• Primary surgical or cardiac (e.g., STEMI) patients.
• Pregnant or postpartum women.
• Prisoners.

Sponsors & Collaborators

• MetroWest Artificial Intelligence Research Workgroup: lead

Study Sites (1)

Framingham Union Hospital/MetroWest Medical Center

Framingham, Massachusetts, 01702, United States

Location

Related Publications (1)

• Singh J, Bohra R, Mukhtiar V, Fernandes W, Bhanushali C, Chinnamuthu R, Kanamgode SS, Ellis J, Silverman E. Diagnostic Accuracy of a Large Language Model (ChatGPT-4) for Patients Admitted to a Community Hospital Medical Intensive Care Unit: A Retrospective Case Study. J Intensive Care Med. 2025 Aug 17:8850666251368270. doi: 10.1177/08850666251368270. Online ahead of print.

  PMID: 40820407 BACKGROUND

MeSH Terms

Conditions

Critical Illness; Sepsis; Multiple Organ Failure; Acute Kidney Injury; Confusion; Shock

Condition Hierarchy (Ancestors)

Disease Attributes; Pathologic Processes; Pathological Conditions, Signs and Symptoms; Infections; Systemic Inflammatory Response Syndrome; Inflammation; Renal Insufficiency; Kidney Diseases; Urologic Diseases; Female Urogenital Diseases; Female Urogenital Diseases and Pregnancy Complications; Urogenital Diseases; Male Urogenital Diseases; Neurobehavioral Manifestations; Neurologic Manifestations; Nervous System Diseases; Signs and Symptoms

Study Officials

• Eric Silverman, M.D.

  MetroWest Medical Center and St. Vincent Hospital

  PRINCIPAL INVESTIGATOR

Central Study Contacts

Eric Silverman, M.D. principal Investigator, M.D.

CONTACT

508-344-5680; esilverman@pamw.org

Study Design

• Study Type: interventional
• Phase: phase 1
• Allocation: RANDOMIZED
• Masking: DOUBLE
• Who Masked: PARTICIPANT, OUTCOMES ASSESSOR
• Purpose: TREATMENT
• Intervention Model: PARALLEL
• Sponsor Type: OTHER
• Responsible Party: SPONSOR

Study Record Dates

• First Submitted: November 17, 2025
• First Posted: December 18, 2025
• Study Start: January 1, 2026
• Primary Completion (Estimated): December 31, 2028
• Study Completion (Estimated): June 30, 2029
• Last Updated: December 18, 2025

Record last verified: 2025-12

Data Sharing

• IPD Sharing: Will share
• Shared Documents: STUDY PROTOCOL, SAP, CSR

Locations

US (1)