Evaluating Artificial Intelligence-Based Clinical Decision Support for Sepsis and ARDS

Part of paid clinical trials in Philadelphia, Pennsylvania.

Sponsor
University of Pennsylvania
Study ID
NCT07025096
Status
Enrolling By Invitation

Conditions

  • Acute Respiratory Distress Syndrome (ARDS)
  • Sepsis

Eligibility Criteria

Sex
ALL
Age
18 Years - N/A
Healthy Volunteers
Not accepted

Interventions

  • Artifical Intelligence-Generated Treatment Recommendations — OTHER
    The clinical vignette will contain treatment recommendations which were generated by an artificial intelligence-based clinical decision support system.

Study Details

Sepsis and acute respiratory distress syndrome (ARDS) are common in intensive care units. Managing sepsis and ARDS is inherently complex and requires making numerous decisions under uncertainty. Artificial intelligence (AI) clinical decision support systems (CDSSs) offer a promising approach to support care management for sepsis and ARDS. The goal of this randomized, survey-based study is to compare treatment recommendations enacted by clinicians to those generated by an AI CDSS. The study will investigate whether an AI CDSS can generate treatment recommendations that are safe, appropriate, and indistinguishable to those provided by real clinicians. In this study, participants (i.e., critical care clinicians) will review a series of critical care cases (vignettes) in an electronic survey. Each vignette will contain a de-identified case of a patient with sepsis and ARDS as well as treatment recommendations for the case. Participants will assess the safety and appropriateness of each treatment recommendations and answer whether they think the treatment recommendations came from the clinician or an AI CDSS.

Key Dates

Start date
Dec 5, 2025
Status verified
Feb 2026
Primary completion
May 31, 2026
Completion
May 31, 2026

Study Design

Enrollment
350 participants (estimated)
Allocation
RANDOMIZED
Intervention model
PARALLEL
Primary purpose
HEALTH_SERVICES_RESEARCH

Arms

  • Experimental: Artificial Intelligence
    Critical care cases / vignettes in this arm will contain treatment recommendations generated by an artificial intelligence-based clinical decision support system. Each participant will review four vignettes from this arm.
  • No Intervention: Human Clinician
    Critical care cases / vignettes in this arm will contain treatment recommendations that were enacted by the clinician in the actual case. Each participant will review four vignettes from this arm.

Primary Outcome Measure

Accuracy of Predicting the Source of Treatment Recommendation [ Time Frame: From enrollment to the end of the survey, an average of 45 minutes ]

Locations (1)

FacilityCityStateZIPSite coordinators
University of PennsylvaniaPhiladelphiaPennsylvania19104-

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By research site
University of Pennsylvania· Philadelphia, PA

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