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

Study Results

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

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Recruitment Status

ENROLLING_BY_INVITATION

Clinical Phase

NA

Total Enrollment

350 participants

Study Classification

INTERVENTIONAL

Study Start Date

2025-12-05

Study Completion Date

2026-01-31

Brief Summary

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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.

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Detailed Description

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Conditions

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Sepsis Acute Respiratory Distress Syndrome (ARDS)

Study Design

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Allocation Method

RANDOMIZED

Intervention Model

PARALLEL

Participants will review a series of clinical vignettes. Each vignette will be randomized to show a treatment recommendation either from an artificial intelligence-based clinical decision support system (AI CDSS) or from the clinician in the case, reflecting actual clinical practice. Vignettes will be randomized equally, and participants will see an equal number of vignettes from each arm.

Primary Study Purpose

HEALTH_SERVICES_RESEARCH

Blinding Strategy

SINGLE

Participants

Study Groups

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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.

Group Type EXPERIMENTAL

Artifical Intelligence-Generated Treatment Recommendations

Intervention Type OTHER

The clinical vignette will contain treatment recommendations which were generated by an artificial intelligence-based clinical decision support system.

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.

Group Type NO_INTERVENTION

No interventions assigned to this group

Interventions

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Artifical Intelligence-Generated Treatment Recommendations

The clinical vignette will contain treatment recommendations which were generated by an artificial intelligence-based clinical decision support system.

Intervention Type OTHER

Eligibility Criteria

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Inclusion Criteria

* Working as a physician (i.e., MD, DO) or an advanced practice provider (i.e., nurse practitioner, physician assistant)
* Working at a hospital or medical center in medical critical care, anesthesia critical care, surgical critical care, or emergency medicine