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

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.

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 Exclusion Criteria: * Has not completed a residency training program (i.e., medical intern or resident)