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Related Experiment Video

Updated: Jul 5, 2025

Author Spotlight: Evaluating Clinicians' Adoption of Ultrasound-Guided Vascular Cannulation Through Simulation Training
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Using Clinical Simulation to Evaluate AI-Enabled Decision Support.

David Lyell1, Adriaan Lustig2, Kate Denyer2

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Clinical simulation offers a safe and controlled method for evaluating artificial intelligence (AI) clinical decision support (CDS). This approach assesses AI

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Area of Science:

  • Medical Informatics
  • Artificial Intelligence in Healthcare
  • Clinical Decision Support Systems

Background:

  • Evaluating artificial intelligence (AI)-enabled clinical decision support (CDS) in real-world clinical settings presents significant ethical and logistical challenges.
  • Traditional clinical studies for CDS evaluation are often limited by patient risk, experimental control, and cost.

Purpose of the Study:

  • To explore the utility of clinical simulation as a robust methodology for evaluating AI-enabled CDS.
  • To demonstrate the feasibility of using simulation studies for assessing the impact of CDS on clinical decision-making.

Main Methods:

  • The study discusses the principles and advantages of employing clinical simulation for CDS evaluation.
  • A case study is presented to illustrate the practical application and feasibility of this simulation-based approach.

Main Results:

  • Clinical simulation provides a patient- and risk-free environment for rigorous evaluation of CDS.
  • It allows for greater experimental control compared to traditional clinical studies, enabling precise measurement of outcomes.

Conclusions:

  • Clinical simulation is a valuable and feasible method for evaluating AI-enabled CDS.
  • Simulation studies can effectively assess the impact of CDS on downstream clinical decisions and actions within the information value chain.