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A Prospective Randomized Controlled Simulation Study to Test a Proof-of-Concept Real-Time Periprocedural Decision
Anthony Dinkel1, Justin Talluto, Vikranth Chinthareddy
1Department of Anesthesiology, Massachusetts Eye and Ear Infirmary, Harvard Medical School, Boston, MA.
Journal of Patient Safety
|August 3, 2026
Summary
Audio-visual decision support systems can improve diagnostic accuracy and efficiency for anesthesiology trainees during simulated patient emergencies. This technology shows promise for enhancing patient safety and training in perioperative care.
Area of Science:
- Anesthesiology
- Medical Simulation
- Decision Support Systems
Background:
- Perioperative patient deterioration requires timely diagnosis and intervention.
- Existing decision support systems for anesthesiology are limited.
- Audio-visual cues may enhance provider performance in critical scenarios.
Purpose of the Study:
- To evaluate the impact of audio-visual decision support on anesthesiology trainees' diagnostic accuracy and efficiency.
- To assess the effectiveness of a realistic operating room simulation environment.
- To measure the ability of trainees to diagnose and treat simulated patient deterioration using audio-visual cues.
Main Methods:
- Prospective, randomized controlled pilot trial involving 21 anesthesiology trainees.
- Participants were randomized into standard of care (control) or audio-visual cue (experimental) groups.
- Three simulated patient deterioration scenarios (anaphylaxis, amniotic fluid embolism, pulseless electrical activity) were utilized.
Main Results:
- The audio-visual group showed a statistically significant increase in correct intervention for anaphylaxis (P=0.0015).
- For AFE, the intervention group had a decreased median time to intervention 1 for residents (P=0.01) but increased for student nurse anesthetists (P=0.01).
- Correct diagnoses for the pediatric dental scenario were significantly higher in the intervention group (P=0.005, P=0.023).
Conclusions:
- Real-time audio-visual cues in simulated settings can improve diagnosis and treatment times.
- This simulation-based approach is an effective educational tool for anesthesiology trainees.
- Further development of decision support technology can enhance safety in periprocedural care.

