A Prospective Randomized Controlled Pilot Simulation Study to Investigate the Effect of Audiovisual Decision Support on Diagnosis and Therapeutic Interventions.

Autor:	Greenberg SB; From the NorthShore University HealthSystem (S.B.G., N.B-I., J.C., C.W., C.G.), Evanston, IL; University of Chicago Pritzker School of Medicine (S.B.G.), Chicago, IL; University of Arizona College of Medicine (S.B.), Tucson, AZ; The Mayo Clinic College of Medicine and Science (T.F.D.), Rochester, MN; and Harvard Medical School (F.S.), Boston, MA., Ben-Isvy N, Cram J, Wang C, Barker S, Dagi TF, Gonzalez C, Shapiro F
Jazyk:	angličtina
Zdroj:	Simulation in healthcare : journal of the Society for Simulation in Healthcare [Simul Healthc] 2024 Oct 01; Vol. 19 (5), pp. 281-286. Date of Electronic Publication: 2023 Sep 21.
DOI:	10.1097/SIH.0000000000000749
Abstrakt:	Introduction: Combining audiovisual decision support during perioperative critical events might enhance provider diagnostic and therapeutic accuracy and efficiency. Methods: This study is a prospective, randomized controlled pilot trial studying the impact of audiovisual decision support on anesthesia professional performance at NorthShore University HealthSystem's high fidelity simulation center. Twenty anesthesia professionals (>2 years of clinical experience in the current role) were randomized to 2 groups (current care model vs. audiovisual assistance) and underwent 3 periprocedural simulation scenarios, where patient deterioration occurs: anaphylaxis, amniotic fluid embolism, and cardiac arrest during dental case. Results: Overall, there was a statistically significant decrease in the mean and median pooled times to diagnosis in both the amniotic fluid embolism and pediatric dental scenarios. There was a statistically significant increase in the number of participants in the intervention group who made diagnosis 3 before the end of the scene ( P = 0.03) in the amniotic fluid embolism case. In the pediatric dental case, there was a statistically significant reduction in the median time to diagnosis 1 and diagnosis 3 in the intervention group versus control ( P = 0.01 and P = 0.0002). A significant increase in the number of participants in the intervention group versus control made the correct diagnosis 2 before vital sign change 3 ( P = 0.03), and more participants in the intervention group made the correct diagnosis 3 before the end of the scene when compared with control ( P = 0.001). The median time to start intervention 2 during the dental case was statistically significantly greater in the intervention group versus the control ( P = 0.05). All other endpoints were not statistically significant among the 3 simulation scenarios. Six questions were answered by all participants upon immediate completion of the simulation scenarios and revealed that 19 of 20 participants had delivered anesthesia care to patients similar to the 3 simulation scenarios and 18 of 20 participants reported that they would prefer audiovisual assistance to detect abnormalities in vital signs that subsequently provides appropriate diagnostic and therapeutic options. Conclusions: This pilot study suggested some significant improvement in anesthesia professional time to correct diagnosis and completion of identification of the correct diagnosis before the next vital change in the audiovisual cue group versus control, particularly in the outpatient dental case. In addition, the mean and median pooled times to diagnosis were significantly reduced by approximately 1 minute in both evaluated simulation scenarios. The postsimulation survey responses also suggest the desirability of an audiovisual decision support tool among the current anesthesia professional participants. However, overall, there were no significant differences in the time to intervention between groups in all simulation scenarios. Competing Interests: Conflicts of Interest: Steven Greenberg is the current Editor of the Anesthesia Patient Safety Foundation (APSF) and Secretary of the APSF and has received grants from Merck and Cook Medical for research unrelated to the present topic. Noah Ben-Isvy, John Cram, Chi Wang, Candy Gonzalez, and T. Forcht Dagi declare no conflict of interest. Steven Barker serves as the Chief Science Officer of Massimo and director of the Patient Safety Movement Foundation. Fred Shapiro is a consultant for Fresenius-Kabi, USA, and is on the advisory board for GE Healthcare. (Copyright © 2023 Society for Simulation in Healthcare.)
Databáze:	MEDLINE
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