Measuring cognitively demanding activities in pediatric out-of-hospital cardiac arrest

Advances in Simulation

Methodological Intersections

Matthew Hansen¹  Jonathan Ivankovic²  Nathan Bahr²  Jeanne-Marie Guise³  Garth Meckler⁴  Carl Eriksson⁵ 

[1] Department of Emergency Medicine, Oregon Health and Science University, 3181 SW Sam Jackson Park Rd, HRC 11D01, 97239, Portland, OR, USA;Department of Obstetrics and Gynecology, Oregon Health and Science University, 3181 SW Sam Jackson Park Rd, L-466, 97239, Portland, OR, USA;Department of Obstetrics, Gynecology, and Reproductive Biology, Beth Israel Deaconess Medical Center and Harvard Medical School, East Campus, Kirstein 3Rd Floor, OBGYN, 330 Brookline Ave, 02215, Boston, MA, USA;Department of Pediatric Emergency Medicine, University of British Columbia, 24-1160 Nicola Street, V6G 2E5, Vancouver, BC, Canada;Department of Pediatrics, University of British Columbia, V6G 2E5, Vancouver, Canada;Department of Pediatrics, Oregon Health and Science University, 3181 SW Sam Jackson Park Rd, CDRC 1231, 97239, Portland, OR, USA;

关键词: Simulation;    Pediatric out-of-hospital cardiac arrest;    Emergency medical services;    Cognitive load;    Functional near-infrared spectroscopy;   

DOI  :  10.1186/s41077-023-00253-4

 received in 2022-10-04, accepted in 2023-05-03,  发布年份 2023

来源: Springer

【 摘 要 】

BackgroundThis methodological intersection article demonstrates a method to measure cognitive load in clinical simulations. Researchers have hypothesized that high levels of cognitive load reduce performance and increase errors. This phenomenon has been studied primarily by experimental designs that measure responses to predetermined stimuli and self-reports that reduce the experience to a summative value. Our goal was to develop a method to identify clinical activities with high cognitive burden using physiologic measures.MethodsTeams of emergency medical responders were recruited from local fire departments to participate in a scenario with a shockable pediatric out-of-hospital cardiac arrest (POHCA) patient. The scenario was standardized with the patient being resuscitated after receiving high-quality CPR and 3 defibrillations. Each team had a person in charge (PIC) who wore a functional near-infrared spectroscopy (fNIRS) device that recorded changes in oxygenated and deoxygenated hemoglobin concentration in their prefrontal cortex (PFC), which was interpreted as cognitive activity.We developed a data processing pipeline to remove nonneural noise (e.g., motion artifacts, heart rate, respiration, and blood pressure) and detect statistically significant changes in cognitive activity. Two researchers independently watched videos and coded clinical tasks corresponding to detected events. Disagreements were resolved through consensus, and results were validated by clinicians.ResultsWe conducted 18 simulations with 122 participants. Participants arrived in teams of 4 to 7 members, including one PIC. We recorded the PIC’s fNIRS signals and identified 173 events associated with increased cognitive activity. [Defibrillation] (N = 34); [medication] dosing (N = 33); and [rhythm checks] (N = 28) coincided most frequently with detected elevations in cognitive activity. [Defibrillations] had affinity with the right PFC, while [medication] dosing and [rhythm checks] had affinity with the left PFC.ConclusionsFNIRS is a promising tool for physiologically measuring cognitive load. We describe a novel approach to scan the signal for statistically significant events with no a priori assumptions of when they occur. The events corresponded to key resuscitation tasks and appeared to be specific to the type of task based on activated regions in the PFC. Identifying and understanding the clinical tasks that require high cognitive load can suggest targets for interventions to decrease cognitive load and errors in care.

【 授权许可】

CC BY   
© The Author(s) 2023

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