Adam Cheng1, Frank Overly2, David Kessler3, Vinay M Nadkarni4, Yiqun Lin5, Quynh Doan6, Jonathan P Duff7, Nancy M Tofil8, Farhan Bhanji9, Mark Adler10, Alex Charnovich11, Elizabeth A Hunt12, Linda L Brown13. 1. University of Calgary, KidSim-ASPIRE Research Program, Division of Emergency Medicine, Department of Pediatrics, Alberta Children's Hospital, 2888 Shaganappi Trail NW, Calgary, Alberta, Canada T3B 6A8. Electronic address: chenger@me.com. 2. Hasbro Children's Hospital, Alpert Medical School of Brown University, 593 Eddy St, Providence, RI 02903, USA. Electronic address: foverly@lifespan.org. 3. Columbia University College of Physicians and Surgeons, 630 W 168th St, New York, NY 10032, USA. Electronic address: dk2592@cumc.columbia.edu. 4. The Children's Hospital of Philadelphia, University of Pennsylvania Perelman School of Medicine, 34th Street and Civic Center Boulevard, Philadelphia, PA 19104, USA. Electronic address: nadkarni@chop.edu. 5. KidSIM-ASPIRE Simulation Research Program, Alberta Children's Hospital, University of Calgary, 2888 Shaganappi Trail NW, Calgary, Alberta, Canada T3B 6A8. Electronic address: jeffylin@hotmail.com. 6. British Columbia Children's Hospital, University of British Columbia, 4480 Oak Street, Vancouver, BC, Canada V6H 3V4. Electronic address: qdoan@cw.bc.ca. 7. Stollery Children's Hospital, University of Alberta, 8215 112 St NW, Edmonton, AB, Canada T6G 2L9. Electronic address: jon.duff@albertahealthservices.ca. 8. Children's of Alabama, University of Alabama at Birmingham, 1600 7th Ave, S. Birmingham, AL 35233, USA. Electronic address: ntofil@peds.uab.edu. 9. Montreal Children's Hospital, McGill University, 2300 Tupper St, Montreal, QC, Canada H3H 1P3. Electronic address: farhan.bhanji@mcgill.ca. 10. Ann & Robert H. Lurie Children's Hospital of Chicago, Northwestern University School of Medicine, 225 E Chicago Ave, Chicago, IL 60611, USA. Electronic address: m-adler@northwestern.edu. 11. Johns Hopkins University School of Medicine, 733 N Broadway, Baltimore, MD 21205, USA. Electronic address: echarno1@jhmi.edu. 12. Johns Hopkins University School of Medicine, 733 N Broadway, Baltimore, MD 21205, USA. Electronic address: ehunt@jhmi.edu. 13. Hasbro Children's Hospital, Alpert Medical School of Brown University, 593 Eddy St, Providence, RI 02903, USA. Electronic address: lbrown8@lifespan.org.
Abstract
AIM: Many healthcare providers rely on visual perception to guide cardiopulmonary resuscitation (CPR), but little is known about the accuracy of provider perceptions of CPR quality. We aimed to describe the difference between perceived versus measured CPR quality, and to determine the impact of provider role, real-time visual CPR feedback and Just-in-Time (JIT) CPR training on provider perceptions. METHODS: We conducted secondary analyses of data collected from a prospective, multicenter, randomized trial of 324 healthcare providers who participated in a simulated cardiac arrest scenario between July 2012 and April 2014. Participants were randomized to one of four permutations of: JIT CPR training and real-time visual CPR feedback. We calculated the difference between perceived and measured quality of CPR and reported the proportion of subjects accurately estimating the quality of CPR within each study arm. RESULTS: Participants overestimated achieving adequate chest compression depth (mean difference range: 16.1-60.6%) and rate (range: 0.2-51%), and underestimated chest compression fraction (0.2-2.9%) across all arms. Compared to no intervention, the use of real-time feedback and JIT CPR training (alone or in combination) improved perception of depth (p<0.001). Accurate estimation of CPR quality was poor for chest compression depth (0-13%), rate (5-46%) and chest compression fraction (60-63%). Perception of depth is more accurate in CPR providers versus team leaders (27.8% vs. 7.4%; p=0.043) when using real-time feedback. CONCLUSION: Healthcare providers' visual perception of CPR quality is poor. Perceptions of CPR depth are improved by using real-time visual feedback and with prior JIT CPR training.
RCT Entities:
AIM: Many healthcare providers rely on visual perception to guide cardiopulmonary resuscitation (CPR), but little is known about the accuracy of provider perceptions of CPR quality. We aimed to describe the difference between perceived versus measured CPR quality, and to determine the impact of provider role, real-time visual CPR feedback and Just-in-Time (JIT) CPR training on provider perceptions. METHODS: We conducted secondary analyses of data collected from a prospective, multicenter, randomized trial of 324 healthcare providers who participated in a simulated cardiac arrest scenario between July 2012 and April 2014. Participants were randomized to one of four permutations of: JIT CPR training and real-time visual CPR feedback. We calculated the difference between perceived and measured quality of CPR and reported the proportion of subjects accurately estimating the quality of CPR within each study arm. RESULTS:Participants overestimated achieving adequate chest compression depth (mean difference range: 16.1-60.6%) and rate (range: 0.2-51%), and underestimated chest compression fraction (0.2-2.9%) across all arms. Compared to no intervention, the use of real-time feedback and JIT CPR training (alone or in combination) improved perception of depth (p<0.001). Accurate estimation of CPR quality was poor for chest compression depth (0-13%), rate (5-46%) and chest compression fraction (60-63%). Perception of depth is more accurate in CPR providers versus team leaders (27.8% vs. 7.4%; p=0.043) when using real-time feedback. CONCLUSION: Healthcare providers' visual perception of CPR quality is poor. Perceptions of CPR depth are improved by using real-time visual feedback and with prior JIT CPR training.
Authors: Murray M Pollack; Richard Holubkov; Robert A Berg; Christopher J L Newth; Kathleen L Meert; Rick E Harrison; Joseph Carcillo; Heidi Dalton; David L Wessel; J Michael Dean Journal: Resuscitation Date: 2018-09-25 Impact factor: 5.262
Authors: Adam Cheng; David Kessler; Ralph Mackinnon; Todd P Chang; Vinay M Nadkarni; Elizabeth A Hunt; Jordan Duval-Arnould; Yiqun Lin; David A Cook; Martin Pusic; Joshua Hui; David Moher; Matthias Egger; Marc Auerbach Journal: BMJ Simul Technol Enhanc Learn Date: 2016-07-24
Authors: R J MacKinnon; R Stoeter; C Doherty; C Fullwood; A Cheng; V Nadkarni; T Stenfors-Hayes; T P Chang Journal: BMJ Simul Technol Enhanc Learn Date: 2015-10-06
Authors: Elizabeth A Hunt; Jordan Duval-Arnould; Nnenna O Chime; Marc Auerbach; David Kessler; Jonathan P Duff; Nicole Shilkofski; Marissa Brett-Fleegler; Vinay Nadkarni; Adam Cheng Journal: BMJ Simul Technol Enhanc Learn Date: 2016-04-12
Authors: Michael Cassara; Kimberly Schertzer; Michael J Falk; Ambrose H Wong; Sara M Hock; Suzanne Bentley; Glenn Paetow; Lauren W Conlon; Patrick G Hughes; Ryan T McKenna; Michael Hrdy; Charles Lei; Miriam Kulkarni; Colleen M Smith; Amanda Young; Ernesto Romo; Michael D Smith; Jessica Hernandez; Christopher G Strother; Alise Frallicciardi; Nur-Ain Nadir Journal: AEM Educ Train Date: 2019-12-27
Authors: Robert Greif; Andrew Lockey; Jan Breckwoldt; Francesc Carmona; Patricia Conaghan; Artem Kuzovlev; Lucas Pflanzl-Knizacek; Ferenc Sari; Salma Shammet; Andrea Scapigliati; Nigel Turner; Joyce Yeung; Koenraad G Monsieurs Journal: Notf Rett Med Date: 2021-06-02 Impact factor: 0.826
Authors: Haamid Chamdawala; James A Meltzer; Viswanathan Shankar; Dina Elachi; Shannon M Jarzynka; Abigail F Nixon Journal: Resusc Plus Date: 2021-02-06