Comparison of sudden cardiac arrest resuscitation performance data obtained from in-hospital incident chart review and in situ high-fidelity medical simulation

Abstract Introduction High-fidelity medical simulation of sudden cardiac arrest (SCA) presents an opportunity for systematic probing of in-hospital resuscitation systems. Investigators developed and implemented the SimCode program to evaluate simulation's ability to generate meaningful data for...

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Published in:	Resuscitation Vol. 81; no. 4; pp. 463 - 471
Main Authors:	Kobayashi, Leo, Lindquist, David G, Jenouri, Ilse M, Dushay, Kevin M, Haze, Donna, Sutton, Elizabeth M, Smith, Jessica L, Tubbs, Robert J, Overly, Frank L, Foggle, John, Dunbar-Viveiros, Jennifer, Jones, Mark S, Marcotte, Scott T, Werner, David L, Cooper, Mary R, Martin, Peggy B, Tammaro, Dominick, Jay, Gregory D
Format:	Journal Article
Language:	English
Published:	Shannon Elsevier Ireland Ltd 01-04-2010 Elsevier
Subjects:	Anesthesia. Intensive care medicine. Transfusions. Cell therapy and gene therapy Biological and medical sciences Cardiopulmonary Resuscitation Electric Countershock Emergency Emergency and intensive cardiocirculatory care. Cardiogenic shock. Coronary intensive care Emergency treatment Health care quality improvement Heart Arrest - therapy Hospital Records Humans Intensive care medicine Medical emergency team Medical sciences Microsystem Resuscitation Resuscitation - standards Simulation Sudden cardiac death Emergency treatment Simulation Microsystem Medical emergency team Research Sudden cardiac death Resuscitation Health care quality improvement Cardiocirculatory arrest Cardiac performance Intensive care Sudden death Cardiovascular disease Sudden Treatment Emergency Comparative study
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Summary:	Abstract Introduction High-fidelity medical simulation of sudden cardiac arrest (SCA) presents an opportunity for systematic probing of in-hospital resuscitation systems. Investigators developed and implemented the SimCode program to evaluate simulation's ability to generate meaningful data for system safety analysis and determine concordance of observed results with institutional quality data. Methods Resuscitation response performance data were collected during in situ SCA simulations on hospital medical floors. SimCode dataset was compared with chart review-based dataset of actual (live) in-hospital resuscitation system performance for SCA events of similar acuity and complexity. Results 135 hospital personnel participated in nine SimCode resuscitations between 2006 and 2008. Resuscitation teams arrived at 2.5 ± 1.3 min (mean ± SD) after resuscitation initiation, started bag-valve-mask ventilation by 2.8 ± 0.5 min, and completed endotracheal intubations at 11.3 ± 4.0 min. CPR was performed within 3.1 ± 2.3 min; arrhythmia recognition occurred by 4.9 ± 2.1 min, defibrillation at 6.8 ± 2.4 min. Chart review data for 168 live in-hospital SCA events during a contemporaneous period were extracted from institutional database. CPR and defibrillation occurred later during SimCodes than reported by chart review, i.e., live: 0.9 ± 2.3 min ( p < 0.01) and 2.1 ± 4.1 min ( p < 0.01), respectively. Chart review noted fewer problems with CPR performance (simulated: 43% proper CPR vs. live: 98%, p < 0.01). Potential causes of discrepancies between resuscitation response datasets included sample size and data limitations, simulation fidelity, unmatched SCA scenario pools, and dissimilar determination of SCA response performance by complementary reviewing methodologies. Conclusion On-site simulations successfully generated SCA response measurements for comparison with live resuscitation chart review data. Continued research may refine simulation's role in quality initiatives, clarify methodologic discrepancies and improve SCA response.
Bibliography:	ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23
ISSN:	0300-9572 1873-1570
DOI:	10.1016/j.resuscitation.2010.01.003