Elsevier

Resuscitation

Volume 81, Issue 4, April 2010, Pages 463-471
Resuscitation

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

https://doi.org/10.1016/j.resuscitation.2010.01.003Get rights and content

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.

Introduction

Sudden cardiac arrest (SCA) is a leading cause of death in the United States, accounting for an estimated 325,000 deaths per year.1, 2 A significant proportion of these patients experience ventricular fibrillation (VF) or pulseless ventricular tachycardia, arrhythmias that may be reversible if cardiopulmonary supportive interventions and defibrillation are immediately available.3, 4 The proven association of early intervention and rapid defibrillation with survival-to-discharge,5, 6, 7 however, has not resulted in hospital resuscitation performance that consistently meets nationally established recommendations.8

In-hospital SCA presents an opportunity for definable improvements in patient outcomes,9, 10 even though specifics of its current incidence are limited11 and its very nature poses several challenges. A fundamental problem is exposed in published reviews of unanticipated in-hospital medical resuscitation (“code” or “emergency”) management, which repeatedly report problems with documentation of events.12, 13 Especially for patients admitted to non-telemetry units, accurate resuscitation records following Utstein14 and National Registry of Cardiopulmonary Resuscitation (NRCPR)15 guidelines, e.g., documentation of intervals between time of cardiac arrest until time to cardiopulmonary resuscitation (CPR) initiation or time to first defibrillation, may not be available. Events preceding the arrest may never be fully clarified even in monitored high-acuity settings, and temporal measurements of critical actions during the resuscitation may be incomplete and imprecise.12 Medicolegal concerns may discourage disclosure16 and clear discussion of peri-arrest details, effectively impeding quality management efforts. Limitations in data collection can generate misleading, if not hazardous or ineffective,17 interpretations of in-hospital SCA response performance.

An alternative approach to examining in-hospital SCA exists in the form of advanced medical simulation (SIM), the advent of which is changing education and assessment across the spectrum of healthcare systems.18 In situ simulations employing interactive full-body manikins and carried out within actual clinical environments are especially pertinent for systems probing and context-dependent performance assessment19; examples include pediatric medical and trauma patient care scenarios in an Emergency Department resuscitation bay20 and teamwork and communications sessions held inside an actual obstetric suite.21, 22

Investigators applied in situ medical simulation to conduct in-hospital medical cardiopulmonary arrest scenarios [SimCodes] to (1) assess the local feasibility of in-hospital high-fidelity medical resuscitation simulations; (2) evaluate the simulation methodology's ability to generate objective, reproducible resuscitation data for system safety analysis; and (3) determine the concordance of common and accessible data elements between SimCode observation results and institutional quality management data compiled from chart review of actual (live) resuscitations. This manuscript presents SimCode program development and the investigative acquisition, characterization, and comparison of resuscitation performance datasets from traditional and simulated methods.

Section snippets

Setting and sample

The SimCode program is ongoing at an academic 719-bed regional referral hospital and Level 1 trauma center. Personnel from the institution's simulation center and departments of Emergency Medicine, Medicine, Nursing Education, Quality Management and Risk Management developed and implemented the program.

The SimCode team developed several on-site SIM scenarios with a modified SimMan manikin (Laerdal, Wappingers Falls, NY) for interdisciplinary resuscitation team immersion. Scenarios featured

Results

During a 27-month period between May 2006 and July 2008, a convenience sample of nine multi-disciplinary resuscitation teams involving a total of 135 hospital personnel participated in nine on-site SimCode resuscitations. Data from completed simulation sessions (excluding one set of time data lost with video record) revealed resuscitation teams arriving 2.5 ± 1.3 min (mean ± SD; range 0.5–4.4 min [nteam(SIM) = 8 available data points out of 9 possible]) after SimCode initiation, proper bag-valve-mask

Discussion

Simulation is described as “a technique to replace or amplify [real-life] experiences with guided experiences that evoke or replicate substantial aspects of the real world in a fully interactive fashion.”23 Even as studies are ongoing to establish its efficacy and validity, medical simulation is generally believed to contribute to the safety of patients. Notably, several recent reports demonstrate the utility of simulation training for knowledge and skills acquisition with retention in medical,

Conclusions

Scientific investigation of system performance in situ during simulated in-hospital SCA events may reveal overt as well as latent issues that jeopardize patient safety. SIM may prove valuable in accurate assessment of the care of patients requiring unanticipated cardiopulmonary resuscitation.

Conflicts of interest statement

No conflicts of interest for authors have arisen during the study or manuscript preparation.

Funding

This material is based upon work supported by the institution's Departments of Emergency Medicine and Risk Management. The opinions, findings, conclusions and recommendations expressed in the manuscript are those of the authors and do not necessarily reflect the views of the supporting departments.

Acknowledgements

The authors would like to acknowledge Anna C. Cousins for her insight and assistance in manuscript preparation and Jason Machan for his assistance with statistical analysis.

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    A Spanish translated version of the abstract of this article appears as Appendix in the final online version at doi:10.1016/j.resuscitation.2010.01.003.

    ☆☆

    Aspects of portable and mobile simulation sessions discussed within the article were presented as abstracts at the April 2008 BMJ International Forum on Patient Safety in Healthcare, Paris, France, the October 2008 Research Forum of the American College of Emergency Physicians Scientific Assembly in Chicago, IL, the November 2008 Lifespan Research Celebration, Providence, RI, and the January 2009 International Meeting on Simulation in Healthcare in Orlando, FL.

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