Reducing Time to Medical Intervention Through Code Team Reorganization and Simulation Training
Main Article Content
Abstract
Background
Cardiac arrest is an acute event with very high morbidity and mortality rates. Ten in 1,000 admitted patients go into cardiac arrest each year and only a quarter of these patients survive to hospital discharge. Code environments are highly complex and require expert coordination among participants to improve patient survival. Despite recognition of the necessary elements for successful resuscitation. Time to medical intervention (TMI) and quality of chest compressions are well documented crucial aspects of a successful code, but other qualities such as demonstrative leadership, clear communication, effective team member interaction, and succinct task completion may also contribute to patient outcomes. Clearly identifying the role of each team member, their responsibilities, and bedside position may improve the success of a code situation. Similarly, pre-defined teams consistently outperform ad hoc teams.
Aim
The aim of this project was to decrease the time to medical intervention during mock code situations, improve close loop communication and leadership during a code.
Methods
We achieved our goals by restructuring our code team. First, all members necessary for a code team were identified, their respective roles clearly defined, and the most appropriate bedside positions for each role was carefully selected. Multidisciplinary team leaders were identified and trained as trainers by the core team for this project. Next, random mock codes were called to obtain baseline TMI. After the mock codes for baseline TMI to medical intervention, the trainers then trained the members of their unit on the appropriate roles and specific responsibilities they would be expected to complete during a code situation. Once training was completed, mock codes were randomly called and TMI was recorded. Also, there was a debriefing after these mock codes in which the participants were asked to give their impression of our Quality improvement project on the code team communication, leadership during the mock codes, quietness of the room and their comfort levels with performing the responsibilities of the role they performed. Time to medical intervention in these simulated codes were compared to the average time to medical intervention in our baseline mock codes.
Results
Post-code debriefings revealed a general sense of improved communication, improved crowd control, and clearer leadership when compared to other code situations the participants had been involved in. Similarly, time to shock delivery or medication administration shortened from the prior average of 2 minutes 46 seconds to 2 minutes 3 seconds, a statistically significant improvement (p-value 0.036). Participants also reported clearer communication, better understanding of their role and improved noise in the code environment.
Conclusions
Disorganized codes are costly in terms morbidity and post-arrest care. Having well organized codes with clear roles, responsibilities, and positions may decrease the TMI, communication, noise, leadership and improve patient outcomes. Real-life implementation and analysis of this intervention is needed.
TMI was defined as the time from when a code is called to the time when the first medication or defibrillation was administered which ever was warranted first.
Article Details
The Medical Research Archives grants authors the right to publish and reproduce the unrevised contribution in whole or in part at any time and in any form for any scholarly non-commercial purpose with the condition that all publications of the contribution include a full citation to the journal as published by the Medical Research Archives.
References
2. Benjamin EJ, Virani SS, Callaway CW, et al. Heart Disease and Stroke Statistics-2018 Update: A Report From the American Heart Association. Circulation. 2018;137(12):e67-e492.
3. Girotra S, Cram P, Spertus JA, et al. Hospital variation in survival trends for in-hospital cardiac arrest. J Am Heart Assoc. 2014;3(3):e000871.
4. Andersen LW, Holmberg MJ, Berg KM, Donnino MW, Granfeldt A. In-Hospital Cardiac Arrest: A Review. Jama. 2019;321(12):1200-1210.
5. Chan PS, Spertus JA, Krumholz HM, et al. A validated prediction tool for initial survivors of in-hospital cardiac arrest. Arch Intern Med. 2012;172(12):947-953.
6. Meaney PA, Bobrow BJ, Mancini ME, et al. Cardiopulmonary resuscitation quality: [corrected] improving cardiac resuscitation outcomes both inside and outside the hospital: a consensus statement from the American Heart Association. Circulation. 2013;128(4):417-435.
7. Prince CR, Hines EJ, Chyou PH, Heegeman DJ. Finding the key to a better code: code team restructure to improve performance and outcomes. Clin Med Res. 2014;12(1-2):47-57.
8. Hunziker S, Tschan F, Semmer NK, et al. Hands-on time during cardiopulmonary resuscitation is affected by the process of teambuilding: a prospective randomised simulator-based trial. BMC Emerg Med. 2009;9:3.
9. Marsch SCU, Müller C, Marquardt K, Conrad G, Tschan F, Hunziker PR. Human factors affect the quality of cardiopulmonary resuscitation in simulated cardiac arrests. Resuscitation. 2004;60(1):51-56.
10. Qureshi S, Ahern T, O'Shea R, Hatch L, Henderson SO. A standardized Code Blue Team eliminates variable survival from in-hospital cardiac arrest. J Emerg Med. 2012;42(1):74-78.
11. Wayne DB, Didwania A, Feinglass J, Fudala MJ, Barsuk JH, McGaghie WC. Simulation-based education improves quality of care during cardiac arrest team responses at an academic teaching hospital: a case-control study. Chest. 2008;133(1):56-61.
12. Andreatta P, Saxton E, Thompson M, Annich G. Simulation-based mock codes significantly correlate with improved pediatric patient cardiopulmonary arrest survival rates. Pediatr Crit Care Med. 2011;12(1):33-38.
13. Josey K, Smith ML, Kayani AS, et al. Hospitals with more-active participation in conducting standardized in-situ mock codes have improved survival after in-hospital cardiopulmonary arrest. Resuscitation. 2018;133:47-52.
14. Sinha SS, Sukul D, Lazarus JJ, et al. Identifying Important Gaps in Randomized Controlled Trials of Adult Cardiac Arrest Treatments: A Systematic Review of the Published Literature. Circ Cardiovasc Qual Outcomes. 2016;9(6):749-756.
15. Larkin GL, Copes WS, Nathanson BH, Kaye W. Pre-resuscitation factors associated with mortality in 49,130 cases of in-hospital cardiac arrest: a report from the National Registry for Cardiopulmonary Resuscitation. Resuscitation. 2010;81(3):302-311.
16. Joseph L, Chan PS, Bradley SM, et al. Temporal Changes in the Racial Gap in Survival After In-Hospital Cardiac Arrest. JAMA Cardiol. 2017;2(9):976-984.
17. Nadkarni VM, Larkin GL, Peberdy MA, et al. First documented rhythm and clinical outcome from in-hospital cardiac arrest among children and adults. Jama. 2006;295(1):50-57.
18. Rohlin O, Taeri T, Netzereab S, Ullemark E, Djarv T. Duration of CPR and impact on 30-day survival after ROSC for in-hospital cardiac arrest-A Swedish cohort study. Resuscitation. 2018;132:1-5.