Aaron Dix and co-authors describe their study to improve Out of Hospital Cardiac Arrest for EMTs.

Aaron Dix, MBA, EMT, Marty Lutz, MD and Callie Heyne, MHA candidate examine the use of simulation to improve OHCA in the Greenville, South Carolina EMS System.

Sudden non-traumatic out-of-hospital cardiac arrest (OHCA) is a significant public health threat affecting over 350,000 Americans annually. The American Heart Association (AHA) has provided evidence-based guidelines to improve survivability from OHCA, yet survivability continues to remain low throughout the nation and ranges between 2%- 11% 1. Two factors preventing an increase in outcomes have been described: the first is a lack of adherence to the accepted guidelines, and the second is the existence of knowledge gaps in the fundamental importance of CPR quality.2

Simulation is a widely accepted educational concept in the medical field and is frequently implemented to improve knowledge and procedural skills.3 Previously published studies have demonstrated that simulation improves adherence to advanced cardiac life support (ACLS) guidelines, group communication, confidence, and knowledge during resuscitation.3,4

Additional studies have determined that retention of resuscitation skills after simulation has a lasting effect.4 Several studies have demonstrated the effectiveness of simulation as a component of resuscitation education, while correlation to improved patient outcomes has been elusive. Despite the correlation of mock pediatric codes with improved outcomes with in-hospital pediatric cardiac arrests5, a randomized controlled study found no effect on outcomes from inpatient adult codes after simulation based ACLS training.3 An additional published study found improved adult ACLS care after simulation but no correlation with patient outcomes. 6

This retrospective study examines the simulation program of a large metropolitan emergency medical service (EMS) that implemented several protocol changes in an attempt to improve neurologically intact survival from cardiac arrest. EMS ACLS protocols were established following American Heart Association (AHA) 2010 ACLS guidelines and included the use of an impedance threshold device (ITD), initiation of therapeutic hypothermia after return of spontaneous circulation (ROSC), and field termination of unsuccessful resuscitation prior to transport. A continuous quality improvement program conducted by the EMS system reviewed every cardiac arrest for adherence to protocol. Prior to the simulation initiative, adherence to established protocols was low. In 2011, a rigorous simulation-based training program was implemented to improve adherence to those existing protocols. The sole purpose of the simulation initiative was to improve outcomes and data was not collected with the intent to publish. After an increase in positive outcomes was observed, an institutional review board (IRB) approved study was conducted to determine if the training statistically improved the quality of care and if the increase in outcomes was statistically significant.

Methods

Study Setting: Greenville County, South Carolina, is 790 square miles with a population of 450,000. Greenville County EMS (GCEMS) is the sole provider of emergency medical services in the county with a staff of 220 employees including approximately 170 paramedics. Medical first response is provided by 30 separate fire departments with varying capabilities but primarily CPR, AED, and oxygen. Eleven of the fire departments are trained to at least the EMT level and are licensed by the state of South Carolina to provide medical first response and operate under the protocols and medical direction of GCEMS. The system provides care for approximately 55,000 patients a year and initiates resuscitation on over 330 medical cardiac arrests a year.

Greenville Healthcare Simulation Center (GHSC) is a multidisciplinary center serving nearly every teaching program affiliated with the Greenville Health System. Participants include high school and college students, medical students from the University of South Carolina School of Medicine Greenville, nursing students from Clemson University and Greenville Technical College, pharmacy, emergency medical personnel, residents, and faculty members from a variety of healthcare disciplines.

Training: In 2011, a comprehensive simulation-based training program was designed for all EMS field providers. The program consisted of four hours of lectures on the 2010 AHA ACLS guidelines, in-depth instruction on resuscitation science, emphasis on maximizing coronary perfusion pressure with compressions, and timing of defibrillations that reduced the peri-shock pause to less than 10 seconds.

Participants then completed a series of three scenarios focused on CPR and ACLS, post-resuscitation and termination of unsuccessful resuscitation (TOR) in the field. The first resuscitation scenario; a middle-aged male who suddenly collapsed in ventricular fibrillation. Participants, in groups of two, demonstrated competency in resuscitation on a Laerdal 3G that allowed CPR feedback. Competency was defined as a compression rate between 100-120 compressions per minute, a peri-shock pause less than 10 seconds, use of an ITD, and appropriate timing of defibrillations. The scenario ended after the simulated patient converted to a normal sinus rhythm after the third defibrillation. The second scenario; participants were presented with a patient who was successfully resuscitated by first responders after a shock from an AED. Competency was defined as successfully initiating therapeutic hypothermia and acquiring a 12-lead ECG within 10 minutes of starting the scenario. The final scenario; an entire 20 minute resuscitation that ended with termination of resuscitative efforts.

Having a protocol to terminate unsuccessful resuscitation in the field was essential to improving outcomes. The amount of movement required to ready the patient for transport and place the patient into the ambulance causes multiple lengthy pauses in compressions. Allowing paramedics to provide lengthy resuscitation at the point of collapse would hopefully improve CPR quality and outcomes. Terminating an unsuccessful resuscitation was a necessary step in allowing paramedics to have lengthy resuscitation scene times.

Study Design: Approval to conduct a retrospective study of patient outcomes was obtained from the institutional review board (IRB) at Greenville Health System. The dataset included prehospital and in-hospital records of patients older than 18 years of age who suffered a non-traumatic out-of-hospital cardiac arrest and were treated by Greenville County EMS (GCEMS) and either terminated in the field or transported to Greenville Memorial Hospital. The study period was from June 1, 2012 to May 31, 2013; the pre-intervention period was between January 1, 2010 and December 31, 2010. Simulation occurred between the pre- and post-data sample periods.

 Methods of Measurement: Bivariate analysis was performed to determine if simulation resulted in differences in treatment at a significant level. Only three data sets were available during both study years: therapeutic hypothermia, utilization of an impedance threshold device, and termination of resuscitation in the field. CPR analytics, while probably the most predictive variable of a positive outcome from OHCA, were not collected prior to 2012.

Bivariate analysis was performed on patient demographics, presenting rhythm, and whether arrests were witnessed. Multivariable logistic regressions were then performed on the three available data sets and outcomes with the control characteristics as independent variables.

 Results

Table 1. Bivariate Analysis of Protocol Changes
Protocol Pre-Intervention (N=201) Post- Intervention (N=245) P-value
Therapeutic Hypothermia 9 (4.5%) 57 (23.3%) <0.001
Impedance Threshold Device Usage 62 (30.8%) 169 (69.0%) <0.001
Terminated in the Field 11 (5.5%) 74 (30.2%) <0.001
Table 1 shows that implementation of therapeutic hypothermia, use of the impedance threshold device and termination in the field all increased significantly by Chi-squared bivariate analysis after implementation of new protocols and training. The increased rate of arrests that were terminated in the field was a key part of the study, both as a goal of the improved protocols, and as a key outcome in data analysis.
Table 2. OHCA Characteristics
Characteristic Pre-Intervention (N=201) Post-Intervention

(N=245)

P-value
Age, Mean ± SD 63.6715.17 63.48±16.07 0.900
White, N (%) 151(75.1%) 180(73.5%) 0.691
Non-White, N (%) 50 (24.9%) 65 (26.5%) 0.691
Male, N (%) 131 (65.2%) 162 (66.1%) 0.834
Shockable Rhythm, N (%) 45 (22.4%) 62 (25.3%) 0.473
Witnessed Arrest, N (%) 94 (46.8%) 134 (54.7%) 0.096
There were no significant differences between the two groups that may have impacted the protocol implementation and survivability (age, race, whether arrest was witnessed and whether patients had shockable rhythm when emergency responders arrived).
Table 3. OHCA Outcomes
Outcome Pre-Intervention (N=201) Post-Intervention (N=245) P-value
Survive CPC score of 1 or 2 17 (8.5%) 35 (14.3%) 0.056
Termination of Resuscitation in the Field 11 (5.4%) 74 (30.2%) 0.005
Died in the ED 129 (64.2%) 85 (34.7%) <0.001
Died in the Hospital 44 (21.9%) 51 (20.8%) 0.109
 

The proportion of patients who survived to discharge increased from 8.4% to 14.3% (p=0.056). Only patients with a CPC score of 1 or 2 were included in the survival to discharge outcome. No patients in 2010 survived with a CPC score of 3 or 4, but three additional patients were discharged in the Post-Intervention group who were not included in the data. Only patients with a CPC score of 1 or 2, positive neurological outcomes, were included in the data analysis.

After simulation training, the number of cardiac arrests terminated in the field increased significantly from 39.3% to 67.9% (p=0.005). As the patients who died in the field increased, the proportion of patients who died in the ED decreased significantly (p=<0.001) and the number of patients who died in the hospital did not change (p=0.109). This data suggests that the correct patients were identified for termination of arrest in the field, reducing the number of transports and emergency department resources utilized while still accurately determining those patients with the potential to benefit from further treatment.

Overall, patients were more likely to survive after simulation was provided, although not to a statistically significant level.

Limitations

The study only included transports to the largest receiver of OHCA, Greenville Memorial Hospital. The lower sample size made it statistically infeasible to look separately at subgroups such as ventricular rhythm and witnessed arrests. Including all transported OHCA patients may have been enough to increase the improvement in outcomes to a significant level.

Conclusion

Results of this retrospective study found that simulation did improve adherence to resuscitation treatment protocols. The three measurable treatments - ITD usage, initiation of therapeutic hypothermia, and termination of unsuccessful resuscitation in the field - all improved after simulation training. While patient outcomes from OHCA did improve after training, the increase was not statistically significant. This may have been due to the limited sample size. Most studies evaluate the effectiveness of resuscitation simulation by using checklists, mock codes, and questionnaires. This study sought to analyze clinical data in order to demonstrate that high-fidelity simulation can improve adherence to resuscitation protocols and improve patient outcomes.

An aggressive simulation strategy implemented by Greenville County EMS for the treatment of OHCA was validated and improved care. Favorable neurological outcomes from OHCA were increased, futility of additional care was recognized, and transports of non-survivable cardiac arrest patients were decreased.

About the Authors

Aaron Dix is the Operations Director for the Greenville Healthcare Simulation Center. He has a MBA in Healthcare Management, is a Nationally Certified EMS Educator, and has 20 years of EMS experience. Prior to becoming Operations Director, he was the training coordinator for the largest and busiest EMS system in South Carolina managing the education of over 500 EMTs, paramedics, and fire-fighters. In addition to his duties at the simulation center, he remains a practicing paramedic with Anderson County EMS, Clear Spring Fire Rescue, and is an active member of the Emergency Medical Services for Children Advisory Council in South Carolina.

Dr. Marty Lutz finished his Emergency Medicine residency in Ohio in 1984 and moved to Greenville where he has been a practicing Emergency Medicine Physician at Greenville Health System (GHS). He has been a fellow of ACEP since 1987. Dr. Lutz is past Chairman of the Department of Emergency Medicine. He has served on multiple GHS Committees in the past, including Credentials, Trauma, and Emergency Preparedness. He is currently a member of the Medical Executive Committee and chairs the Practitioner Health Committee. Currently Dr. Lutz is Chief, Emergency Medical Transport Services and the Medical Director of the Patient Referral and Transfer Center. He is also medical control physician for GHS Mobile Care Ambulance Service, Greenville County EMS, Eagle Med fixed wing service and GHS Med Trans helicopter service.

Callie Heyne is a MHA Candidate at the University of Minnesota, graduated Summa Cum Laude from Clemson University. She earned Clemson University's Health and Human Development Phi Kappa Phi Certificate of Merit, presented a Departmental Honors Thesis titled Advanced EMS Treatment of Out of Hospital Cardiac Arrest, and was awarded a Calhoun Honors College Research Grant.

REFERENCES

  1. Sayre MR, Cantrell SA, White LJ, Hiestand BC, Keseg DP, Koser S. Impact of the 2005 American heart association cardiopulmonary resuscitation and emergency cardiovascular care guidelines on out-of-hospital cardiac arrest survival. Prehospital Emerg Care. 2009;13(4):469-477.
  2. Meaney P, Bobrow BJ, Mancini ME, Christenson J, de Caen AR, Bhanji F, Abella BS, Kleinman ME, Edelson DP, Berg RA, Aufderheide TP, Menon V, Leary M; CPR Quality Summit Investigators, the American Heart Association Emergency Cardiovascular Care Committee, and the Council on Cardiopulmonary, Critical Care, Perioperative and Resuscitation. Cardiopulmonary resuscitation quality: improving cardiac resuscitation outcomes both inside and outside the hospital: a consensus statement from the American Heart Association. Circulation 2013;128:417-435.
  3. Han J, Trammell A, Udoji TN, Dressler D, Honig EG, Abraham P, et al. Evaluating simulation-based ACLS Education on patient outcomes: A randomized, controlled pilot study. J Grad Med Educ 2014;6(3): 501-506.
  4. Sahu S, Lata I. Simulation in resuscitation teaching and training, an evidence based practice review . J Emerg Trauma Shock 2010;3(4): 378-384.
  5. 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.
  6. 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.