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Can a flowchart improve the quality of bystander cardiopulmonary resuscitation?
Resuscitation 84 (2013) 982–986
Contents lists available at ScienceDirect
Resuscitation journal homepage: www.elsevier.com/locate/resuscitation
Simulation and education
Can a flowchart improve the quality of bystander cardiopulmonary resuscitation?夽 B. Rössler a,∗ , M. Ziegler b , M. Hüpfl a,b , R. Fleischhackl c , K.A. Krychtiuk b , K. Schebesta a a b c
Medical Simulation and Emergency Management Research Group, Department of Anaesthesia, General Intensive Care and Pain Management, Medical University of Vienna, Austria St. John’s Ambulance, Vienna, Austria “Puls” Association to Fight against Sudden Cardiac Death, Vienna, Austria
a r t i c l e
i n f o
Article history: Received 14 August 2012 Accepted 1 January 2013 Available online 07 January 2013 Keywords: Cardiopulmonary resuscitation Basic life support Bystander Pictograms Algorithm
a b s t r a c t Background: Since the introduction of basic life support in the 1950s, on-going efforts have been made to improve the quality of bystander cardiopulmonary resuscitation (CPR). Even though bystander-CPR can increase the chance of survival almost fourfold, the rates of bystander initiated CPR have remained low and rarely exceed 20%. Lack of confidence and fear of committing mistakes are reasons why helpers refrain from initiating CPR. The authors tested the hypothesis that quality and confidence of bystanderCPR can be increased by supplying lay helpers with a basic life support flowchart when commencing CPR, in a simulated resuscitation model. Materials and methods: After giving written informed consent, 83 medically untrained laypersons were randomised to perform basic life support for 300s with or without a supportive flowchart. The primary outcome parameter was hands-off time (HOT). Furthermore, the participants’ confidence in their actions on a 10-point Likert-like scale and time-to-chest compressions were assessed. Results: Overall HOT was 147 ± 30 s (flowchart) vs. 169 ± 55 s (non-flowchart), p = 0.024. Time to chest compressions was significantly longer in the flowchart group (60 ± 24 s vs. 23 ± 18 s, p < 0.0001). Participants in the flowchart group were significantly more confident when performing BLS than the non-flowchart counterparts (7 ± 2 vs. 5 ± 2, p = 0.0009). Conclusions: A chart provided at the beginning of resuscitation attempts improves quality of CPR significantly by decreasing HOT and increasing the participants’ confidence when performing CPR. As reducing HOT is associated with improved outcome and positively impacting the helpers’ confidence is one of the main obstacles to initiate CPR for lay helpers, charts could be utilised as simple measure to improve outcome in cardiopulmonary arrest. © 2013 Elsevier Ireland Ltd. All rights reserved.
1. Introduction Since the introduction of the basic life support (BLS) in the 1950s, on-going efforts have been made to improve the quality of resuscitation measures.1–4 International BLS algorithms have been designed, validated and published to meliorate the outcome after a cardiac arrest.3,5 However, the fundament of a functional chain of survival is in most cases built by lay people, since approximately 67% of the sudden cardiac deaths are witnessed by bystanders and the Emergency Medical Services response interval is eight minutes or more.6,7 Still, the respective bystanders may or may not have
夽 A Spanish translated version of the summary of this article appears as Appendix in the final online version at http://dx.doi.org/10.1016/j.resuscitation.2013.01.001. ∗ Corresponding author at: Department of Anaesthesia, Sir Charles Gairdner Hospital, Hospital Avenue, Nedlands, WA 6009, Australia. Tel.: +61 8 9346 3011; fax: +61 8 9346 4375. E-mail address: [email protected] (B. Rössler). 0300-9572/$ – see front matter © 2013 Elsevier Ireland Ltd. All rights reserved. http://dx.doi.org/10.1016/j.resuscitation.2013.01.001
been trained through BLS courses.3 Unfortunately, even though bystander cardiopulmonary resuscitation (CPR) can increase the chance of survival almost fourfold, the rates of bystander CPR have remained low and rarely exceed 20%.8–10 Panicking and lack of confidence are, besides fear of infectious diseases, reasons why helpers refrain from initiating CPR.11–15 Furthermore, perceived inability to perform CPR correctly is an important cause of CPR non-provision.11,16–18 Interruptions of chest compressions (e.g. due to hesitations as a consequence of fear or insecurity) is defined as hands-off-time (HOT) and has a detrimental effect on survival.19 HOT therefore includes all times when chest compressions are not performed. It was one of the aims of the European Resuscitation Council to adapt the BLS Guidelines in order to simplify teaching and skill retention.3 The 2010 BLS algorithm of the European Resuscitation Council was therefore implemented in order to enable bystanders to execute the algorithm more correctly and aiming at a higher percentage of bystander-initiated resuscitations.3 Various strategies have been developed to assist bystanders to recognise a cardiac arrest situation, initiate CPR
B. Rössler et al. / Resuscitation 84 (2013) 982–986
correctly, and improve its quality.20,21 Graphic images have been used in to convey medical information and can improve its acquisition and comprehension.22 Along with written instructions, graphic images are included in current BLS guidelines.3
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Consequently, we wanted to test the hypothesis that quality of BLS as well as the confidence of the bystander can be increased by supplying lay helpers with a flowchart containing an easy to understand BLS instruction in written and graphic steps. As a selfexplanatory term we introduced the name “HeartChart” (Fig. 1).
Fig. 1. Flowchart. Unconscious! – What to do? (1) Speak to and touch the collapsed person! No reaction? (2) Shout for help! (3) Open airway: breathing? – No? (4) Dial emergency medical service: 144! (5) Send for an automated external defibrillator: activate and follow voice instructions! (6) Chest compressions: 30× push hard! (7) Open airway and give two mouth-to-mouth ventilations. Repeat 6 and 7 until emergency medical service arrives.
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HOT was chosen as primary outcome parameter, while the participants’ confidence was chosen as a secondary outcome parameter.
2. Methods After approval by the Ethics Committee of the Medical University of Vienna, Vienna, Austria (Protocol Nr.: 385/2011) the investigation was conducted as a prospective, randomised controlled trial. Volunteers between 18 and 80 years of age irrespective of gender, of non-medical profession (thus excluding e.g. nurse, medical doctor, physiotherapist, ergo therapist, and paramedics), who were registered to participate in a first aid course were enrolled. Pregnant women and people with physical impairment or illness prohibiting physical effort were excluded. After giving written informed consent, participants were randomised using a computer-generated random sequence that was kept in opaque and sealed envelopes. Participants were then allocated to perform CPR with or without flowchart support. The evaluation was performed with an independent investigator using a computer attached Laerdal Skill Reporting System with Segstats (Version 2.3.0, Laerdal Medical, Stavanger, Norway). The participants were then asked to undertake any action they deem necessary to rescue the person simulated by the resuscitation manikin. At the beginning of the scenario, the manikin was positioned in a supine position on the floor. The room was prepared to minimise outside interruptions. Participants in the flowchart group received the chart right at the beginning of the scenario with the start of the clock and without further instructions regarding its content. Both groups did not receive any further introduction or support. Data of steps performed or omitted as well as the exact times were documented electronically and on hardcopy case report forms where appropriate.
3. Endpoints The primary outcome parameter was HOT in five minutes of manikin-simulated CPR. Secondary outcome parameter was corrected HOT, which was defined as HOT from the first set of chest compressions (CC) to the end of the scenario. Furthermore, completeness of the initial BLS assessment was evaluated in accordance to the BLS algorithm 2010 (1. Unresponsive? 2. Shout for help. 3. Open airway. 4. Not breathing normally? 5. Call local emergency number. 6. Start chest compressions).3 Following parameters regarding CC were analysed: time to CC, total number of CC, CC per cycle, compression depth, and compression rate. Furthermore, the participants’ confidence and fear was assessed on a 10-point Likert-like scale directly after the scenario. Confidence was assessed by asking the participant “How confident did you feel while performing CPR?” (0: not confident at all, 10: absolutely confident). Additionally, individuals were asked to rate their fear of committing a mistake, and of harming the cardiac arrest victim as a consequence of their actions, again on the 10-point Likert-like scale. If participants of any group choose to perform CC only and refrain from rescue breaths, data would not be excluded from analysis.
4. Statistical methods In accordance to previously collected pilot data HOT within 300 s of CPR by lay helpers was estimated to be 200 s with a standard deviation of 32 s. In order to detect a clinical important difference of 10% in HOT at a power of 80% and a p-level of 0.05 a total sample size of 81 was needed. In order to compensate a potential dropout rate of up to 15%, 94 participants had to be enrolled.
Table 1 provides details on the participants’ demographics (mean ± standard deviation). Cardiopulmonary resuscitation (CPR). Real CPR: Have you ever performed CPR in on a cardiac arrest victim? Start CPR: Would you start CPR on an unknown adult in cardiac arrest?
Age (y) Gender: female Years since last course Real CPR: yes Start CPR: yes
Non-flowchart (n = 41)
Flowchart (n = 43)
34 ± 12 13 (32%) 12 ± 10 1 (2%) 32 (78%)
39 ± 11 13 (30%) 15 ± 12 1 (2%) 36 (84%)
Data management was conducted with Microsoft Excel for Mac 2011 (14.0.2, Redmond, WA, USA). Data are presented as mean ± standard deviation with the corresponding 95% confidence intervals unless otherwise specified. Two sided Student’s T-test and Chi-Square test were performed were apropriate. All p-values are two-sided and p ≤ 0.05 was regarded to be statistically significant. Prism (Version 5.0a, Graph Pad Software, San Diego, USA) and R 2.8.1 for Mac was used for statistical analysis (R Foundation for Statistical Computing, Vienna, Austria).23
5. Results Within the recruitment period between 12/12/2011 and 06/04/2012 a total of 94 individuals were randomised to participate in the trial, 10 chose to drop out. Eighty-four participants were included in the analysis. One individual (flowchart group) did not perceive the situation correctly and did never commence any form of CPR. Consequently, this set of data was excluded from analysis of primary and secondary outcome parameters. Details on baseline data are provided in Table 1. Overall HOT was 147 ± 30 s in the flowchart group and 169 ± 55 s in the non-flowchart group in the 300s scenario (p = 0.024, 95% CI of difference 3.0–41.6). Corrected HOT (HOT from the first set of CC to the end of the scenario) was 87 ± 25 (flowchart) and 146 ± 54 s (non-flowchart, p < 0.0001, 95% CI of difference 40.8–77.5). Twentysix (62%) participants completed the BLS algorithm correctly in the flowchart group, while no participant did so in the non-flowchart group (p < 0.0001). Details on the quality of the initial BLS algorithm are provided in Table 2. Time to CC was significantly longer in the flowchart group (60 ± 24 vs. 23 ± 18 s, p < 0.0001, 95% CI of difference −46.2 to −27.6). Total number of CC was 200 ± 51 (flowchart) vs. 189 ± 110 (non-flowchart, p = 0.55, 95% CI of difference −48.7 to 26.0). Further details on CC are provided in Table 3. Participants in the flowchart group were significantly more confident when performing BLS than the non-flowchart counterparts (7 ± 2 vs. 5 ± 2, p = 0.0009, 95% CI of difference −2.8 to −0.7). Fear of harming the cardiac arrest victim did not differ between the groups (3 ± 3 vs. 3 ± 3, p = 0.40, 95% CI of difference −0.8 to 1.9). Accordingly, fear of making a mistake was 4 ± 3 vs. 5 ± 3 (p = 0.18, 95% CI of difference −0.4 to 2.3).
Table 2 provides details on the initial BLS assessment in accordance to the 2010 BLS guidelines.3 Automated external defibrillator (AED). Non-flowchart (n = 41) Stimulate (yes) Shout for help (yes) Open airway (yes) Check for normal breathing (yes) Emergency call/AED (yes)
7 (17%) 0 (0%) 9 (22%) 15 (37%) 2 (5%)
Flowchart (n = 42)
p
37 (88%) 39 (93%) 34 (81%) 31 (74%) 39 (92%)
<0.0001 <0.0001 <0.0001 0.002 <0.0001
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Table 3 provides details on the quality of chest compressions (CC). Confidence interval (CI). Non-flowchart (n = 41) Compression depth (mm) Rate of CC (min−1 ) CC in 5 min (n) CC per cycle (n)
41 76 189 17
± ± ± ±
12 36 110 13
6. Discussion By introducing a BLS flowchart containing instructions in written and graphic steps, HOT as well as corrected HOT improved significantly in this simulated resuscitation model. Most noteworthy, the participants’ confidence and adherence to the BLS Guidelines increased significantly when utilising the flowchart. This novel supportive technique can impact practical BLS quality of bystanders in a simple and effective manner. These findings constitute an essential improvement since interruptions to chest compressions have a negative impact on survival.19 Previously published data clearly demonstrated the positive impact of previous guideline changes and training on HOT.24,25 Additionally, it has been shown that fear and insecurity result in decreased CPR performance.26 When utilising the flowchart, participants also followed the BLS Algorithm more correctly. Initial steps in the BLS Algorithm are not only essential for the correct perception of the cardiac arrest situation but also include steps such as timely call for help and obtaining an automated external defibrillator rapidly. With an increasing number of automated external defibrillators available this becomes increasingly more important, since early defibrillation impacts the chance of successful resuscitation.27 Nevertheless, this improvement comes at the price of prolonged time to CC. While the interval to commence CC should be ideally as short as possible, this delay is made up by improved initial assessment, CC ratio and decreased HOT. The delayed start of CC by using the flowchart has been more than overcome in this 5-min scenario. Since response times of emergency medical services are often eight minute or more, the effect of the reduction of HOT by far outweighs the initial “cost” of longer time to CC.7 Most noteworthy, the chart increased the perception of confidence in lay helpers. In a previous trial by Taniguchi et al., the reasons for the unwillingness among laypeople to perform CPR were inadequate knowledge and/or doubt regarding whether they could perform the techniques effectively.26 Accordingly, dispatcher-assisted CPR including audio–visual aids on mobile phones also improved confidence of lay helpers significantly.21 Consequently, impacting the confidence of lay helpers must be regarded as an important component when aiming at increased bystander CPR rates. Previous trials evaluating the impact of visual aids on CPR performance have shown differing results.28,29 While one checklist did not improve the performance of trained lay helpers, a longer checklist improved quality of post-course cardiopulmonary resuscitation.28 While the study by Ward and colleagues also included lay helpers, all of them were undergraduate students and had participated in a BLS course 8 weeks prior to assessment.28 Recently published data evaluating the impact of a flowchart provided to healthcare professionals when performing neonatal resuscitation did also not show significant quality improvement of post-course neonatal resuscitation performance.29 Noteworthy, in the study by Bould and colleagues, many participants assigned to the intervention group refrained from using the flowchart due to lack of clarity.29 The nature of the chart as step-by-step approach, the included pictograms and independence from electrical devices or power
Flowchart (n = 42) 43 78 200 28
± ± ± ±
12 29 51 4
p-Value
95% CI of difference
0.49 0.75 0.55 <0.0001
−7 to 3 −16 to 11 −49 to 26 −16 to −7
supply constitute essential advantages. Furthermore, this low-cost technique can be implemented in private households and public places and additionally create awareness about BLS before an incident. While quality improvement of BLS in the context of this manikin setting is possible when using the flowchart, further trials are needed to evaluate its effectiveness in human cardiac arrest situations. Individuals involved in a medical emergency experience high levels of stress during this demanding situation.30 While the manikin setting per se inevitably influences emotional responses regarding confidence and fear, previous publication have highlighted comparable substantial emotional involvement in simulated CPR scenarios.31 In this study setting, the chart was provided “just-in-time”. This potentially influences the impact of the chart since, if applied to e.g. households and companies, the chart would be available beforehand and a learning effect before entering the CPR situation cannot be ruled out. Consequently, the effect of the flowchart on confidence and quality of CPR could be underestimated. Our findings are align with the results of Bradley et al., who described “just-intime” instructions from dispatcher-assisted CPR that could increase bystander CPR and improve the likelihood of survival.32 The impact of an electronic version of this visual aid for mobile phones remains to be evaluated. Further research is needed to evaluate the applicability and cost-effectiveness of distributing the flowchart to a broader public.
7. Conclusion A simple BLS flowchart can improve the quality of bystander CPR significantly. By using this tool, hands-off-time decreased significantly, while at the same time the participants’ confidence increased. Other than the non-flowchart group, participants using the chart were able to follow the BLS algorithm correctly. Consequently, significant quality improvement and consequently improved outcome in bystander CPR is possible.
Conflict of interest statement Three of the authors (KS, BR, MH) are members and instructors of the Paediatric Working Group of the Austrian Resuscitation Council the national division of the European Resuscitation Council, and instructors for European Trauma Courses. However, there are no financial and/or personal relationships of any of our authors with other people or organisations that could inappropriately influence our work.
Acknowledgements The authors express their sincere gratitude to Aron Cserveny, graphic designer who was responsible for drawing the pictograms and creating the design of the chart. PULS for spreading the news and supporting the idea of assisted bystander CPR.
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Appendix A. Supplementary data Supplementary data associated with this article can be found, in the online version, at http://dx.doi.org/10.1016/ j.resuscitation.2013.01.001. References 1. Nolan J. European Resuscitation Council Guidelines for resuscitation 2005 Section 1. Introduction. Resuscitation 2005;67:3–6. 2. Handley AJ, Koster R, Monsieurs K, Perkins GD, Davies S, Bossaert L. European Resuscitation Council European Resuscitation Council guidelines for resuscitation 2005. Section 2. Adult basic life support and use of automated external defibrillators. Resuscitation 2005;67:7–23. 3. Koster RW, Baubin MA, Bossaert LL, et al. European Resuscitation Council Guidelines for Resuscitation 2010. Section 2. Adult basic life support and use of automated external defibrillators. Resuscitation 2010;81:1277–92. 4. Ewy GA, Kellum M. Advancing resuscitation science. Curr Opin Crit Care 2012;18:221–7. 5. Berg RA, Hemphill R, Abella BS, et al. Part 5: adult basic life support: 2010 American Heart Association Guidelines for cardiopulmonary resuscitation and emergency cardiovascular care. Circulation 2010;122:685–705. 6. Müller D, Agrawal R, Arntz HR. How sudden is sudden cardiac death? Circulation 2006;12, 114:1146–50. 7. vanAlemAP, Vrenken RH, de Vos R, Tijssen JG, Koster RW. Use of automatedexternal defibrillator by first responders in out of hospital cardiac arrest: prospective controlled trial. BMJ 2003;327:1312–7. 8. Stiell IG, Wells GA, Field B, et al. Advanced cardiac life sup- port in out-of-hospital cardiac arrest. N Engl J Med 2004;351:647–56. 9. Nichol G, Thomas E, Callaway CW, et al. Regional variation in out-ofhospital cardiac arrest incidence and outcome. J Am Med Assoc 2008;300: 1423–31. 10. Vaillancourt C, Stiell IG. Canadian Cardiovascular Outcomes Research Team (CCORT) cardiac arrest care and emergency medical services in Canada. Can J Cardiol 2004;20:1081–90. 11. Shibata K, Taniguchi T, Yoshida M, Yamamoto K. Obstacles to bystander cardiopulmonary resuscitation in Japan. Resuscitation 2000;44:187–93. 12. Swor R, Khan I, Domeier R, Honeycutt L, Chu K, Compton S. CPR training and CPR performance: do CPR-trained bystanders perform CPR? Acad Emerg Med 2006;13:596–601. 13. Locke CJ, Berg RA, Sanders AB, et al. Bystander cardiopulmonary resuscitation concerns about mouth-to-mouth contact. Arch Intern Med 1995;155: 938–43. 14. Brenner BE, Kauffman J. Reluctance of internists and medical nurses to perform mouth-to-mouth resuscitation. Arch Intern Med 1993;153:1763–9.
15. Ornato JP, Hallagan LF, McMahan SB, Peeples EH, Rostafinski AG. Attitudes of BCLS instructors about mouth-to-mouth resuscitation during the AIDS epidemic. Ann Emerg Med 1990;19:151–6. 16. Idris AH. Reassessing the need for ventilation during CPR. Ann Emerg Med 1996;27:569–75. 17. Smith KL, Cameron PA, Meyer AD, McNeil JJ. Is the public equipped to act in out of hospital cardiac emergencies? Emerg Med J 2003;20:85–7. 18. Platz E, Scheatzle MD, Pepe PE, Dearwater SR. Attitudes towards CPR training and performance in family members of patients with heart disease. Resuscitation 2000;47:273–80. 19. Eftestol T, Sunde K, Steen PA. Effects of interrupting precordial compressions on the calculated probability of defibrillation success during out-of-hospital cardiac arrest. Circulation 2002;105:2270–3. 20. Vaillancourt C, Verma A, Trickett J, et al. Evaluating the effectiveness of dispatch-assisted cardiopulmonary resuscitation instructions. Acad Emerg Med 2007;14:877–83. 21. Bolle SR, Johnsen E, Gilbert M. Video calls for dispatcher-assisted cardiopulmonary resuscitation can improve the confidence of lay rescuers – surveys after simulated cardiac arrest. J Telemed Telecare 2011;17:88–92. 22. Mansoor LE, Dowse R. Effect of pictograms on readability of patient information materials. Ann Pharmacother 2003;37:1003–9. 23. R Development Core Team: R. A language and environment for statistical computing. Vienna, Austria: R Foundation for Statistical Computing; 2009. 24. Roessler B, Fleischhackl R, Losert H, et al. Reduced hands-off-time and time to first shock in CPR according to the ERC Guidelines 2005. Resuscitation 2009;80:104–8. 25. Nielsen AM, Henriksen MJ, Isbye DL, Lippert FK, Rasmussen LS. Acquisition and retention of basic life support skills in an untrained population using a personal resuscitation manikin and video self-instruction (VSI). Resuscitation 2010;81:1156–60. 26. Taniguchi T, Omi W, Inaba H. Attitudes toward the performance of bystander cardiopulmonary resuscitation in Japan. Resuscitation 2007;75:82–7. 27. Kitamura T, Iwami T, Kawamura T, Nagao K, Tanaka H, Hiraide A. Nationwide public-access defibrillation in Japan. NEJM 2010;362:994–1004. 28. Ward P, Johnson LA, Mulligan NW, Ward MC, Jones DL. Improving cardiopulmonary resuscitation skills retention: effect of two checklists designed to prompt correct performance. Resuscitation 1997;34:221–5. 29. Bould MD, Hayter MA, Campbell DM, Chandra DB, Joo HS, Naik VN. Cognitive aid for neonatal resuscitation: a prospective single-blinded randomized controlled trial. Br J Anaesth 2009;103:570–5. 30. Scott G, Mulgrew E, Smith T. Cardiopulmonary resuscitation: attitudes and perceptions of junior doctors. Hosp Med 2003;64:425–8. 31. Hunziker S, Laschinger L, Portmann-Schwarz S, Semmer NK, Tschan F, Marsch S. Perceived stress and team performance during a simulated resuscitation. Intensive Care Med 2011;37:1473–9. 32. Bradley SM, Rea TD. Improving bystander cardiopulmonary resuscitation. Curr Opin Crit Care 2011;17:219–24.
Contents lists available at ScienceDirect
Resuscitation journal homepage: www.elsevier.com/locate/resuscitation
Simulation and education
Can a flowchart improve the quality of bystander cardiopulmonary resuscitation?夽 B. Rössler a,∗ , M. Ziegler b , M. Hüpfl a,b , R. Fleischhackl c , K.A. Krychtiuk b , K. Schebesta a a b c
Medical Simulation and Emergency Management Research Group, Department of Anaesthesia, General Intensive Care and Pain Management, Medical University of Vienna, Austria St. John’s Ambulance, Vienna, Austria “Puls” Association to Fight against Sudden Cardiac Death, Vienna, Austria
a r t i c l e
i n f o
Article history: Received 14 August 2012 Accepted 1 January 2013 Available online 07 January 2013 Keywords: Cardiopulmonary resuscitation Basic life support Bystander Pictograms Algorithm
a b s t r a c t Background: Since the introduction of basic life support in the 1950s, on-going efforts have been made to improve the quality of bystander cardiopulmonary resuscitation (CPR). Even though bystander-CPR can increase the chance of survival almost fourfold, the rates of bystander initiated CPR have remained low and rarely exceed 20%. Lack of confidence and fear of committing mistakes are reasons why helpers refrain from initiating CPR. The authors tested the hypothesis that quality and confidence of bystanderCPR can be increased by supplying lay helpers with a basic life support flowchart when commencing CPR, in a simulated resuscitation model. Materials and methods: After giving written informed consent, 83 medically untrained laypersons were randomised to perform basic life support for 300s with or without a supportive flowchart. The primary outcome parameter was hands-off time (HOT). Furthermore, the participants’ confidence in their actions on a 10-point Likert-like scale and time-to-chest compressions were assessed. Results: Overall HOT was 147 ± 30 s (flowchart) vs. 169 ± 55 s (non-flowchart), p = 0.024. Time to chest compressions was significantly longer in the flowchart group (60 ± 24 s vs. 23 ± 18 s, p < 0.0001). Participants in the flowchart group were significantly more confident when performing BLS than the non-flowchart counterparts (7 ± 2 vs. 5 ± 2, p = 0.0009). Conclusions: A chart provided at the beginning of resuscitation attempts improves quality of CPR significantly by decreasing HOT and increasing the participants’ confidence when performing CPR. As reducing HOT is associated with improved outcome and positively impacting the helpers’ confidence is one of the main obstacles to initiate CPR for lay helpers, charts could be utilised as simple measure to improve outcome in cardiopulmonary arrest. © 2013 Elsevier Ireland Ltd. All rights reserved.
1. Introduction Since the introduction of the basic life support (BLS) in the 1950s, on-going efforts have been made to improve the quality of resuscitation measures.1–4 International BLS algorithms have been designed, validated and published to meliorate the outcome after a cardiac arrest.3,5 However, the fundament of a functional chain of survival is in most cases built by lay people, since approximately 67% of the sudden cardiac deaths are witnessed by bystanders and the Emergency Medical Services response interval is eight minutes or more.6,7 Still, the respective bystanders may or may not have
夽 A Spanish translated version of the summary of this article appears as Appendix in the final online version at http://dx.doi.org/10.1016/j.resuscitation.2013.01.001. ∗ Corresponding author at: Department of Anaesthesia, Sir Charles Gairdner Hospital, Hospital Avenue, Nedlands, WA 6009, Australia. Tel.: +61 8 9346 3011; fax: +61 8 9346 4375. E-mail address: [email protected] (B. Rössler). 0300-9572/$ – see front matter © 2013 Elsevier Ireland Ltd. All rights reserved. http://dx.doi.org/10.1016/j.resuscitation.2013.01.001
been trained through BLS courses.3 Unfortunately, even though bystander cardiopulmonary resuscitation (CPR) can increase the chance of survival almost fourfold, the rates of bystander CPR have remained low and rarely exceed 20%.8–10 Panicking and lack of confidence are, besides fear of infectious diseases, reasons why helpers refrain from initiating CPR.11–15 Furthermore, perceived inability to perform CPR correctly is an important cause of CPR non-provision.11,16–18 Interruptions of chest compressions (e.g. due to hesitations as a consequence of fear or insecurity) is defined as hands-off-time (HOT) and has a detrimental effect on survival.19 HOT therefore includes all times when chest compressions are not performed. It was one of the aims of the European Resuscitation Council to adapt the BLS Guidelines in order to simplify teaching and skill retention.3 The 2010 BLS algorithm of the European Resuscitation Council was therefore implemented in order to enable bystanders to execute the algorithm more correctly and aiming at a higher percentage of bystander-initiated resuscitations.3 Various strategies have been developed to assist bystanders to recognise a cardiac arrest situation, initiate CPR
B. Rössler et al. / Resuscitation 84 (2013) 982–986
correctly, and improve its quality.20,21 Graphic images have been used in to convey medical information and can improve its acquisition and comprehension.22 Along with written instructions, graphic images are included in current BLS guidelines.3
983
Consequently, we wanted to test the hypothesis that quality of BLS as well as the confidence of the bystander can be increased by supplying lay helpers with a flowchart containing an easy to understand BLS instruction in written and graphic steps. As a selfexplanatory term we introduced the name “HeartChart” (Fig. 1).
Fig. 1. Flowchart. Unconscious! – What to do? (1) Speak to and touch the collapsed person! No reaction? (2) Shout for help! (3) Open airway: breathing? – No? (4) Dial emergency medical service: 144! (5) Send for an automated external defibrillator: activate and follow voice instructions! (6) Chest compressions: 30× push hard! (7) Open airway and give two mouth-to-mouth ventilations. Repeat 6 and 7 until emergency medical service arrives.
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B. Rössler et al. / Resuscitation 84 (2013) 982–986
HOT was chosen as primary outcome parameter, while the participants’ confidence was chosen as a secondary outcome parameter.
2. Methods After approval by the Ethics Committee of the Medical University of Vienna, Vienna, Austria (Protocol Nr.: 385/2011) the investigation was conducted as a prospective, randomised controlled trial. Volunteers between 18 and 80 years of age irrespective of gender, of non-medical profession (thus excluding e.g. nurse, medical doctor, physiotherapist, ergo therapist, and paramedics), who were registered to participate in a first aid course were enrolled. Pregnant women and people with physical impairment or illness prohibiting physical effort were excluded. After giving written informed consent, participants were randomised using a computer-generated random sequence that was kept in opaque and sealed envelopes. Participants were then allocated to perform CPR with or without flowchart support. The evaluation was performed with an independent investigator using a computer attached Laerdal Skill Reporting System with Segstats (Version 2.3.0, Laerdal Medical, Stavanger, Norway). The participants were then asked to undertake any action they deem necessary to rescue the person simulated by the resuscitation manikin. At the beginning of the scenario, the manikin was positioned in a supine position on the floor. The room was prepared to minimise outside interruptions. Participants in the flowchart group received the chart right at the beginning of the scenario with the start of the clock and without further instructions regarding its content. Both groups did not receive any further introduction or support. Data of steps performed or omitted as well as the exact times were documented electronically and on hardcopy case report forms where appropriate.
3. Endpoints The primary outcome parameter was HOT in five minutes of manikin-simulated CPR. Secondary outcome parameter was corrected HOT, which was defined as HOT from the first set of chest compressions (CC) to the end of the scenario. Furthermore, completeness of the initial BLS assessment was evaluated in accordance to the BLS algorithm 2010 (1. Unresponsive? 2. Shout for help. 3. Open airway. 4. Not breathing normally? 5. Call local emergency number. 6. Start chest compressions).3 Following parameters regarding CC were analysed: time to CC, total number of CC, CC per cycle, compression depth, and compression rate. Furthermore, the participants’ confidence and fear was assessed on a 10-point Likert-like scale directly after the scenario. Confidence was assessed by asking the participant “How confident did you feel while performing CPR?” (0: not confident at all, 10: absolutely confident). Additionally, individuals were asked to rate their fear of committing a mistake, and of harming the cardiac arrest victim as a consequence of their actions, again on the 10-point Likert-like scale. If participants of any group choose to perform CC only and refrain from rescue breaths, data would not be excluded from analysis.
4. Statistical methods In accordance to previously collected pilot data HOT within 300 s of CPR by lay helpers was estimated to be 200 s with a standard deviation of 32 s. In order to detect a clinical important difference of 10% in HOT at a power of 80% and a p-level of 0.05 a total sample size of 81 was needed. In order to compensate a potential dropout rate of up to 15%, 94 participants had to be enrolled.
Table 1 provides details on the participants’ demographics (mean ± standard deviation). Cardiopulmonary resuscitation (CPR). Real CPR: Have you ever performed CPR in on a cardiac arrest victim? Start CPR: Would you start CPR on an unknown adult in cardiac arrest?
Age (y) Gender: female Years since last course Real CPR: yes Start CPR: yes
Non-flowchart (n = 41)
Flowchart (n = 43)
34 ± 12 13 (32%) 12 ± 10 1 (2%) 32 (78%)
39 ± 11 13 (30%) 15 ± 12 1 (2%) 36 (84%)
Data management was conducted with Microsoft Excel for Mac 2011 (14.0.2, Redmond, WA, USA). Data are presented as mean ± standard deviation with the corresponding 95% confidence intervals unless otherwise specified. Two sided Student’s T-test and Chi-Square test were performed were apropriate. All p-values are two-sided and p ≤ 0.05 was regarded to be statistically significant. Prism (Version 5.0a, Graph Pad Software, San Diego, USA) and R 2.8.1 for Mac was used for statistical analysis (R Foundation for Statistical Computing, Vienna, Austria).23
5. Results Within the recruitment period between 12/12/2011 and 06/04/2012 a total of 94 individuals were randomised to participate in the trial, 10 chose to drop out. Eighty-four participants were included in the analysis. One individual (flowchart group) did not perceive the situation correctly and did never commence any form of CPR. Consequently, this set of data was excluded from analysis of primary and secondary outcome parameters. Details on baseline data are provided in Table 1. Overall HOT was 147 ± 30 s in the flowchart group and 169 ± 55 s in the non-flowchart group in the 300s scenario (p = 0.024, 95% CI of difference 3.0–41.6). Corrected HOT (HOT from the first set of CC to the end of the scenario) was 87 ± 25 (flowchart) and 146 ± 54 s (non-flowchart, p < 0.0001, 95% CI of difference 40.8–77.5). Twentysix (62%) participants completed the BLS algorithm correctly in the flowchart group, while no participant did so in the non-flowchart group (p < 0.0001). Details on the quality of the initial BLS algorithm are provided in Table 2. Time to CC was significantly longer in the flowchart group (60 ± 24 vs. 23 ± 18 s, p < 0.0001, 95% CI of difference −46.2 to −27.6). Total number of CC was 200 ± 51 (flowchart) vs. 189 ± 110 (non-flowchart, p = 0.55, 95% CI of difference −48.7 to 26.0). Further details on CC are provided in Table 3. Participants in the flowchart group were significantly more confident when performing BLS than the non-flowchart counterparts (7 ± 2 vs. 5 ± 2, p = 0.0009, 95% CI of difference −2.8 to −0.7). Fear of harming the cardiac arrest victim did not differ between the groups (3 ± 3 vs. 3 ± 3, p = 0.40, 95% CI of difference −0.8 to 1.9). Accordingly, fear of making a mistake was 4 ± 3 vs. 5 ± 3 (p = 0.18, 95% CI of difference −0.4 to 2.3).
Table 2 provides details on the initial BLS assessment in accordance to the 2010 BLS guidelines.3 Automated external defibrillator (AED). Non-flowchart (n = 41) Stimulate (yes) Shout for help (yes) Open airway (yes) Check for normal breathing (yes) Emergency call/AED (yes)
7 (17%) 0 (0%) 9 (22%) 15 (37%) 2 (5%)
Flowchart (n = 42)
p
37 (88%) 39 (93%) 34 (81%) 31 (74%) 39 (92%)
<0.0001 <0.0001 <0.0001 0.002 <0.0001
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Table 3 provides details on the quality of chest compressions (CC). Confidence interval (CI). Non-flowchart (n = 41) Compression depth (mm) Rate of CC (min−1 ) CC in 5 min (n) CC per cycle (n)
41 76 189 17
± ± ± ±
12 36 110 13
6. Discussion By introducing a BLS flowchart containing instructions in written and graphic steps, HOT as well as corrected HOT improved significantly in this simulated resuscitation model. Most noteworthy, the participants’ confidence and adherence to the BLS Guidelines increased significantly when utilising the flowchart. This novel supportive technique can impact practical BLS quality of bystanders in a simple and effective manner. These findings constitute an essential improvement since interruptions to chest compressions have a negative impact on survival.19 Previously published data clearly demonstrated the positive impact of previous guideline changes and training on HOT.24,25 Additionally, it has been shown that fear and insecurity result in decreased CPR performance.26 When utilising the flowchart, participants also followed the BLS Algorithm more correctly. Initial steps in the BLS Algorithm are not only essential for the correct perception of the cardiac arrest situation but also include steps such as timely call for help and obtaining an automated external defibrillator rapidly. With an increasing number of automated external defibrillators available this becomes increasingly more important, since early defibrillation impacts the chance of successful resuscitation.27 Nevertheless, this improvement comes at the price of prolonged time to CC. While the interval to commence CC should be ideally as short as possible, this delay is made up by improved initial assessment, CC ratio and decreased HOT. The delayed start of CC by using the flowchart has been more than overcome in this 5-min scenario. Since response times of emergency medical services are often eight minute or more, the effect of the reduction of HOT by far outweighs the initial “cost” of longer time to CC.7 Most noteworthy, the chart increased the perception of confidence in lay helpers. In a previous trial by Taniguchi et al., the reasons for the unwillingness among laypeople to perform CPR were inadequate knowledge and/or doubt regarding whether they could perform the techniques effectively.26 Accordingly, dispatcher-assisted CPR including audio–visual aids on mobile phones also improved confidence of lay helpers significantly.21 Consequently, impacting the confidence of lay helpers must be regarded as an important component when aiming at increased bystander CPR rates. Previous trials evaluating the impact of visual aids on CPR performance have shown differing results.28,29 While one checklist did not improve the performance of trained lay helpers, a longer checklist improved quality of post-course cardiopulmonary resuscitation.28 While the study by Ward and colleagues also included lay helpers, all of them were undergraduate students and had participated in a BLS course 8 weeks prior to assessment.28 Recently published data evaluating the impact of a flowchart provided to healthcare professionals when performing neonatal resuscitation did also not show significant quality improvement of post-course neonatal resuscitation performance.29 Noteworthy, in the study by Bould and colleagues, many participants assigned to the intervention group refrained from using the flowchart due to lack of clarity.29 The nature of the chart as step-by-step approach, the included pictograms and independence from electrical devices or power
Flowchart (n = 42) 43 78 200 28
± ± ± ±
12 29 51 4
p-Value
95% CI of difference
0.49 0.75 0.55 <0.0001
−7 to 3 −16 to 11 −49 to 26 −16 to −7
supply constitute essential advantages. Furthermore, this low-cost technique can be implemented in private households and public places and additionally create awareness about BLS before an incident. While quality improvement of BLS in the context of this manikin setting is possible when using the flowchart, further trials are needed to evaluate its effectiveness in human cardiac arrest situations. Individuals involved in a medical emergency experience high levels of stress during this demanding situation.30 While the manikin setting per se inevitably influences emotional responses regarding confidence and fear, previous publication have highlighted comparable substantial emotional involvement in simulated CPR scenarios.31 In this study setting, the chart was provided “just-in-time”. This potentially influences the impact of the chart since, if applied to e.g. households and companies, the chart would be available beforehand and a learning effect before entering the CPR situation cannot be ruled out. Consequently, the effect of the flowchart on confidence and quality of CPR could be underestimated. Our findings are align with the results of Bradley et al., who described “just-intime” instructions from dispatcher-assisted CPR that could increase bystander CPR and improve the likelihood of survival.32 The impact of an electronic version of this visual aid for mobile phones remains to be evaluated. Further research is needed to evaluate the applicability and cost-effectiveness of distributing the flowchart to a broader public.
7. Conclusion A simple BLS flowchart can improve the quality of bystander CPR significantly. By using this tool, hands-off-time decreased significantly, while at the same time the participants’ confidence increased. Other than the non-flowchart group, participants using the chart were able to follow the BLS algorithm correctly. Consequently, significant quality improvement and consequently improved outcome in bystander CPR is possible.
Conflict of interest statement Three of the authors (KS, BR, MH) are members and instructors of the Paediatric Working Group of the Austrian Resuscitation Council the national division of the European Resuscitation Council, and instructors for European Trauma Courses. However, there are no financial and/or personal relationships of any of our authors with other people or organisations that could inappropriately influence our work.
Acknowledgements The authors express their sincere gratitude to Aron Cserveny, graphic designer who was responsible for drawing the pictograms and creating the design of the chart. PULS for spreading the news and supporting the idea of assisted bystander CPR.
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