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Advanced life support provider course in Italy: A 5-year nationwide study to identify the determinants of course success
Resuscitation 96 (2015) 246–251
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Simulation and education
Advanced life support provider course in Italy: A 5-year nationwide study to identify the determinants of course success夽 Federico Semeraro a,b,∗ , Andrea Scapigliati a,c,1 , Gaetano Tammaro a,b,2 , Umberto Olcese d,3 , Erga L. Cerchiari a,b,4 , Giuseppe Ristagno a,e,5 a
Italian Resuscitation Council, Bologna, Italy Department of Anaesthesia and Intensive Care, Ospedale Maggiore, Bologna, Italy c Institute of Anaesthesia and Intensive Care, Department of Cardiovascular Sciences, Catholic University of the Sacred Heart, Rome, Italy d Swammerdam Institute for Life Sciences, University of Amsterdam, Amsterdam, The Netherlands e IRCCS-Istituto di Ricerche Farmacologiche “Mario Negri”, Milan, Italy b
a r t i c l e
i n f o
Article history: Received 17 March 2015 Received in revised form 20 July 2015 Accepted 14 August 2015 Keywords: Advanced life support Course Education Database Cardiac arrest
a b s t r a c t Introduction: The advanced life support (ALS) provider course is the gold standard for teaching and assessing competence in advanced resuscitation. Outcomes over a 5-year period of European Resuscitation (ERC)/IRC ALS provider courses in Italy were investigated, and the factors associated with course success are described. Methods: In 2008, the Italian Resuscitation Council (IRC) created a database in which every ERC/IRC ALS course was recorded. Data from courses organized from 2008 to 2012 were analysed. The data included: candidate’s age and degree (medical doctor (MD) or nurse), medical specialty of MD candidates, course outcomes, duration and reference guidelines, number of instructors and course director. Relationships between the course outcomes and the courses and candidates’ characteristics were analysed using logistic regression. Results: A total of 13,624 candidates were evaluated from 871 courses. Among the candidates, 55% were MDs and 45% were nurses. Ninety-seven percent of candidates passed the final evaluation, while 3% failed. Candidates who passed were younger (37 [31–44] vs. 43 [37–50] years, p < 0.0001) and had a greater precourse resuscitation knowledge (multiple choice quiz (MCQ) score: 88 [83–93] vs. 80 [73–87], p < 0.0001) compared to those who failed. The course pass rate was higher for MDs compared to nurses (98% vs. 95%, p < 0.0001) and participants in emergency disciplines were most significantly associated with course success (2 71, p < 0.0001). In the multivariate analysis, an older age (OR 0.926, 95%CI [0.915–0.937]) was independently associated with course failure, while being a MD (OR 3.021, 95%CI [2.212–4.132]), having a higher pre-course MCQ score (OR 1.033, 95%CI [1.026–1.040]) together with a higher candidate/instructor ratio (OR 1.314, 95%CI [1.067–1.618]), and having a longer course duration (OR 1.717, 95%CI [1.090–2.703]), were independently associated with success. Conclusions: Younger age, professional background, and pre-course resuscitation knowledge are the most important predictors of ALS provider course success, together with higher candidate/instructor ratios and longer course durations. © 2015 Elsevier Ireland Ltd. All rights reserved.
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.2015.08.006. ∗ Corresponding author. Present affiliation: Consultant in Anaesthesia and Intensive Care, Maggiore Hospital, Bologna, Italy. Fax: +39 0514189693. E-mail address: [email protected] (F. Semeraro). 1 Present affiliation: Institute of Anaesthesia and Intensive Care, Department of Cardiovascular Sciences, Catholic University of the Sacred Heart, Rome, Italy. 2 Present affiliation: Critical Care Nurse, Maggiore Hospital, Bologna, Italy. 3 Present affiliation: Swammerdam Institute for Life Sciences, University of Amsterdam, Amsterdam, The Netherlands. 4 Present affiliation: Anaesthesia and Intensive Care, Maggiore Hospital, Bologna, Italy. 5 Present affiliation: Istituto di Ricerche Farmacologiche “Mario Negri”—IRCCS, Milano, Italy. http://dx.doi.org/10.1016/j.resuscitation.2015.08.006 0300-9572/© 2015 Elsevier Ireland Ltd. All rights reserved.
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Introduction The quality of cardiopulmonary resuscitation (CPR) is a major determinant of successful resuscitation.1 However, CPR quality is often poor in clinical settings, and a lack of resuscitation skills in basic and advanced life support (BLS and ALS) can contribute to poor outcomes.2,3 Improvements in CPR knowledge and skills through specific training courses are therefore essential. The ALS provider course is recognized as the gold standard in teaching and assessing competencies in advanced resuscitation for healthcare professionals.4,5 It provides a standardized approach to the management of cardiac arrest, including: manual defibrillation; advanced airway; drug therapy; peri-arrest circumstances; and post-resuscitation care.4,6 Indeed, ALS courses are held in a uniform format throughout Europe by the national resuscitation councils under the auspices of the European Resuscitation Council (ERC). More than 1.5 million healthcare professionals around the world attend ALS provider courses each year.7 A main advantage of the course is the simulation of different cardiac arrest scenarios (CAS), in which candidates practice and interact as members of a potential resuscitation team.5,6 However, the same training format must fit the varying professional backgrounds of the attending professionals who can experience the course as too basic or can become overwhelmed with information and skill requirements.5,8–11 The identification of factors associated with course outcomes might help instructors identify and target candidates’ specific needs. In Italy, the Italian Resuscitation Council (IRC) organizes ERC/IRC ALS courses nationwide in compliance with the ERC guidelines.6,10,11 To oversee the courses and instructors’ activities, in 2008, the IRC created a national database in which course data are recorded, including information on the course itself and on the candidates. The aim of this study was to investigate the outcomes of ALS provider courses in Italy over a 5-year period and to describe the determinants associated with course pass/fail rates. This is a large-scale and multi-centre analysis, including 871 ALS courses nationwide and more than 13,000 candidates.
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of MDs; course outcomes; pre- and post-course multiple choice quiz (MCQ) scores; outcomes of the first CAS testing (CASTest 1) and second (re-test) CASTest (CASTest 2); course duration and reference guidelines (2005 or 2010); candidate/instructor ratio; and course director. Only candidates who attended the ALS provider course for the first time were included in this study. For the analysis, MDs working in the following areas were considered to belong to “emergency” disciplines: anaesthesia and intensive care; cardiology; emergency medical systems; emergency departments; and neonatology. Statistical analysis Categorical variables are presented as proportions, and continuous variables are presented as medians with a range (from min to max) or the interquartile range (IQR). Univariate analysis was employed to investigate the predictors of the ALS course outcomes. For categorical outcomes (ALS, CASTest 1 and 2, and pre/postcourse MCQ scores), Fisher’s exact test or the Chi-square test were used to evaluate their relationship with categorical variables (i.e., specialty), while logistic regression was used for continuous variables (i.e., age). For continuous outcomes (the MCQ score), the Wilcoxon rank sum test and Kruskal–Wallis test were employed to evaluate their relationship with categorical variables, while quantile regressions were used for continuous variables.13 For multivariate analysis, all of the independent variables were entered in the logistic regression model. Goodness of fit was evaluated by comparing the actual and fit values. Because approximately one-third of records lacked a pre-course MCQ score, a multiple imputation method was employed to include the whole dataset in the multivariate analysis.14 The results of the linear regressions are reported in terms of the beta coefficients ± SD, while the results of the multivariate logistic regressions are reported as the odds ratio (OR) with the corresponding 95% confidence interval (CI). Statistical significance was set at p < 0.05.15 Statistical analyses were performed in R (www.r-project.org). Zelig and Amelia packages were employed for multivariate analyses, while the Quantreg package was used for quantile regressions.
Methods Results The study was a retrospective analysis of data recorded in the national IRC ALS course database for administrative and statistical reasons. Candidates were informed of the data collection and provided written consent for their use. The IRC ALS provider course The ERC ALS provider course was devised in 1992.5 It was partly modelled on the Advanced Cardiac Life Support (ACLS) course introduced by the American Heart Association in 1975.12 The ERC/IRC course then significantly evolved into a standardized format with a European-derived manual.6,10,11 Details are in the Supplemental methods. The IRC database
Overall, 13,744 candidates participated in 871 ALS provider courses during the 5-year period. One hundred-thirty-two candidates were excluded due to previous course attendance, while 145 candidates dropped out of the course. Finally, data from 13,264 participants (median age 37) were included in the analyses. Fiftyfive percent of the candidates were MDs, and 45% were nurses (Table 1). Described using medians, there were 179 [min–max, 144–197] courses per year involving 2705 [2348–2891] candidates, 61 [46–67] course directors, and 116 [104–159] new potential instructors.
Table 1 Descriptive of candidates in relationship to ALS provider course outcome. All
The IRC ALS course database was created in 2007 and became operative on January 1st, 2008 (www.ircouncil.it/corsi). All ERC/IRC ALS courses organized in Italy are recorded in the database, including information on the course outcomes, structure, director, and candidates’ characteristics. Course registration in the database is mandatory to obtain ERC/IRC recognition and certifications. For this study, data from 2008 to 2012 were extracted from the database. The data analysed included: the candidates’ age; professional background (medical doctors (MD) or nurses) and specialty
Age (median[IQR]) Candidates, n MD, n Nurses, n Pre-course MCQ, (median[IQR]) Post-course MCQ, (median[IQR])
Pass
Fail
37 [31–44] 13,264 7352 5912 88 [83–93]
37 [31–44] 12,803 7180 5623 88 [83–93]
43 [37-50]* 461 172 289 80 [73-87]*
89 [84–93]
89 [85–93]
72 [60-80]*
MD, medical doctor; IQR, interquartile range; MCQ, multiple choice quiz. * p < 0.0001 vs. Pass.
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Fig. 1. ALS provider course outcomes in relation to the course structure (candidate/instructor ratio, duration, and CPR guidelines (GL) used as a reference) and to the candidates’ characteristics (degree and age). Numbers in brackets represent the number of candidates. White bars, course success; black bars, course failure.
Ninety-seven percent of candidates successfully passed the course, with a constant pass rate over the years (min–max, 95–98%). More than 98% of candidates passed the post-course MCQ and 90% passed the CASTest 1; however, of those who underwent a retest, only 68% passed the CASTest 2. The pre-course MCQ score was significantly higher in candidates who passed the course compared to those who failed (p < 0.0001, Table 1). More specifically, in the univariate analysis, higher pre-course MCQ scores were positively correlated with higher pass rates of the ALS course (ˇ 0.0246 ± 0.003, p < 0.0001) and its sub-tests: post-course MCQ (ˇ 0.0282 ± 0.003, p < 0.0001); CASTest 1 (ˇ 0.0184 ± 0.002, p < 0.0001); and CASTest 2 (ˇ 0.0177 ± 0.005, p < 0.0001). Course outcomes in relationship with candidates’ ages, candidate/instructor ratio, changes in the CPR guidelines, course duration, and candidates’ professional backgrounds are reported in Fig. 1. Younger candidates had higher percentages of passed courses and their sub-tests (p < 0.0001, Fig. 1 and Table 2). Indeed, increasing age was inversely correlated with course success, as represented by the negative ˇ in the univariate analysis: ˇ −0.0596 ± 0.005, for the ALS course (p < 0.0001); ˇ −0.0674 ± 0.07, for the post-course MCQ (p < 0.0001); ˇ −0.0374 ± 0.003, for the CASTest 1 (p < 0.0001); and ˇ −0.0445 ± 0.007, for the CASTest 2 (p < 0.0001). A greater rate of success was observed in courses with a lower number of instructors compared to those with a higher number of instructors (Fig. 1 and Table 2). Indeed, in the univariate analysis, a higher candidate/instructor ratio was positively correlated with a higher likelihood of passing the ALS course (ˇ 0.2217 ± 0.084, p = 0.009), the post-course MCQ (ˇ 0.2350 ± 0.109, p = 0.031), and the CASTest 2 (ˇ 0.2927 ± 0.108, p = 0.006), but not the CASTest 1 (ˇ 0.0168 ± 0.049, p = 0.736). Courses based on the 2005 CPR guidelines had a higher pass rate compared with those based on the 2010 guidelines (97% vs. 96%, OR 1.230, 95%CI [1.016–1.488], p = 0.03) (Fig. 1 and Table 2). More specifically, the 2005 guidelines were associated with positive outcomes at the post-course MCQ (OR 1.279, 95%CI [0.999–1.638], p = 0.048), but not at the CASTest 1 (OR 1.098, 95%CI [0.977–1.234],
p = 0.11) or the CASTest 2 (OR 1.253, 95%CI [0.980–1.602], p = 0.067). The course duration, 2 vs. 3 days, was not associated with differences in the course outcomes in univariate analysis (Fig. 1 and Table 2). Ninety-eight percent of MDs passed the course compared to 95% of nurses (p < 0.0001, Table 1 and Fig. 1). The percentage of MDs who passed the post-course MCQ, CASTest 1, and CASTest 2 was also significantly higher compared to the percentage of nurses who passed (p < 0.0001, Table 2). Being an MD was associated with a higher pass rate in the ALS course (OR 2.146, 95%CI [1.764–2.618], p < 0.0001) and its sub-tests: the post-test MCQ (OR 2.545, 95%CI [1.965–3.322], p < 0.0001), the CASTest 1 (OR 1.389, 95%CI [1.238–1.560], p < 0.0001), and the CASTest 2 (OR 1.852, 95%CI [1.443–2.381], p < 0.0001). MDs working in “emergency” disciplines passed the overall ALS course and its sub-tests at significantly higher rates compared to candidate MDs working in other disciplines (surgery or medicine) and compared to nurses (p < 0.05, Fig. 2). Indeed, the “emergency” disciplines were significantly associated with overall positive outcomes in the ALS course (2 71, p < 0.0001), the posttest MCQ (2 60, p < 0.0001), the CASTest 1 (2 52, p < 0.0001) and the CASTest 2 (2 26, p < 0.0001). Among the specialties included in the “emergency” disciplines, anaesthesiology was the most significantly associated with course success: 2 206, for the overall ALS course (p < 0.0001); 2 180, for the post-course MCQ (p < 0.0001); 2 230, for the CASTest 1 (p < 0.0001); and 2 101, for the CASTest2 (p < 0.0001). The outcomes of the ALS courses stratified by the different healthcare specialties are detailed in the Supplemental Figure. Finally, the proportion of candidates passing the course varied between different course directors, with a pass rate per director of 98.1% [min–max, 84–100%]. Thus, the course director was significantly associated with the course outcome; indeed, the 2 was 487 (p < 0.0001), for the ALS outcome; 483 (p < 0.0001), for the post-course MCQ; 556 (p < 0.0001), for the CASTest 1; and 226 (p < 0.0001), for the CASTest 2.
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Table 2 ALS provider course sub-tests outcome in relationship to course structure and candidate’s characteristics. Post-course MCQ
CASTest 1
CASTest 2
Candidates (n)
Pass (%)
Fail (%)
Pass (%)
Fail (%)
Pass (%)
Fail (%)
Age (quartiles) ≤30 31–36 37–43 ≥44
2990 3204 3480 3588
89 90 88 88 p < 0.0001
11 10 12 12
94 92 89 86 p < 0.0001
6 8 11 14
84 74 69 59 p < 0.0001
16 26 31 41
Degree MD Nurse
7352 5912
99 97 p < 0.0001
1 3
91 88 p < 0.0001
9 12
75 62 p < 0.0001
25 38
Course duration 2 day 3 day
1535 11,729
98 98 p = 0.44
2 2
90 90 p = 0.68
10 10
65 69 p = 0.44
35 31
Guidelines 2005 2010
7620 5644
98 98 p = 0.05
2 2
90 90 p = 0.11
10 10
70 66 p = 0.07
30 34
Candidates/instructor ratio 1 2 3 4 5 6
54 2582 8596 1819 170 43
83 88 89 89 88 96 p = 0.03
17 12 11 11 12 4
91 90 90 90 92 84 p = 0.74
9 10 10 10 8 16
40 60 70 76 62 83 p = 0.006
60 40 30 24 38 17
MD, medical doctor; MCQ, multiple choice quiz; CASTest, cardiac arrest scenario test.
In the multivariate analysis, the factors independently associated with ALS course success were a younger age, higher candidate/instructor ratio, longer duration of the course (3 days), being an MD, and having a higher pre-course MCQ score (Table 3). Changes in the CPR guidelines were not independently associated with the course pass rates. Younger age, being an MD, and a higher pre-course MCQ score were also independently associated with the success of the course sub-tests, including the post-course MCQ, CASTest 1, and CASTest 2 (Table 3). Discussion This study investigated the nationwide ALS provider course outcomes in relation with the course and candidate characteristics. Overall, the course pass rate was high, 97%, with a constant rate
over the years and with no difference after the introduction of the 2010 ERC guidelines. A higher level of pre-course resuscitation knowledge, a younger age of the candidates, and being an MD were factors that were associated with higher course pass rates. More specifically, being an MD in an emergency discipline was associated with the highest success rate. Of interest, there was a positive association between fewer instructors, as represented by a higher candidate/instructor ratio, and course success. Finally, courses of longer duration resulted in higher pass rates. Our results confirm earlier observations from a single centre in Italy, where the association between the ALS course outcomes and demographics, professional background, and pre-course knowledge were investigated in 283 candidates.16 In that study, candidates who passed the course were more frequently MDs and of younger age and attained a higher pre-course MCQ score.16
Fig. 2. Outcomes of the ALS provider course (a) and its sub-tests (b), post-course multiple choice quiz (MCQ), and cardiac arrest scenario tests (CASTest 1 and 2) in relation to the candidates’ professional backgrounds (medical doctor (MD) or nurse) and to the medical specialty of the MD candidates. Numbers on the top of the bars represent the course pass and fail rates. White bars, course success; black bars, course failure.
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Table 3 Courses and candidates’ characteristics independently associated with ALS provider course and its sub-tests success. Multivariate OR [95%CI]
p Value
ALS course outcome Candidate’s age (years) Candidates/instructor (ratio) Course duration (3 days) Guideline (2005) Candidate’s role (MD) Pre-course MCQ (score)
0.926 [0.915–0.937] 1.314 [1.067–1.618] 1.717 [1.090–2.703] 0.821 [0.561–1.199] 3.021 [2.212–4.132] 1.033 [1.026–1.040]
<0.0001 0.009 0.019 0.16 <0.0001 <0.0001
Post-course MCQ outcome Candidate’s age (years) Candidates/instructor (ratio) Course duration (3 days) Guideline (2005) Candidate’s role (MD) Pre-course MCQ (score)
0.919 [0.905–0.934] 1.316 [0.919–1.886] 2.886 [1.194–6.976] 0.791 [0.490–1.278] 2.639 [1.754–3.968] 1.038 [1.030–1.047]
<0.0001 0.132 0.018 0.33 <0.0001 <0.0001
CASTest 1 outcome Age candidates (years) Candidates/instructor (ratio) Course duration (3 days) Guideline (2005) Candidate’s role (MD) Pre-course MCQ (score)
0.953 [0.946–0.959] 1.067 [0.923–1.232] 1.162 [0.779–1.732] 1.038 [0.844–1.275] 1.626 [1.376–1.923] 1.025 [1.020–1.029]
<0.0001 0.37 0.37 0.98 <0.0001 <0.0001
CASTest 2 outcome Candidate’s age (years) Candidates/instructor (ratio) Course duration (3 days) Guideline (2005) Candidate’s role (MD) Pre-course MCQ (score)
0.954 [0.937–0.971] 1.118 [0.782–1.597] 2.521 [1.307–4.822] 0.673 [0.472–0.957] 2.725 [1.754–4.237] 1.018 [1.007–1.029]
<0.0001 0.116 0.006 0.027 <0.0001 <0.0001
Multivariate regression analysis. CASTest, cardiac arrest simulation test; MCQ, multiple choice quiz; MD, medical doctor.
However, in contrast with our results, the candidates’ backgrounds were not a predictor of course success. A reason for this discrepancy may be related to the limited number of courses and candidates evaluated compared to our nationwide investigation that enrolled more than 13,000 trainees, including a large variety of healthcare specialties. The course pass rate in our study was high, which is consistent with earlier reports from our country in which 95% of candidates passed the final evaluation.15 In contrast to our results, the failure rates of ALS courses ranged from 40% to 93% in a group of 65 UK course centres.17 Nevertheless, those data referred only to the CASTest 1 and did not include retests. In our study, the specific failure of the CASTest 1 was only 10%. Indeed, two recent investigations enrolling 1446 candidates in the UK and Australia18 and more than 18,000 candidates in the UK19 found a pass rate for the CASTest 1 ranging from 80% to 85%, yielding a final ALS course pass rate, after retests, of approximately 97%, similar to the pass rate reported in the present analysis. The professional background of the candidates has been reported to influence the likelihood of passing the final assessment, with significantly higher pass rates for MDs in comparison to nurses.16,18–20 These data have been confirmed in our population. An explanation for this result might be the relationship between theoretical resuscitation knowledge and professional experience. More specifically, MDs compared to nurses have been reported more confidence in CPR interventions, especially with drug dosage, defibrillation, and ECG rhythm recognition, while nurses are more competent in BLS.21 In earlier investigations, the impact of the professional profile and resuscitation knowledge on course outcomes were anticipated by higher pre-course MCQ scores.16,20
Accordingly, in our study, being an MD and having a high pre-course MCQ score were independent predictors of course success. It is reasonable to expect that clinical experience might improve knowledge and the levels of resuscitation competence.19,22,23 Indeed, nurses and doctors working in high-risk areas for cardiac arrest or encountering more cardiac arrest events have demonstrated greater BLS and ALS theoretical knowledge compared to their colleagues working in lesser exposed areas.7,21,24 Our results are in accordance with the above observations. In fact, a higher ALS provider course pass rate was observed in candidates who were MDs working in an emergency discipline compared to MDs not working in an emergency field. Moreover, among the emergency disciplines, candidates who were anaesthesiologists were the most successful in passing the ALS final assessment; indeed, anaesthesiologists are traditionally responsible for cardiac arrests in Italy and are therefore the most experienced in this setting. Increasing age is another determinant that is associated with a lower probability of passing the final ALS assessment.7,16 The reason for this observation is related to a higher resuscitation knowledge decay among older candidates, concurrent with a physiological decay in learning capabilities, more specifically, in the ‘working memory’.16,25 Indeed, the ALS course requires candidates to learn and maintain a variety of information while dealing with additional incoming stimuli and skills acquisition. This learning process may therefore be more difficult as the candidate age increases. Allowing more time for ALS training would improve memory processing, resulting in improved retention of the new information and skills acquired.19 This hypothesis may explain why in our study, the longer duration ALS course was independently associated with higher course pass rates. Indeed, the 3-day IRC ALS course is structured to have more time spent in repeating and thereby consolidating knowledge concepts and in CAS simulations, allowing for a longer learning curve compared with the 2-day course. The quality and effectiveness of the ALS course have been reported to be largely dependent on the strength of its instructors.5 Unfortunately, there is evidence of considerable inconsistencies amongst ALS instructors, probably due to the variability in performance ratings.5,17,26 Indeed, a recent evaluation of over 10,000 candidates taking the MRCP PACES examination demonstrated that up to 12% of the differences in candidates’ assessments was due to examiner variability in leniency/stringency during observations and the interpretation of errors.27 Accordingly, our study demonstrated that the course director was independently associated with the pass/fail outcome. Perkins et al.28 showed that pairing examiners not only helped in reducing the number of observational errors but also resulted in reduced pass rates. In fact, when examiners disagree on a pass/fail decision they tend to refer the candidates for a re-test.28 This may well explain the apparent contradictory lower course pass rate observed in our study when a higher number of instructors were present. While the candidate/instructors ratio was independently associated with course outcomes, we cannot exclude the presence of other unknown and or unmeasured confounding factors that may have played a role in this result. Current ALS course regulations dictate the need for at least one instructor for every three candidates; nevertheless, previous studies have anticipated that a better ratio may result in a higher retention of knowledge.29,30 From our results, however, the educational quality, reflected in course success, was not improved when more than three instructors per candidate were present. The skills required for ALS are more complex than those for BLS and automated external defibrillation. Therefore, MDs who work in acute areas and candidates who might have been resuscitation team leaders and members are more likely to pass ALS courses.5,6 Nevertheless, this study was not aimed to advise the restriction of ALS courses to practitioners that are regularly involved in the
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management of cardiac arrest patients, re-directing lesser experienced professionals to other course formats, i.e., the Immediate Life Support (ILS) course.31 In contrast, the present study attempts to provide potentially useful information for designing successful ALS courses tailored to specific candidates. Our data may allow instructors to identify, at the beginning of a course, candidates who are at risk of failure and who may need additional teaching/training support. We recognize limitations in the interpretation of our findings. First, skill retention was not investigated.32 Second, data on the course directors’ teaching experiences prior to 2008 were not available, which prevented a more specific investigation of the impact of the director on course outcomes. The above limitations withstanding, the strength of our study is its nationwide scale. More than 13,000 candidates were included, encompassing different professional backgrounds and healthcare specialties. The results are therefore representative of all of the course outcomes and candidate characteristics in Italy and may be translated to the European context. Conclusions Younger age, professional background, and pre-course resuscitation knowledge were the most important predictors of ALS provider course success, together with a higher candidate/instructor ratio and a longer course duration. Conflicts of interest statement FS, GR, and ELC are members of the Executive Committee of the IRC. AS is member of the Scientific Committee of the IRC. AS and GT are members of the IRC Educational Working Group. UO is a paid consultant for all of the statistical analyses. Acknowledgments We thank the ALS working group of the IRC for the data collection. 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. 2015.08.006. References 1. Nolan J, Soar J, Zideman DA, et al. European resuscitation council guidelines for resuscitation 2010 section 1. Executive summary. Resuscitation 2010;81:1219–76. 2. Abella BS, Alvarado JP, Myklebust H, et al. Quality of cardiopulmonary resuscitation during in-hospital cardiac arrest. JAMA 2005;293:305–10. 3. Wik L, Kramer-Johansen J, Myklebust H, et al. Quality of cardiopulmonary resuscitation during out-of-hospital cardiac arrest. JAMA 2005;293: 299–304. 4. Perkins G, Lockey A. The advanced life support provider course. BMJ 2002;325:S81. 5. Nolan JP. Advanced life support training. Resuscitation 2001;50:9–11.
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6. Soar J, Monsieurs KG, Ballance JH, et al. European resuscitation council guidelines for resuscitation 2010 section 9. Principles of education in resuscitation. Resuscitation 2010;81:1434–44. 7. Fischer H, Strunk G, Neuhold S, et al. The effectiveness of ERC advanced life support (ALS) provider courses for the retention of ALS knowledge. Resuscitation 2012;83:227–31. 8. Ringsted C, Lippert F, Hesselfeldt R, et al. Assessment of advanced life support competence when combining different test methods—reliability and validity. Resuscitation 2007;75:153–60. 9. Young R, King L. An evaluation of knowledge and skill retention following an in-house advanced life support course. Nurs Crit Care 2000;5:7–14. 10. Baskett PJ, Nolan JP, Handley A, Soar J, Biarent D, Richmond S; European Resuscitation Council. European Resuscitation Council guidelines for resuscitation 2005. Section 9. Principles of training in resuscitation. Resuscitation. 2005 Dec;67 Suppl 1:S181-9. 11. ERC. ALS Course documents 2010. https://www.erc.edu/index.php/docLibrary/ pl/viewDoc/1753/3/. 12. Carveth SW, Burnap TK, Bechtel J, et al. Training in advanced cardiac life support. JAMA 1976;235:2311–5. 13. Koenker R, Hallock KF. Quantile regression—an introduction. J Econ Perspect 2001;15:143–56. 14. King G, Honaker J, Joseph A, Scheve K. Analyzing incomplete political science data: an alternative algorithm for multiple imputation. Am Polit Sci Rev 2001;95:49–69. 15. Breslow NE, Day NE. Classical methods of analysis of grouped data. In: Breslow NE, Day NE, editors. Statistical methods in cancer research. Volume I—the analysis of CaseControl studies. Lyon: International Agency for Research on Cancer; 1980. p. 122–61. 16. Sandroni C, Gonnella GL, de Waure C, Cavallaro F, La Torre G, Antonelli M. Which factors predict candidate out come in advanced life support courses? A preliminary observational study. Intensive Care Med 2010;36:1521–5. 17. Perkins GD, Davies RP, Stallard N, Bullock I, Stevens H, Lockey A. Advanced life support cardiac arrest scenario test evaluation. Resuscitation 2007;75:484–90. 18. Perkins JD, Kimani PK, Bullock I, et al. Improving the efficiency of advanced life support training. A randomized, controlled trial. Ann Intern Med 2012;157:19–28. 19. Thorne CJ, Lockey AS, Bullock I, Hampshire S, Begum-Ali S, Perkins GD. eLearning in advanced life support—an evaluation by the resuscitation council (UK). Resuscitation 2015, http://dx.doi.org/10.1016/j.resuscitation.2015.02.026. 20. Jensen ML, Hesselfeldt R, Rasmussen MB, et al. Newly graduated doctors’ competence in managing cardiopulmonary arrests assessed using a standardized Advanced Life Support (ALS) assessment. Resuscitation 2008;77:63–8. 21. Passali C, Pantazopoulos I, Dontas I, et al. Evaluation of nurses’ and doctors’ knowledge of basic & advanced life support resuscitation guidelines. Nurse Educ Pract 2011;11:365–9. 22. Noordergraaf G, Be WK, Sabbe M, Diets RF, Noordergraaf A, Van Hemelrijck J. Training needs and qualifications of anaesthesiologists not exposed to ALS. Resuscitation 1999;40:147–60. 23. Napier F, Davies RP, Baldock C, et al. Validation for a scoring system of the ALS cardiac arrest simulation test (CASTest). Resuscitation 2009;80:1034–8. 24. Hopstock LA. Motivation and adult learning: a survey among hospital personnel attending a CPR course. Resuscitation 2008;76:425–30. 25. Grady CL, Craik FI. Changes in memory processing with age. Curr Opin Neurobiol 2000;10:224–31. 26. Perkins GD, Hulme J, Tweed MJ. Variability in the assessment of advanced life support skills. Resuscitation 2001;50:281–6. 27. McManus IC, Thompson M, Mollon J. Assessment of examiner leniency and stringency (‘hawk-dove effect’) in the MRCP(UK) clinical examination (PACES) using multi-facet Rasch modelling. BMC Med Educ 2006;6:42. 28. Perkins GD, Tweed MJ. Evaluation assessment of advanced life support skills: examiner consistency. Med Educ 2001;35:S60, abstract. 29. Chamberlain D, Smith A, Woollard M, et al. Trials of teaching methods in basic life support (3): comparison of simulated CPR performance after first training and at 6 months, with a note on the value of re-training. Resuscitation 2002;53: 179–87. 30. Langhan TS, Rigby IJ, Walker IW, Howes D, Donnon T, Lord JA. Simulation-based training in critical resuscitation procedures improves residents’ competence. CJEM 2009;11:535–9. 31. Soar J, Perkins GD, Harris S, Nolan J. The immediate life support course. Resuscitation 2003;57:21–6. 32. Yang CW, Yen ZS, McGowan JE, et al. A systematic review of retention of adult advanced life support knowledge and skills in healthcare providers. Resuscitation 2012;83:1055–60.
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Simulation and education
Advanced life support provider course in Italy: A 5-year nationwide study to identify the determinants of course success夽 Federico Semeraro a,b,∗ , Andrea Scapigliati a,c,1 , Gaetano Tammaro a,b,2 , Umberto Olcese d,3 , Erga L. Cerchiari a,b,4 , Giuseppe Ristagno a,e,5 a
Italian Resuscitation Council, Bologna, Italy Department of Anaesthesia and Intensive Care, Ospedale Maggiore, Bologna, Italy c Institute of Anaesthesia and Intensive Care, Department of Cardiovascular Sciences, Catholic University of the Sacred Heart, Rome, Italy d Swammerdam Institute for Life Sciences, University of Amsterdam, Amsterdam, The Netherlands e IRCCS-Istituto di Ricerche Farmacologiche “Mario Negri”, Milan, Italy b
a r t i c l e
i n f o
Article history: Received 17 March 2015 Received in revised form 20 July 2015 Accepted 14 August 2015 Keywords: Advanced life support Course Education Database Cardiac arrest
a b s t r a c t Introduction: The advanced life support (ALS) provider course is the gold standard for teaching and assessing competence in advanced resuscitation. Outcomes over a 5-year period of European Resuscitation (ERC)/IRC ALS provider courses in Italy were investigated, and the factors associated with course success are described. Methods: In 2008, the Italian Resuscitation Council (IRC) created a database in which every ERC/IRC ALS course was recorded. Data from courses organized from 2008 to 2012 were analysed. The data included: candidate’s age and degree (medical doctor (MD) or nurse), medical specialty of MD candidates, course outcomes, duration and reference guidelines, number of instructors and course director. Relationships between the course outcomes and the courses and candidates’ characteristics were analysed using logistic regression. Results: A total of 13,624 candidates were evaluated from 871 courses. Among the candidates, 55% were MDs and 45% were nurses. Ninety-seven percent of candidates passed the final evaluation, while 3% failed. Candidates who passed were younger (37 [31–44] vs. 43 [37–50] years, p < 0.0001) and had a greater precourse resuscitation knowledge (multiple choice quiz (MCQ) score: 88 [83–93] vs. 80 [73–87], p < 0.0001) compared to those who failed. The course pass rate was higher for MDs compared to nurses (98% vs. 95%, p < 0.0001) and participants in emergency disciplines were most significantly associated with course success (2 71, p < 0.0001). In the multivariate analysis, an older age (OR 0.926, 95%CI [0.915–0.937]) was independently associated with course failure, while being a MD (OR 3.021, 95%CI [2.212–4.132]), having a higher pre-course MCQ score (OR 1.033, 95%CI [1.026–1.040]) together with a higher candidate/instructor ratio (OR 1.314, 95%CI [1.067–1.618]), and having a longer course duration (OR 1.717, 95%CI [1.090–2.703]), were independently associated with success. Conclusions: Younger age, professional background, and pre-course resuscitation knowledge are the most important predictors of ALS provider course success, together with higher candidate/instructor ratios and longer course durations. © 2015 Elsevier Ireland Ltd. All rights reserved.
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.2015.08.006. ∗ Corresponding author. Present affiliation: Consultant in Anaesthesia and Intensive Care, Maggiore Hospital, Bologna, Italy. Fax: +39 0514189693. E-mail address: [email protected] (F. Semeraro). 1 Present affiliation: Institute of Anaesthesia and Intensive Care, Department of Cardiovascular Sciences, Catholic University of the Sacred Heart, Rome, Italy. 2 Present affiliation: Critical Care Nurse, Maggiore Hospital, Bologna, Italy. 3 Present affiliation: Swammerdam Institute for Life Sciences, University of Amsterdam, Amsterdam, The Netherlands. 4 Present affiliation: Anaesthesia and Intensive Care, Maggiore Hospital, Bologna, Italy. 5 Present affiliation: Istituto di Ricerche Farmacologiche “Mario Negri”—IRCCS, Milano, Italy. http://dx.doi.org/10.1016/j.resuscitation.2015.08.006 0300-9572/© 2015 Elsevier Ireland Ltd. All rights reserved.
F. Semeraro et al. / Resuscitation 96 (2015) 246–251
Introduction The quality of cardiopulmonary resuscitation (CPR) is a major determinant of successful resuscitation.1 However, CPR quality is often poor in clinical settings, and a lack of resuscitation skills in basic and advanced life support (BLS and ALS) can contribute to poor outcomes.2,3 Improvements in CPR knowledge and skills through specific training courses are therefore essential. The ALS provider course is recognized as the gold standard in teaching and assessing competencies in advanced resuscitation for healthcare professionals.4,5 It provides a standardized approach to the management of cardiac arrest, including: manual defibrillation; advanced airway; drug therapy; peri-arrest circumstances; and post-resuscitation care.4,6 Indeed, ALS courses are held in a uniform format throughout Europe by the national resuscitation councils under the auspices of the European Resuscitation Council (ERC). More than 1.5 million healthcare professionals around the world attend ALS provider courses each year.7 A main advantage of the course is the simulation of different cardiac arrest scenarios (CAS), in which candidates practice and interact as members of a potential resuscitation team.5,6 However, the same training format must fit the varying professional backgrounds of the attending professionals who can experience the course as too basic or can become overwhelmed with information and skill requirements.5,8–11 The identification of factors associated with course outcomes might help instructors identify and target candidates’ specific needs. In Italy, the Italian Resuscitation Council (IRC) organizes ERC/IRC ALS courses nationwide in compliance with the ERC guidelines.6,10,11 To oversee the courses and instructors’ activities, in 2008, the IRC created a national database in which course data are recorded, including information on the course itself and on the candidates. The aim of this study was to investigate the outcomes of ALS provider courses in Italy over a 5-year period and to describe the determinants associated with course pass/fail rates. This is a large-scale and multi-centre analysis, including 871 ALS courses nationwide and more than 13,000 candidates.
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of MDs; course outcomes; pre- and post-course multiple choice quiz (MCQ) scores; outcomes of the first CAS testing (CASTest 1) and second (re-test) CASTest (CASTest 2); course duration and reference guidelines (2005 or 2010); candidate/instructor ratio; and course director. Only candidates who attended the ALS provider course for the first time were included in this study. For the analysis, MDs working in the following areas were considered to belong to “emergency” disciplines: anaesthesia and intensive care; cardiology; emergency medical systems; emergency departments; and neonatology. Statistical analysis Categorical variables are presented as proportions, and continuous variables are presented as medians with a range (from min to max) or the interquartile range (IQR). Univariate analysis was employed to investigate the predictors of the ALS course outcomes. For categorical outcomes (ALS, CASTest 1 and 2, and pre/postcourse MCQ scores), Fisher’s exact test or the Chi-square test were used to evaluate their relationship with categorical variables (i.e., specialty), while logistic regression was used for continuous variables (i.e., age). For continuous outcomes (the MCQ score), the Wilcoxon rank sum test and Kruskal–Wallis test were employed to evaluate their relationship with categorical variables, while quantile regressions were used for continuous variables.13 For multivariate analysis, all of the independent variables were entered in the logistic regression model. Goodness of fit was evaluated by comparing the actual and fit values. Because approximately one-third of records lacked a pre-course MCQ score, a multiple imputation method was employed to include the whole dataset in the multivariate analysis.14 The results of the linear regressions are reported in terms of the beta coefficients ± SD, while the results of the multivariate logistic regressions are reported as the odds ratio (OR) with the corresponding 95% confidence interval (CI). Statistical significance was set at p < 0.05.15 Statistical analyses were performed in R (www.r-project.org). Zelig and Amelia packages were employed for multivariate analyses, while the Quantreg package was used for quantile regressions.
Methods Results The study was a retrospective analysis of data recorded in the national IRC ALS course database for administrative and statistical reasons. Candidates were informed of the data collection and provided written consent for their use. The IRC ALS provider course The ERC ALS provider course was devised in 1992.5 It was partly modelled on the Advanced Cardiac Life Support (ACLS) course introduced by the American Heart Association in 1975.12 The ERC/IRC course then significantly evolved into a standardized format with a European-derived manual.6,10,11 Details are in the Supplemental methods. The IRC database
Overall, 13,744 candidates participated in 871 ALS provider courses during the 5-year period. One hundred-thirty-two candidates were excluded due to previous course attendance, while 145 candidates dropped out of the course. Finally, data from 13,264 participants (median age 37) were included in the analyses. Fiftyfive percent of the candidates were MDs, and 45% were nurses (Table 1). Described using medians, there were 179 [min–max, 144–197] courses per year involving 2705 [2348–2891] candidates, 61 [46–67] course directors, and 116 [104–159] new potential instructors.
Table 1 Descriptive of candidates in relationship to ALS provider course outcome. All
The IRC ALS course database was created in 2007 and became operative on January 1st, 2008 (www.ircouncil.it/corsi). All ERC/IRC ALS courses organized in Italy are recorded in the database, including information on the course outcomes, structure, director, and candidates’ characteristics. Course registration in the database is mandatory to obtain ERC/IRC recognition and certifications. For this study, data from 2008 to 2012 were extracted from the database. The data analysed included: the candidates’ age; professional background (medical doctors (MD) or nurses) and specialty
Age (median[IQR]) Candidates, n MD, n Nurses, n Pre-course MCQ, (median[IQR]) Post-course MCQ, (median[IQR])
Pass
Fail
37 [31–44] 13,264 7352 5912 88 [83–93]
37 [31–44] 12,803 7180 5623 88 [83–93]
43 [37-50]* 461 172 289 80 [73-87]*
89 [84–93]
89 [85–93]
72 [60-80]*
MD, medical doctor; IQR, interquartile range; MCQ, multiple choice quiz. * p < 0.0001 vs. Pass.
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F. Semeraro et al. / Resuscitation 96 (2015) 246–251
Fig. 1. ALS provider course outcomes in relation to the course structure (candidate/instructor ratio, duration, and CPR guidelines (GL) used as a reference) and to the candidates’ characteristics (degree and age). Numbers in brackets represent the number of candidates. White bars, course success; black bars, course failure.
Ninety-seven percent of candidates successfully passed the course, with a constant pass rate over the years (min–max, 95–98%). More than 98% of candidates passed the post-course MCQ and 90% passed the CASTest 1; however, of those who underwent a retest, only 68% passed the CASTest 2. The pre-course MCQ score was significantly higher in candidates who passed the course compared to those who failed (p < 0.0001, Table 1). More specifically, in the univariate analysis, higher pre-course MCQ scores were positively correlated with higher pass rates of the ALS course (ˇ 0.0246 ± 0.003, p < 0.0001) and its sub-tests: post-course MCQ (ˇ 0.0282 ± 0.003, p < 0.0001); CASTest 1 (ˇ 0.0184 ± 0.002, p < 0.0001); and CASTest 2 (ˇ 0.0177 ± 0.005, p < 0.0001). Course outcomes in relationship with candidates’ ages, candidate/instructor ratio, changes in the CPR guidelines, course duration, and candidates’ professional backgrounds are reported in Fig. 1. Younger candidates had higher percentages of passed courses and their sub-tests (p < 0.0001, Fig. 1 and Table 2). Indeed, increasing age was inversely correlated with course success, as represented by the negative ˇ in the univariate analysis: ˇ −0.0596 ± 0.005, for the ALS course (p < 0.0001); ˇ −0.0674 ± 0.07, for the post-course MCQ (p < 0.0001); ˇ −0.0374 ± 0.003, for the CASTest 1 (p < 0.0001); and ˇ −0.0445 ± 0.007, for the CASTest 2 (p < 0.0001). A greater rate of success was observed in courses with a lower number of instructors compared to those with a higher number of instructors (Fig. 1 and Table 2). Indeed, in the univariate analysis, a higher candidate/instructor ratio was positively correlated with a higher likelihood of passing the ALS course (ˇ 0.2217 ± 0.084, p = 0.009), the post-course MCQ (ˇ 0.2350 ± 0.109, p = 0.031), and the CASTest 2 (ˇ 0.2927 ± 0.108, p = 0.006), but not the CASTest 1 (ˇ 0.0168 ± 0.049, p = 0.736). Courses based on the 2005 CPR guidelines had a higher pass rate compared with those based on the 2010 guidelines (97% vs. 96%, OR 1.230, 95%CI [1.016–1.488], p = 0.03) (Fig. 1 and Table 2). More specifically, the 2005 guidelines were associated with positive outcomes at the post-course MCQ (OR 1.279, 95%CI [0.999–1.638], p = 0.048), but not at the CASTest 1 (OR 1.098, 95%CI [0.977–1.234],
p = 0.11) or the CASTest 2 (OR 1.253, 95%CI [0.980–1.602], p = 0.067). The course duration, 2 vs. 3 days, was not associated with differences in the course outcomes in univariate analysis (Fig. 1 and Table 2). Ninety-eight percent of MDs passed the course compared to 95% of nurses (p < 0.0001, Table 1 and Fig. 1). The percentage of MDs who passed the post-course MCQ, CASTest 1, and CASTest 2 was also significantly higher compared to the percentage of nurses who passed (p < 0.0001, Table 2). Being an MD was associated with a higher pass rate in the ALS course (OR 2.146, 95%CI [1.764–2.618], p < 0.0001) and its sub-tests: the post-test MCQ (OR 2.545, 95%CI [1.965–3.322], p < 0.0001), the CASTest 1 (OR 1.389, 95%CI [1.238–1.560], p < 0.0001), and the CASTest 2 (OR 1.852, 95%CI [1.443–2.381], p < 0.0001). MDs working in “emergency” disciplines passed the overall ALS course and its sub-tests at significantly higher rates compared to candidate MDs working in other disciplines (surgery or medicine) and compared to nurses (p < 0.05, Fig. 2). Indeed, the “emergency” disciplines were significantly associated with overall positive outcomes in the ALS course (2 71, p < 0.0001), the posttest MCQ (2 60, p < 0.0001), the CASTest 1 (2 52, p < 0.0001) and the CASTest 2 (2 26, p < 0.0001). Among the specialties included in the “emergency” disciplines, anaesthesiology was the most significantly associated with course success: 2 206, for the overall ALS course (p < 0.0001); 2 180, for the post-course MCQ (p < 0.0001); 2 230, for the CASTest 1 (p < 0.0001); and 2 101, for the CASTest2 (p < 0.0001). The outcomes of the ALS courses stratified by the different healthcare specialties are detailed in the Supplemental Figure. Finally, the proportion of candidates passing the course varied between different course directors, with a pass rate per director of 98.1% [min–max, 84–100%]. Thus, the course director was significantly associated with the course outcome; indeed, the 2 was 487 (p < 0.0001), for the ALS outcome; 483 (p < 0.0001), for the post-course MCQ; 556 (p < 0.0001), for the CASTest 1; and 226 (p < 0.0001), for the CASTest 2.
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Table 2 ALS provider course sub-tests outcome in relationship to course structure and candidate’s characteristics. Post-course MCQ
CASTest 1
CASTest 2
Candidates (n)
Pass (%)
Fail (%)
Pass (%)
Fail (%)
Pass (%)
Fail (%)
Age (quartiles) ≤30 31–36 37–43 ≥44
2990 3204 3480 3588
89 90 88 88 p < 0.0001
11 10 12 12
94 92 89 86 p < 0.0001
6 8 11 14
84 74 69 59 p < 0.0001
16 26 31 41
Degree MD Nurse
7352 5912
99 97 p < 0.0001
1 3
91 88 p < 0.0001
9 12
75 62 p < 0.0001
25 38
Course duration 2 day 3 day
1535 11,729
98 98 p = 0.44
2 2
90 90 p = 0.68
10 10
65 69 p = 0.44
35 31
Guidelines 2005 2010
7620 5644
98 98 p = 0.05
2 2
90 90 p = 0.11
10 10
70 66 p = 0.07
30 34
Candidates/instructor ratio 1 2 3 4 5 6
54 2582 8596 1819 170 43
83 88 89 89 88 96 p = 0.03
17 12 11 11 12 4
91 90 90 90 92 84 p = 0.74
9 10 10 10 8 16
40 60 70 76 62 83 p = 0.006
60 40 30 24 38 17
MD, medical doctor; MCQ, multiple choice quiz; CASTest, cardiac arrest scenario test.
In the multivariate analysis, the factors independently associated with ALS course success were a younger age, higher candidate/instructor ratio, longer duration of the course (3 days), being an MD, and having a higher pre-course MCQ score (Table 3). Changes in the CPR guidelines were not independently associated with the course pass rates. Younger age, being an MD, and a higher pre-course MCQ score were also independently associated with the success of the course sub-tests, including the post-course MCQ, CASTest 1, and CASTest 2 (Table 3). Discussion This study investigated the nationwide ALS provider course outcomes in relation with the course and candidate characteristics. Overall, the course pass rate was high, 97%, with a constant rate
over the years and with no difference after the introduction of the 2010 ERC guidelines. A higher level of pre-course resuscitation knowledge, a younger age of the candidates, and being an MD were factors that were associated with higher course pass rates. More specifically, being an MD in an emergency discipline was associated with the highest success rate. Of interest, there was a positive association between fewer instructors, as represented by a higher candidate/instructor ratio, and course success. Finally, courses of longer duration resulted in higher pass rates. Our results confirm earlier observations from a single centre in Italy, where the association between the ALS course outcomes and demographics, professional background, and pre-course knowledge were investigated in 283 candidates.16 In that study, candidates who passed the course were more frequently MDs and of younger age and attained a higher pre-course MCQ score.16
Fig. 2. Outcomes of the ALS provider course (a) and its sub-tests (b), post-course multiple choice quiz (MCQ), and cardiac arrest scenario tests (CASTest 1 and 2) in relation to the candidates’ professional backgrounds (medical doctor (MD) or nurse) and to the medical specialty of the MD candidates. Numbers on the top of the bars represent the course pass and fail rates. White bars, course success; black bars, course failure.
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Table 3 Courses and candidates’ characteristics independently associated with ALS provider course and its sub-tests success. Multivariate OR [95%CI]
p Value
ALS course outcome Candidate’s age (years) Candidates/instructor (ratio) Course duration (3 days) Guideline (2005) Candidate’s role (MD) Pre-course MCQ (score)
0.926 [0.915–0.937] 1.314 [1.067–1.618] 1.717 [1.090–2.703] 0.821 [0.561–1.199] 3.021 [2.212–4.132] 1.033 [1.026–1.040]
<0.0001 0.009 0.019 0.16 <0.0001 <0.0001
Post-course MCQ outcome Candidate’s age (years) Candidates/instructor (ratio) Course duration (3 days) Guideline (2005) Candidate’s role (MD) Pre-course MCQ (score)
0.919 [0.905–0.934] 1.316 [0.919–1.886] 2.886 [1.194–6.976] 0.791 [0.490–1.278] 2.639 [1.754–3.968] 1.038 [1.030–1.047]
<0.0001 0.132 0.018 0.33 <0.0001 <0.0001
CASTest 1 outcome Age candidates (years) Candidates/instructor (ratio) Course duration (3 days) Guideline (2005) Candidate’s role (MD) Pre-course MCQ (score)
0.953 [0.946–0.959] 1.067 [0.923–1.232] 1.162 [0.779–1.732] 1.038 [0.844–1.275] 1.626 [1.376–1.923] 1.025 [1.020–1.029]
<0.0001 0.37 0.37 0.98 <0.0001 <0.0001
CASTest 2 outcome Candidate’s age (years) Candidates/instructor (ratio) Course duration (3 days) Guideline (2005) Candidate’s role (MD) Pre-course MCQ (score)
0.954 [0.937–0.971] 1.118 [0.782–1.597] 2.521 [1.307–4.822] 0.673 [0.472–0.957] 2.725 [1.754–4.237] 1.018 [1.007–1.029]
<0.0001 0.116 0.006 0.027 <0.0001 <0.0001
Multivariate regression analysis. CASTest, cardiac arrest simulation test; MCQ, multiple choice quiz; MD, medical doctor.
However, in contrast with our results, the candidates’ backgrounds were not a predictor of course success. A reason for this discrepancy may be related to the limited number of courses and candidates evaluated compared to our nationwide investigation that enrolled more than 13,000 trainees, including a large variety of healthcare specialties. The course pass rate in our study was high, which is consistent with earlier reports from our country in which 95% of candidates passed the final evaluation.15 In contrast to our results, the failure rates of ALS courses ranged from 40% to 93% in a group of 65 UK course centres.17 Nevertheless, those data referred only to the CASTest 1 and did not include retests. In our study, the specific failure of the CASTest 1 was only 10%. Indeed, two recent investigations enrolling 1446 candidates in the UK and Australia18 and more than 18,000 candidates in the UK19 found a pass rate for the CASTest 1 ranging from 80% to 85%, yielding a final ALS course pass rate, after retests, of approximately 97%, similar to the pass rate reported in the present analysis. The professional background of the candidates has been reported to influence the likelihood of passing the final assessment, with significantly higher pass rates for MDs in comparison to nurses.16,18–20 These data have been confirmed in our population. An explanation for this result might be the relationship between theoretical resuscitation knowledge and professional experience. More specifically, MDs compared to nurses have been reported more confidence in CPR interventions, especially with drug dosage, defibrillation, and ECG rhythm recognition, while nurses are more competent in BLS.21 In earlier investigations, the impact of the professional profile and resuscitation knowledge on course outcomes were anticipated by higher pre-course MCQ scores.16,20
Accordingly, in our study, being an MD and having a high pre-course MCQ score were independent predictors of course success. It is reasonable to expect that clinical experience might improve knowledge and the levels of resuscitation competence.19,22,23 Indeed, nurses and doctors working in high-risk areas for cardiac arrest or encountering more cardiac arrest events have demonstrated greater BLS and ALS theoretical knowledge compared to their colleagues working in lesser exposed areas.7,21,24 Our results are in accordance with the above observations. In fact, a higher ALS provider course pass rate was observed in candidates who were MDs working in an emergency discipline compared to MDs not working in an emergency field. Moreover, among the emergency disciplines, candidates who were anaesthesiologists were the most successful in passing the ALS final assessment; indeed, anaesthesiologists are traditionally responsible for cardiac arrests in Italy and are therefore the most experienced in this setting. Increasing age is another determinant that is associated with a lower probability of passing the final ALS assessment.7,16 The reason for this observation is related to a higher resuscitation knowledge decay among older candidates, concurrent with a physiological decay in learning capabilities, more specifically, in the ‘working memory’.16,25 Indeed, the ALS course requires candidates to learn and maintain a variety of information while dealing with additional incoming stimuli and skills acquisition. This learning process may therefore be more difficult as the candidate age increases. Allowing more time for ALS training would improve memory processing, resulting in improved retention of the new information and skills acquired.19 This hypothesis may explain why in our study, the longer duration ALS course was independently associated with higher course pass rates. Indeed, the 3-day IRC ALS course is structured to have more time spent in repeating and thereby consolidating knowledge concepts and in CAS simulations, allowing for a longer learning curve compared with the 2-day course. The quality and effectiveness of the ALS course have been reported to be largely dependent on the strength of its instructors.5 Unfortunately, there is evidence of considerable inconsistencies amongst ALS instructors, probably due to the variability in performance ratings.5,17,26 Indeed, a recent evaluation of over 10,000 candidates taking the MRCP PACES examination demonstrated that up to 12% of the differences in candidates’ assessments was due to examiner variability in leniency/stringency during observations and the interpretation of errors.27 Accordingly, our study demonstrated that the course director was independently associated with the pass/fail outcome. Perkins et al.28 showed that pairing examiners not only helped in reducing the number of observational errors but also resulted in reduced pass rates. In fact, when examiners disagree on a pass/fail decision they tend to refer the candidates for a re-test.28 This may well explain the apparent contradictory lower course pass rate observed in our study when a higher number of instructors were present. While the candidate/instructors ratio was independently associated with course outcomes, we cannot exclude the presence of other unknown and or unmeasured confounding factors that may have played a role in this result. Current ALS course regulations dictate the need for at least one instructor for every three candidates; nevertheless, previous studies have anticipated that a better ratio may result in a higher retention of knowledge.29,30 From our results, however, the educational quality, reflected in course success, was not improved when more than three instructors per candidate were present. The skills required for ALS are more complex than those for BLS and automated external defibrillation. Therefore, MDs who work in acute areas and candidates who might have been resuscitation team leaders and members are more likely to pass ALS courses.5,6 Nevertheless, this study was not aimed to advise the restriction of ALS courses to practitioners that are regularly involved in the
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management of cardiac arrest patients, re-directing lesser experienced professionals to other course formats, i.e., the Immediate Life Support (ILS) course.31 In contrast, the present study attempts to provide potentially useful information for designing successful ALS courses tailored to specific candidates. Our data may allow instructors to identify, at the beginning of a course, candidates who are at risk of failure and who may need additional teaching/training support. We recognize limitations in the interpretation of our findings. First, skill retention was not investigated.32 Second, data on the course directors’ teaching experiences prior to 2008 were not available, which prevented a more specific investigation of the impact of the director on course outcomes. The above limitations withstanding, the strength of our study is its nationwide scale. More than 13,000 candidates were included, encompassing different professional backgrounds and healthcare specialties. The results are therefore representative of all of the course outcomes and candidate characteristics in Italy and may be translated to the European context. Conclusions Younger age, professional background, and pre-course resuscitation knowledge were the most important predictors of ALS provider course success, together with a higher candidate/instructor ratio and a longer course duration. Conflicts of interest statement FS, GR, and ELC are members of the Executive Committee of the IRC. AS is member of the Scientific Committee of the IRC. AS and GT are members of the IRC Educational Working Group. UO is a paid consultant for all of the statistical analyses. Acknowledgments We thank the ALS working group of the IRC for the data collection. 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. 2015.08.006. References 1. Nolan J, Soar J, Zideman DA, et al. European resuscitation council guidelines for resuscitation 2010 section 1. Executive summary. Resuscitation 2010;81:1219–76. 2. Abella BS, Alvarado JP, Myklebust H, et al. Quality of cardiopulmonary resuscitation during in-hospital cardiac arrest. JAMA 2005;293:305–10. 3. Wik L, Kramer-Johansen J, Myklebust H, et al. Quality of cardiopulmonary resuscitation during out-of-hospital cardiac arrest. JAMA 2005;293: 299–304. 4. Perkins G, Lockey A. The advanced life support provider course. BMJ 2002;325:S81. 5. Nolan JP. Advanced life support training. Resuscitation 2001;50:9–11.
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