Advanced life support cardiac arrest scenario test evaluation.
BACKGROUND
The cardiac arrest scenario test (CASTest) is a central component of the assessment strategy on the Advanced Life Support Course. The aim of this study was to establish equivalence between the four different CASTest scenarios and investigate the impact of profession, candidate order and course centre on the pass rate.


METHODS
This was a cluster randomised study. CASTest scenarios were randomly allocated to candidates stratified by course centre. Candidate demographics and performance were recorded on the criterion referenced check list along with the final assessment outcome (pass/fail). Differences in pass rates according scenario; profession, course centre and candidate order were examined by Chi-squared and multiple logistic regression.


RESULTS
Two thousand, four hundred and forty-nine assessments from 65 course centres were evaluated. There was no difference in pass rate between scenarios (average pass rate 74.4%). Pass rates according to course centre varied widely (40-93%, P<0.0001) as did professional group (42-100%, P<0.0001). The order that candidates took the test did not influence the pass rate.


CONCLUSIONS
The CASTest assessment scenarios used during ALS testing appear equivalent in terms of difficulty. In contrast, the professional background of the candidate and centre at which the assessment is performed do significantly influence the likelihood of passing the assessment. Further evaluation of the reasons for differences between course centres is required.
Perkins
Gavin D
GD
Warwick Medical School, University of Warwick, Warwick CV4 4AL, United Kingdom. gavin.perkins@virgin.net
Davies
Robin P
RP
Stallard
Nigel
N
Bullock
Ian
I
Stevens
Harry
H
Lockey
Andrew
A
D022561:Advanced Cardiac Life Support / Q000193:education*; D016000:Cluster Analysis; D004517:Education, Professional / Q000706:statistics & numerical data; D006323:Heart Arrest / Q000628:therapy*; D006801:Humans; D018794:Problem-Based Learning / Q000379:methods* / Q000706:statistics & numerical data; D011361:Professional Competence; D015203:Reproducibility of Results