Nicolas Mpotos1, Karel Decaluwe2, Vincent Van Belleghem3, Nick Cleymans4, Joris Raemaekers5, Anselme Derese6, Bram De Wever7, Martin Valcke8, Koenraad G Monsieurs9. 1. Emergency Department, Ghent University Hospital, De Pintelaan 185, B-9000 Ghent, Belgium; Faculty of Medicine and Health Sciences, Ghent University, De Pintelaan 185, B-9000 Ghent, Belgium; Faculty of Medicine and Health Sciences, University of Antwerp, Universiteitsplein 1, B-2610 Wilrijk, Belgium. Electronic address: nicolas.mpotos@ugent.be. 2. Emergency Department, AZ Groeninge, Loofstraat 43, B-8500 Kortrijk, Belgium. Electronic address: karel.decaluwe@azgroeninge.be. 3. Emergency Department, AZ Groeninge, Loofstraat 43, B-8500 Kortrijk, Belgium. Electronic address: Vincent.vanbelleghem@azgroeninge.be. 4. Faculty of Medicine and Health Sciences, Ghent University, De Pintelaan 185, B-9000 Ghent, Belgium. Electronic address: nick.cleymans@ugent.be. 5. Faculty of Medicine and Health Sciences, Ghent University, De Pintelaan 185, B-9000 Ghent, Belgium. Electronic address: joris.raemaekers@ugent.be. 6. Faculty of Medicine and Health Sciences, Ghent University, De Pintelaan 185, B-9000 Ghent, Belgium. Electronic address: anselme.derese@ugent.be. 7. Department of Educational Studies, Ghent University, H. Dunantlaan 2, B-9000 Ghent, Belgium. Electronic address: bram.dewever@ugent.be. 8. Department of Educational Studies, Ghent University, H. Dunantlaan 2, B-9000 Ghent, Belgium. Electronic address: martin.valcke@ugent.be. 9. Faculty of Medicine and Health Sciences, Ghent University, De Pintelaan 185, B-9000 Ghent, Belgium; Emergency Department, Antwerp University Hospital, Wilrijkstraat 10, B-2650 Edegem, Belgium; Faculty of Medicine and Health Sciences, University of Antwerp, Universiteitsplein 1, B-2610 Wilrijk, Belgium. Electronic address: koen.monsieurs@ugent.be.
Abstract
OBJECTIVES: To investigate the effect of automated testing and retraining on the cardiopulmonary resuscitation (CPR) competency level of emergency nurses. METHODS: A software program was developed allowing automated testing followed by computer exercises based on the Resusci Anne Skills Station™ (Laerdal, Norway). Using this system, the CPR competencies of 43 emergency nurses (mean age 37 years, SD 11, 53% female) were assessed. Nurses passed the test if they achieved a combined score consisting of ≥70% compressions with depth ≥50 mm and ≥70% compressions with complete release (<5 mm) and a mean compression rate between 100 and 120/min and ≥70% bag-valve-mask ventilations between 400 and 1000 ml. Nurses failing the test received automated feedback and feedforward on how to improve. They could then either practise with computer exercises or take the test again without additional practise. Nurses were expected to demonstrate competency within two months and they were retested 10 months after baseline. RESULTS: At baseline 35/43 nurses failed the test. Seven of them did not attempt further testing/practise and 7 others did not continue until competency, resulting in 14/43 not competent nurses by the end of the training period. After ten months 39 nurses were retested. Twenty-four nurses failed with as most common reason incomplete release. CONCLUSION: Automated testing with feedback was effective in detecting nurses needing CPR retraining. Automated training and retesting improved skills to a predefined pass level. Since not all nurses trained until success, achieving CPR competence remains an important individual and institutional motivational challenge. Ten months after baseline the combined score showed important decay, highlighting the need for frequent assessments.
OBJECTIVES: To investigate the effect of automated testing and retraining on the cardiopulmonary resuscitation (CPR) competency level of emergency nurses. METHODS: A software program was developed allowing automated testing followed by computer exercises based on the Resusci Anne Skills Station™ (Laerdal, Norway). Using this system, the CPR competencies of 43 emergency nurses (mean age 37 years, SD 11, 53% female) were assessed. Nurses passed the test if they achieved a combined score consisting of ≥70% compressions with depth ≥50 mm and ≥70% compressions with complete release (<5 mm) and a mean compression rate between 100 and 120/min and ≥70% bag-valve-mask ventilations between 400 and 1000 ml. Nurses failing the test received automated feedback and feedforward on how to improve. They could then either practise with computer exercises or take the test again without additional practise. Nurses were expected to demonstrate competency within two months and they were retested 10 months after baseline. RESULTS: At baseline 35/43 nurses failed the test. Seven of them did not attempt further testing/practise and 7 others did not continue until competency, resulting in 14/43 not competent nurses by the end of the training period. After ten months 39 nurses were retested. Twenty-four nurses failed with as most common reason incomplete release. CONCLUSION: Automated testing with feedback was effective in detecting nurses needing CPR retraining. Automated training and retesting improved skills to a predefined pass level. Since not all nurses trained until success, achieving CPR competence remains an important individual and institutional motivational challenge. Ten months after baseline the combined score showed important decay, highlighting the need for frequent assessments.
Authors: Kristoffer Sand; Anna Ulstein Guldal; Tor Åge Myklebust; Dag Arne Lihaug Hoff; Per Christian Juvkam; Torstein Hole Journal: Resusc Plus Date: 2021-08-19