Board 173 - Program Innovations Abstract Transfer into the Practice of the ACRM Principles after a Clinical Simulation Course (Submission #1317)
Notice bibliographique
Résumé
Introduction/Background Currently, the formation of anesthesia and CPR specialists considers as part of its curriculum the acquisition of attitudinal competences developing skills in: communication, leadership, decision making, teamwork and conflict resolution in crisis situations, which may reduce the occurrence of adverse outcomes and legal problems, in addition to shortening the learning curves in acquiring these skills. The present work describes the development of the first ACRM course in Chile, based in high fidelity clinical simulation for anesthesia residents at Diego Portales University. The objective is to describe the development of the first ACRM course in Chile and evaluate the teaching quality provided and the perceived non-technical skills attainment. Methods A course was organized into two, five hour blocks for 18 first and second year anesthesia residents divided into five groups. Prior to the beginning of the course, each of the participants received documents for self-study about ACRM. Each activity block was formally carried out with high fidelity simulation and debriefing for four participants and it considered four scenarios validated by the University of Western Ontario. The assessment of the simulation day was performed using the Debriefing Assessment Simulation in Healthcare ("DASH"®) instrument, in its Spanish version for students. Achieved long term non-technical skills assessment was performed at eight months post-course using the Spanish version of the "Anesthetics Non-Technical Skills" (ANTS) instrument. The Spanish version of the ANTS and DASH instruments, were developed by the researchers who conducted the process of semantic validation using the Delphi methodology. The analysis was performed using the SPSS18 software. All of the participants had a 100% attendance to the scheduled activities and performed scenarios recommended by the American Society of Anesthesia (ASA) for ACRM courses. The DASH assessment showed a high valuation in all elements and descriptors (average grade 6.7), with a lower relative valuation related to the use of audiovisual systems (average grade 5.6). The ANTS evaluation was answered by 15 out of the 18 participants (error rate of 10.6% for 95% of IC). The categories with the best improvement perception correspond to decision making and task handling (77% and 81% of the students, respectively). In the teamwork field, there is a good observation in 69% of the students, with significant differences in the valuation of the different elements that form this category. The situational awareness item was the one that showed the least improvement attained with a 56%. The evaluation showed an improvement perception with regards to knowledge and handling of the situation when they faced real life situations in daily practice. Results: Conclusion Incorporating ACRM courses in initial training levels for the formation of anesthesia specialists, provides major tools for the development of non-technical skills in these professionals, within a safe and positive environment according to the valuations obtained using the DASH instrument. The improving perception is high, however, probably due to the lack of experience and with the need of strengthening their own knowledge of the specialty, advanced training courses may have a greater impact on the participants. This is the first experience we have had in Chile with this type of course in anesthesia residents. References 1. Anaesthetists’ Non-Technical Skills (ANTS) System Handbook v1.0. Scottish Clinical Simulation Centre . University of Aberdeen. 2012. 2. G. Fletcher, R. Flin: Anaesthetists’ Non-Technical Skills (ANTS): evaluation of a behavioural marker system. British Journal of Anaesthesia 2003; 90 (5): 580-8. 3. Graham, J.; Hocking, G.; Giles, E: Anaesthesia Non-Technical Skills: can anaesthetists be trained to reliably use this behavioural marker system in 1 day?British Journal of Anaesthesia 2010 ; 104(4) : 440-445. 4. D. M. Gaba : Crisis resource management and teamwork training in anaesthesia Editorial II. British Journal of Anaesthesia 2010 ;105(1), 3-6. 5. David M. Gaba,Steven K. Howard, Kevin J. Fish :Simulation-based training in anesthesia crisis resource management (ACRM): A decade of experience.Simulation & Gaming,2001 ; 32 (2), 175-193. 6. Blum RH, Raemer DB, Carroll JS, Sunder N, Felstein DM, Cooper JB: . Crisis resource management training for an anaesthesia faculty: a new approach to continuing education. Med Educ.2004 ;38(1):45-55. 7. Weller J, Wilson L, Robinson B: Survey of change in practice following simulation-based training in crisis management Anaesthesia, 2003 ; 58 (5):471-3. 8. Blum RH, Raemer DB, Carroll JS, Dufresne RL, Cooper JB: A method for measuring the effectiveness of simulation-based team training for improving communication skills Anesth Analg.2005;100(5):1375-80. Disclosures None.
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,004 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,002 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,291 | 0,064 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».