Board 173 - Program Innovations Abstract Transfer into the Practice of the ACRM Principles after a Clinical Simulation Course (Submission #1317)
Bibliographic record
Abstract
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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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.291 | 0.064 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".