Board 280 - Program Innovations Abstract Interprofessional Education for Pediatric Resuscitation in the PACU using High-Fidelity Simulation in a Tertiary Care Pediatric Hospital (Submission #63)
Notice bibliographique
Résumé
Introduction/Background Life-threatening pediatric emergencies in the post-anesthesia care unit (PACU) are infrequent but challenging for the staff, even in a tertiary care pediatric hospital. These high stakes situations require both medical knowledge and effective team crisis resource management (CRM): leadership, situation awareness, communication, team-work, planning, resource management and decision making. Simulation-based team training has been shown to be effective in improving these cognitive and non-technical skills In our institution, we introduced a monthly one hour training course using high-fidelity simulation-based training in order to optimize teamwork and efficiency in pediatric resuscitation in the PACU. This training was designed for staff pediatric anesthesiologists, PACU nurses and operating room respiratory therapists working in a tertiary care pediatric hospital. Methods Prior to each session, participants were given didactic material including PALS algorithms 2 and recommendations for team work in the context of CRM.3 Each training session consisted of two high-fidelity simulation scenarios based on real life events. The break down was two 10 minute high-fidelity simulations using Sim Baby(Laerdal) followed by a 20 minute interprofessional debriefing session. The first scenario focused on pulseless electrical activity secondary to severe hypoglycemia in a three month old, 3.5 kg ex-premie. The second scenario focused on ventricular arrythmias in the context of local anesthetic toxicity in a 14 month old child, post neuroblastoma resection with a thoracic epidural. The emphasis during debriefing was placed on : 1) Medical skills: PALS algorithm in the PACU context; 2) CRM principles : situational awareness, communication, decision making, task management and team work during a life threatening event in the PACU. Participants for each session included two staff anesthesiologists, two PACU nurses and two OR respiratory therapists. An evaluation survey was completed by the participants at the end of each session. Results: Conclusion After a 12 month period, 16 anesthesiologists (80%), 14 PACU nurses (100%) and 17 respiratory therapists (80%) participated in the course. Results from the post-course questionnaire : 1) Despite the wide range of clinical experience (less than 5 years to over 35 years), all the participants (anesthesiologists, nurses and respiratory therapists) really enjoyed the session, especially the opportunity to work together on rare but life threatening situations. Participants from all three professions reported that they most benefited from the CRM principles taught in the course, although the PALS review was also cited as being an important aspect. After the session most participants stated that they felt more confident in dealing with similar types of situations. This interprofessional training course was aimed at teams who are used to working together. It allowed participants to discuss both challenges surrounding communication and team work, in addition to the medical complexities. The principles evoked during this type of simulation-based training may be valuable in real life emergency situations. As this course was well received by the participants of all three professions, the future directions for this course include expanding to all the professionals involved in perioperative care and introducing objective measures of team performance. References 1. Fehr JJ, Honkanen A, Murray DJ : Simulation in pediatric anesthesiology. Pediatric Anesthesia 2012 ; 22 :988-94. 2. Kleinman ME, Chameides L, Schexnayder SM, Samson RA, Hazinski MF, Atkins DL et. Al. : Pediatric Advanced Life Support:: 2010 American Heart Association Guidelines for Cardiopulmonary Resuscitation and Emergency Cardiovascular Care. Circulation 2010 ; 122 : S876-S908. 3. American heart Association : Effective Resuscitation Team Dynamics, Pediatric Advanced Life Support Provider Manual, First American Heart Association printing, 2011, pp 31-5. Disclosures None.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
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 | 0,002 | 0,004 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| 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) | 0,116 | 0,016 |
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 ».