183: High Fidelity Simulation Results in Improving Clinician Performance in the Management of Massive Hemorrhage Cases
Notice bibliographique
Résumé
A massive haemorrhage can be a rare but serious complication of paediatric trauma and obstetrical cases. In order to optimize the management of massive haemorrhages, a protocol was implemented at our centre. However, recent audits showed that necessary improvements were to be made to many aspects of its application. To evaluate the application of a massive hemorrhage protocol and the ability to work in interdisciplinary teams using simulation and targeted training. We also aimed to evaluate confidence levels of different team members to apply the protocol and to hold their role in an interdisciplinary team during a crisis situation. Prospective observational study held at the simulation lab of a tertiary mother-child health care facility. Participants were nurses, respiratory technicians, orderlies, anesthetists, obstetricians, pediatric emergency physicians, pediatric intensivists and hematologists. Pediatric emergency/intensive care and obstetrical/anesthesia teams were submitted to high fidelity simulated pediatric trauma and post-partum massive hemorrhage scenarios respectively (Simbaby (Laerdal) and Noelle (Gaumard)). Each participant was asked to hold their usual role in an interdisciplinary team. Targeted training consisted of a debriefing session and a presentation reviewing the massive hemorrhage protocol as well as teamwork skills. All sessions were videotaped. Documents were given during the first session for future references and to prepare for the post session two weeks later. Confidence questionnaires were filled out during both sessions. Four blinded independent trained raters reviewed the videos and assessment was done using a checklist derived from the protocol and the Mayo High Performance Teamwork Scale. Means and standard deviations of scores for performances were calculated for each scenario and compared using an ANOVA test. Descriptive statistics for the confidence questionnaires were compared using a Mann Whitney test. A total of 62 healthcare professionals involved in eight interdisciplinary teams (four obstetrics/anaesthesia and four paediatric emergency/intensive care) as well as eight blood bank technologists and eight haematologists participated in the study. Following training, scores for the application of the protocol improved by 24% (95% CI 10 to 39). Scores for the ability to work in teams improved by 17% (95% CI 6 to 28). Confidence levels in the ability to apply the protocol and work in teams improved by 13% (95% CI 11 to 16). Targeted training involving HF simulated scenarios and protocol review improved participant ability to apply the massive haemorrhage protocol and to work in interdisciplinary teams. Confidence levels improved among participants from all disciplines.
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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 | 0,004 | 0,031 |
| 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 | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,004 | 0,001 |
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 ».