Board 372 - Research Abstract The Other End
Notice bibliographique
Résumé
Introduction/Background Massive hemorrhages are infrequent but life threatening complications of pediatric trauma and obstetrical cases. Expertise and effective communication is key among all team members actively involved in managing such events. Collaboration with blood bank technologists and hematologists responsible in assisting the team with prompt preparation and delivery of blood products further contributes to optimal patient care. We aimed to evaluate communication skills and expertise when preparing and delivering blood products in cases of massive haemorrhages using in-situ simulation and telemedicine. Methods Prospective observational study held at the blood bank and simulation lab of a tertiary mother-child health care facility in 2012. Participants were nurses, respiratory technicians, anesthetists, obstetricians, emergency physicians, intensivists, hematologists and blood bank technologists. Pediatric emergency/intensive care and obstetrical/anesthesia teams were submitted to high fidelity (HF) simulated pediatric trauma and post-partum massive hemorrhage scenarios respectively (SimbabyTM (Laerdal) and NoelleTM (Gaumard)) in the simulation lab. Concomitantly, blood bank technologists were videotaped and telephone conversations between participants at the simulation lab and blood bank technologists were recorded for review. If hematologists were consulted, they were called back by the blood bank chief technologist and were asked to answer questions relevant to the application of the massive hemorrhage protocol (MHP). Prior to the first simulation, blood bank technologists were asked to read the MHP and were individually met to answer questions. The MHP was explained to the hematologists during a formal group presentation and they had access to it at any time during the course of the study. All participants were observed initially and during the post session, two weeks later. A blinded independent trained rater reviewed all sessions and assessed performances. Blood bank technologists were evaluated using a checklist derived by transfusion experts rating expertise and key communication skills necessary when preparing and delivering blood products to teams involved in massive haemorrhages. Haematologists were evaluated using a questionnaire developed by transfusion security experts exploring their ability to assist and communicate with blood bank technologists and clinicians when dealing with the choice of blood products or compatibility issues. Means and standard deviations of scores on checklists and questionnaires were calculated for all observations. Results A total of 8 blood bank technologists, 8 haematologists and 62 healthcare professionals involved in 8 interdisciplinary teams (4 obstetrics/anaesthesia and 4 paediatric emergency/intensive care) participated in the study. Blood bank technologists scored on average 78% (range 61%-92%) and 76% (range 62 to 100%) in expertise and communication skills checklists during trauma and post-partum simulations, respectively. Haematologists rightly refused blood specimens to determine blood type in 57% (4/7) of the cases (discrepant ABO/Rh blood group with previous ABO group Results). Their ability to choose blood products or to substitute them was observed in 71% (5/7) of participants. When challenged by the fact that an incompatible blood product was delivered to the bleeding patient, only 37.5% (3/8) asked for phenotype analysis of products already transfused and those being prepared and no one advised the team caring for the patient of this fact and of the possibility of a haemolytic transfusion reaction. Conclusion Blood bank technologists were considered to be relatively well prepared and possess the necessary expertise and communication skills to prepare and deliver blood products to obstetrical and paediatric trauma teams dealing with massive haemorrhages. For haematologists, knowledge gaps were identified and additional training will be mandatory to ensure proficiency when assisting teams dealing with such emergencies. Using in-situ simulation at the blood bank and telemedicine for haematologists, in addition to HF interdisciplinary team simulations occurring in a simulation lab, can further contribute to improving performances of all professionals actively involved in a massive haemorrhage crisis situation. 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 | 0,007 | 0,022 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,002 | 0,002 |
| Études des sciences et des technologies | 0,002 | 0,001 |
| Communication savante | 0,006 | 0,003 |
| Science ouverte | 0,002 | 0,004 |
| Intégrité de la recherche | 0,002 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,551 | 0,335 |
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 ».