Blood transfusion training for prehospital providers: a scoping review
Notice bibliographique
Résumé
BACKGROUND: Blood transfusion is increasingly utilised to manage haemorrhagic shock in prehospital environments. This practice is particularly relevant in settings where delays to definitive treatment are common due to extended evacuation timelines, limited resupply, and challenging environmental conditions. Safe and effective transfusion in these contexts depends on competent, well-prepared providers. Non-physician personnel may be required to perform transfusions independently in high-stakes situations without direct physician supervision. This scoping review synthesizes current literature on blood transfusion training for prehospital providers, with a focus on instructional design, simulation modalities, knowledge retention, and outcome evaluation. METHODS: We conducted a scoping review following Joanna Briggs Institute methodology and reported in accordance with the PRISMA-ScR framework. Seven databases were systematically searched through 20 February 2025. Eligible studies described transfusion training for non-physician healthcare providers in prehospital or austere environments. Data were extracted on instructional strategies, simulation modalities, and outcome measures. Outcomes were categorised using the Kirkpatrick Model, and instructional design features mapped to simulation-based education frameworks. RESULTS: Six studies involving 475 participants were included. Participants included combat medics, paramedics, registered nurses, physician assistants, and medical students. Training was delivered across environments including simulation centres, field-based exercises, and in-theatre deployments. All studies featured face-to-face instruction and hands-on skills training. Simulation modalities included part-task trainers in four studies, high-fidelity mannequins in two, live human models in two, and real-world transfusions in one. Instructional design features such as team-based learning, repeated practice, and structured feedback were reported in most studies. Outcomes were reported across all four Kirkpatrick levels. Four studies assessed learner satisfaction and confidence (Level 1), five evaluated knowledge and procedural skill acquisition (Level 2), three assessed behavioural change in practice (Level 3), and one reported patient-level outcomes during operational missions (Level 4). None assessed long-term retention. Variability in instructional methods and limited evaluation at higher outcome levels constrained generalizability. CONCLUSIONS: Blood transfusion training for prehospital providers appears feasible and associated with short-term improvements in knowledge, skills, and confidence. However, inconsistent instructional design and limited evaluation of long-term or clinical outcomes indicate important gaps. Structured, simulation-informed programs aligned with operational needs may improve training consistency and effectiveness.
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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 | 0,013 | 0,070 |
| Méta-épidémiologie (sens strict) | 0,002 | 0,001 |
| Méta-épidémiologie (sens large) | 0,004 | 0,004 |
| Bibliométrie | 0,016 | 0,016 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,004 | 0,003 |
| Science ouverte | 0,003 | 0,002 |
| Intégrité de la recherche | 0,004 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,005 | 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 ».