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Record W4412779596 · doi:10.1186/s13049-025-01440-0

Blood transfusion training for prehospital providers: a scoping review

2025· review· en· W4412779596 on OpenAlexaff
Pierre‐Marc Dion, Kanwal Singh, Jillian Coleby, Andrew Beckett, Jacinthe Lampron, Melissa McGowan, Risa Shorr, Brodie Nolan

Bibliographic record

VenueScandinavian Journal of Trauma Resuscitation and Emergency Medicine · 2025
Typereview
Languageen
FieldMedicine
TopicSimulation-Based Education in Healthcare
Canadian institutionsMondelēz International (Canada)Ottawa HospitalUniversity of TorontoDalhousie UniversityDefence Research and Development CanadaSt. Michael's HospitalInstitut du Savoir MontfortUniversity of Ottawa
Fundersnot available
KeywordsMedicineMedical emergencyEmergency medical servicesBlood transfusionEmergency medicineTraining (meteorology)Surgery

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.493
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.168
GPT teacher head0.481
Teacher spread0.313 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designSystematic review
Domainnot available
GenreReview

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".

Quick stats

Citations4
Published2025
Admission routes1
Has abstractyes

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