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Record W3087865364 · doi:10.1002/aet2.10537

Effect of Repetitive Simulation Training on Emergency Medical Services Team Performance in Simulated Pediatric Medical Emergencies

2020· article· en· W3087865364 on OpenAlexaff
Kathryn Kothari, Chelsea Zuger, Neil Desai, Jan Leonard, Michelle Alletag, Ashley Balakas, Mike Binney, Sean Caffrey, Jason Kotas, Patrick Mahar, Kelley Roswell, Kathleen Adelgais

Bibliographic record

VenueAEM Education and Training · 2020
Typearticle
Languageen
FieldMedicine
TopicSimulation-Based Education in Healthcare
Canadian institutionsBC Children's Hospital
FundersMaternal and Child Health BureauNational Center for Advancing Translational SciencesHealth Resources and Services AdministrationColorado Department of Public Health and EnvironmentNational Institutes of HealthGeorgia Clinical and Translational Science AllianceChildren's Hospital Colorado
KeywordsMedicineEmergency medical servicesPsychological interventionEmergency medicineSedationPhysical therapyMedical emergencyAnesthesiaNursing

Abstract

fetched live from OpenAlex

Abstract Objective Emergency medical services (EMS) professionals infrequently transport children leading to difficulty in recognition and management of pediatric critical illness. Simulation provides an opportunity to train EMS professionals on pediatric emergencies. The objective of this study was to examine the effect of serial simulation training over 6 months on EMS psychomotor and cognitive performance during team‐based care. Methods This was a longitudinal prospective study of a simulation curriculum enrolling EMS professionals over a 6‐month period during which they performed three high‐fidelity simulations at 3‐month intervals. The simulation scenarios included a 15‐month‐old seizure (T 0 ), 1‐month‐old with hypoglycemia (T 1 ), and 4‐year‐old clonidine ingestion (T 2 ). All scenarios were standardized and required recognition and management of respiratory failure and decompensated shock. Scenarios were videotaped and two investigators scored EMS team interventions during simulations using a standardized scoring tool. Inter‐rater reliability was assessed on 30% of videos using kappa analysis. Volumes of administered intravenous fluid (IVF) and medications were measured to assess for errors in administration. The primary outcome was the change in scenario score from T 0 to T 2 . Results A total of 135 team‐based simulations were conducted over the study period (48, 40, and 47 at T 0 , T 1 , and T 2 , respectively). Inter‐rater reliability between reviewers was very good (κ = 0.7). Median simulation score improved from T 0 to T 2 (24 vs 31, p < 0.001, maximum score possible = 42). The proportion of completed tasks increased across multiple categories including improved recognition of respiratory decompensation (19% vs. 56%), management of the pediatric airway (44% vs. 88%), and timeliness of vascular access (10% vs. 38%). Correct IVF administration varied by scenario (25% vs. 52% vs. 30%, p = 0.02). Conclusion Serial simulation improved EMS team‐based care in both recognition and management of pediatric emergencies. A standardized pediatric simulation curriculum can be used to train EMS professionals on pediatric emergencies and improve performance.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.313
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.039
GPT teacher head0.380
Teacher spread0.340 · 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 designObservational
Domainnot available
GenreEmpirical

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

Citations16
Published2020
Admission routes1
Has abstractyes

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