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Record W2300785004 · doi:10.1017/s1049023x16000091

First Responder Accuracy Using SALT during Mass-casualty Incident Simulation

2016· article· en· W2300785004 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenuePrehospital and Disaster Medicine · 2016
Typearticle
Languageen
FieldHealth Professions
TopicDisaster Response and Management
Canadian institutionsUniversity of AlbertaWestern University
Fundersnot available
KeywordsTriageMass-casualty incidentMedical emergencyMedicineEmergency medical servicesCoachingPsychological interventionEmergency medicineMass CasualtyPoison controlInjury preventionPsychologyNursing

Abstract

fetched live from OpenAlex

INTRODUCTION: During mass-casualty incidents (MCIs), patient volume often overwhelms available Emergency Medical Services (EMS) personnel. First responders are expected to triage, treat, and transport patients in a timely fashion. If other responders could triage accurately, prehospital EMS resources could be focused more directly on patients that require immediate medical attention and transport. HYPOTHESIS: Triage accuracy, error patterns, and time to triage completion are similar between second-year primary care paramedic (PCP) and fire science (FS) students participating in a simulated MCI using the Sort, Assess, Life-saving interventions, Treatment/Transport (SALT) triage algorithm. METHODS: All students in the second-year PCP program and FS program at two separate community colleges were invited to participate in this study. Immediately following a 30-minute didactic session on SALT, participants were given a standardized briefing and asked to triage an eight-victim, mock MCI using SALT. The scenario consisted of a four-car motor vehicle collision with each victim portrayed by volunteer actors given appropriate moulage and symptom coaching for their pattern of injury. The total number and acuity of victims were unknown to participants prior to arrival to the mock scenario. RESULTS: Thirty-eight PCP and 29 FS students completed the simulation. Overall triage accuracy was 79.9% for PCP and 72.0% for FS (∆ 7.9%; 95% CI, 1.2-14.7) students. No significant difference was found between the groups regarding types of triage errors. Over-triage, under-triage, and critical errors occurred in 10.2%, 7.6%, and 2.3% of PCP triage assignments, respectively. Fire science students had a similar pattern with 15.2% over-triaged, 8.7% under-triaged, and 4.3% critical errors. The median [IQR] time to triage completion for PCPs and FSs were 142.1 [52.6] seconds and 159.0 [40.5] seconds, respectively (P=.19; Mann-Whitney Test). CONCLUSIONS: Primary care paramedics performed MCI triage more accurately than FS students after brief SALT training, but no difference was found regarding types of error or time to triage completion. The clinical importance of this difference in triage accuracy likely is minimal, suggesting that fire services personnel could be considered for MCI triage depending on the availability of prehospital medical resources and appropriate training.

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.

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)0.000
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 score0.257
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.072
GPT teacher head0.411
Teacher spread0.339 · 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