Evidence-based approach for selecting human resources in urgent transport
Bibliographic record
Abstract
Interhospital transport is crucial for ensuring access to specialized care and poses a logistic and clinical challenge that impacts patient safety and resource management. Few tools are available to predict risks in pediatric transport (PT), so a triage scale could help optimize and standardize resources. To analyze the diagnostic accuracy of urgent interhospital transport team selection by health care professionals compared to the use of SCOPETAS, the adapted version Pediatric Transport Triage Tool (PT3), and to assess the agreement between the choices of professionals and those proposed by the scale. Observational cohort study to evaluate the accuracy of the SCOPETAS scale and the agreement between the actual transport team and the one recommended by the scale, considered the gold standard. We analyzed urgent PT cases (aged 1 month to 14 years) from four regional hospitals to the referral hospital over a one-year period. The study included a total of 150 PT cases. The weighted kappa for the agreement in team selection was 0.68 ( P < .001), with greater discordance in the choice of emergency medical technician (EMT) + nursing teams. The weight of evidence (WoE) for selecting advanced and basic life support was 10.1 dB and 7.54 dB, respectively, compared to 3.93 dB and 3.11 dB for EMT and EMT + nursing teams, respectively. The application of SCOPETAS would have reduced costs and optimized staff availability. SCOPETAS is a useful and easy-to-apply tool that standardizes PT and optimizes resources. Future research should cover all pediatric age groups and other regions. El transporte interhospitalario es crucial para garantizar el acceso a atención especializada, representando un reto logístico y clínico con impacto en la seguridad del paciente y el uso de recursos. Existen pocas herramientas para predecir riesgos en el transporte pediátrico (TP), por lo que una escala de triaje podría optimizar y estandarizar recursos. Analizar la exactitud diagnóstica de selección del equipo de TP interhospitalario urgente de los profesionales respecto de la escala PT3 adaptada ( Score pediátrico de transporte , SCOPETAS) y estudiar la concordancia de su elección con la propuesta por la escala. Estudio observacional analítico de una cohorte para evaluar la exactitud de la escala SCOPETAS y la concordancia entre el equipo real y el recomendado por la escala, considerada patrón de oro . Durante un año, se analizaron los TP urgentes (de pacientes entre 1 mes y 14 años) desde 4 hospitales periféricos al hospital de referencia. Se incluyeron 150 T P. La concordancia en la selección del equipo de traslado presentó una kappa ponderada de 0,68 ( p < 0,001), con mayor discordancia en la elección del equipo técnico de emergencias sanitarias (TES)+enfermería. El peso de la evidencia (WoE) para la elección de soporte vital avanzado y básico fue de 10,1 y 7,54 dB; para TES y TES+enfermería, 3,93 y 3,11 dB respectivamente. La aplicación de SCOPETAS habría reducido costes y optimizado la disponibilidad de personal. SCOPETAS es una herramienta útil y fácil de aplicar, que estandariza el TP, y optimiza recursos. Futuras investigaciones deberían abarcar todas las edades pediátricas y otras regiones.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.127 | 0.302 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.007 | 0.009 |
| Bibliometrics | 0.032 | 0.013 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.010 | 0.005 |
| Open science | 0.010 | 0.005 |
| Research integrity | 0.006 | 0.006 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".