EMS Agency Characteristics and Adverse Events in Pediatric Out-of-Hospital Cardiac Arrest Among 49 U.S. EMS Agencies
Bibliographic record
Abstract
OBJECTIVES: Pediatric out-of-hospital cardiac arrest (OHCA) impacts 15,000-25,000 children annually in the U.S. The objective of this study was to determine if specific Emergency Medical Services (EMS) agency factors, such as pediatric volume and preparedness factors, including hours of required pediatric training, pediatric emergency care coordinator (PECC), or pediatric informational resources are associated with improved quality of care or adverse events for pediatric OHCA. METHODS: We conducted a retrospective chart review of EMS clinical records and EMS agency survey among five agencies in the Portland OR, Pittsburgh PA, Milwaukee WI, San Bernardino CA, Atlanta GA, and Dallas TX regions. We reviewed medical records of children who experienced an EMS-treated OHCA between 2013 and 2019 using a validated structured chart review tool to identify adverse safety events (ASEs). Agencies who contributed medical records completed a survey that described elements of pediatric preparedness and organizational structure relevant to pediatric care. We first conducted a descriptive analysis of agency and patient characteristics, followed by an evaluation of the association of agency factors that we hypothesized could improve pediatric care and reduce the occurrence of ASEs. RESULTS: Twenty-two agencies with a total of 659 OHCA patient encounters completed the survey. The Broselow system was used by 81% of agencies, local protocol guides were used in 86% of agencies. Forty-five percent of agencies had a designated pediatric emergency care coordinator (PECC). Agencies reported a similar number of hours for pediatric and neonatal simulation (1.3 and 1.5 h, respectively) and skills training (2.0 and 2.5 h, respectively) annually. We found that younger patient age significantly increased the risk of an ASE. In both univariate and multivariate analyses, several hypothesized variables were not associated with decreased risk of an ASE, including pediatric and neonatal skills/simulation training hours, conducting pediatric-specific quality reviews, and having an identified PECC. CONCLUSIONS: In this large medical record review of EMS-treated pediatric OHCA cases, pediatric training, pediatric care coordination, and conducting pediatric quality reviews were not associated with reduced ASEs. Additional research is needed to understand how EMS agencies can improve the quality of care for pediatric OHCA, especially for infants.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
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 teacher head, 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".