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Record W4415188673 · doi:10.1097/pec.0000000000003493

Standardization of Discharge Instructions by Age for Children Presenting to the ED With Mild Traumatic Brain Injury

2025· article· en· W4415188673 on OpenAlexaff
Nicole Gerber, Snezana Nena Osorio, Michael J. Alfonzo, Sean C. Rose, Miriam H. Beauchamp, Deborah A. Levine

Bibliographic record

VenuePediatric Emergency Care · 2025
Typearticle
Languageen
FieldMedicine
TopicTraumatic Brain Injury Research
Canadian institutionsCentre Hospitalier Universitaire Sainte-Justine
Fundersnot available
KeywordsStandardizationTraumatic brain injuryPsychological interventionEmergency departmentGlasgow Coma ScaleIntensive care

Abstract

fetched live from OpenAlex

INTRODUCTION: Mild traumatic brain injuries (mTBI) are common in pediatric emergency departments (EDs), but inconsistent use of diagnostic labels leads to variable discharge instructions, especially with regard to concussion. Lack of age-appropriate guidance can increase parental anxiety and ED revisits and hinder recovery. OBJECTIVE: This quality improvement (QI) initiative aimed to increase the proportion of mTBI patients receiving age-appropriate discharge instructions to 50% over 13 months in an urban pediatric ED. METHODS: An interdisciplinary QI team conducted an observational time series study with sequential experimentation at a quaternary academic medical center over 13 months. Using a key driver diagram, they created SMART aim, measures, and designed interventions which were tested through 5 Plan-Do-Study-Act (PDSA) cycles. Interventions included an educational curriculum, e-reminders, workspace materials, and pre-written electronic medical record (EMR) templates (smart phrases) for age-specific discharge instructions (0 to 5 y, ≥6 y), and parent surveys were used on a subset of sample families to assess knowledge, behavior, and anxiety post-discharge. Outcome measures included the percentage of age-appropriate discharge instructions provided and use of the new EMR smart phrase. Balancing measures tracked head computed tomography (CT) utilization, ED revisits within 14 days of discharge, and neurology referrals. Process control charts and rules to detect special cause variation were used to analyze data. We use descriptive statistics to analyze survey data. RESULTS: Among 1263 patients, age-appropriate discharge instruction rates improved from 36% to 56%. Smart phrases were used in 58% of relevant cases (n=628). No changes were observed in CT orders, ED revisits, or neurology referrals. Among 37 surveyed parents (28% response rate), 95% (n=35) found instructions helpful, and 68% (n=25) reported reduced anxiety. CONCLUSIONS: Implementing EMR smart phrases in a pediatric ED increased standardized, age-appropriate discharge instructions for children with mTBI. These low-cost interventions are scalable for broader ED use and other settings.

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)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.528
Threshold uncertainty score0.449

Codex and Gemma teacher scores by category

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

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 head0.026
GPT teacher head0.350
Teacher spread0.324 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations0
Published2025
Admission routes1
Has abstractyes

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