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Record W1974070169 · doi:10.5430/jha.v1n2p1

Level of Acuity in Pediatric Patients with Recurrent Emergency Department Visits

2012· article· en· W1974070169 on OpenAlexvenueno aff
Ilene Claudius, Chun Nok Lam

Bibliographic record

VenueJournal of Hospital Administration · 2012
Typearticle
Languageen
FieldMedicine
TopicEmergency and Acute Care Studies
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineTriageEmergency departmentPsychological interventionIntervention (counseling)Emergency medicinePediatricsPediatric emergency medicineRetrospective cohort studyEmergency physicianSurgeryPsychiatry

Abstract

fetched live from OpenAlex

Introduction: Recurrent ED utilizers account for a substantial proportion of ED visits, yet little data exists on children with multiple visits. The objective of this study was to compare the need for interventions and triage acuity of recurrent utilizers of a pediatric emergency department to that of non-recurrent utilizers. Methods: This is a retrospective analysis of children presenting to a pediatric emergency department. Children were classified as recurrent utilizers if they had 4 or more visits to the ED per year and non-recurrent utilizers if they had less than 4 visits. Data was collected and inter-group comparison performed on critical interventions received (admission, consultation, intravenous fluid therapy, observation, and performance of procedures), all interventions received (including critical interventions as well as laboratories, radiographs, and medications), and triage acuity for the index visit. Results: Two-hundred thirty patients were included, of whom, 15% were classified as recurrent utilizers. This group had significantly lower rates of requiring a critical intervention (8.6% vs. 51.4%, p=.001), lower rates of any intervention (51.4% vs. 74.4%, p=.007), and less urgent triage acuity (3.3 vs. 3.1, p=.029). Conclusions: Recurrent utilizers of the pediatric emergency department had significantly lower need for intervention and less urgent mean triage acuity when compared with non-recurrent utilizers.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.280

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0000.000

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 head0.030
GPT teacher head0.307
Teacher spread0.277 · 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
Published2012
Admission routes1
Has abstractyes

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