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Record W2900957389 · doi:10.1097/mej.0000000000000582

Template for uniform reporting of emergency department measures, consensus according to the Utstein method

2018· article· en· W2900957389 on OpenAlexaff
Katrin Hruska, Maaret Castrén, Jay Banerjee, Wilhelm Behringer, Lars Petter Bjørnsen, Peter Cameron, Sharon Einav, Brian R. Holroyd, Peter Jones, Annmarie Touborg Lassen, Melinda Truesdale, Lisa Kurland

Bibliographic record

VenueEuropean Journal of Emergency Medicine · 2018
Typearticle
Languageen
FieldMedicine
TopicEmergency and Acute Care Studies
Canadian institutionsAlberta HealthUniversity of AlbertaAlberta Health Services
Fundersnot available
KeywordsComparabilityEmergency departmentStaffingMedical emergencyMedicineProcess (computing)Health carePopulationOperations managementNursingComputer scienceEngineeringPolitical science

Abstract

fetched live from OpenAlex

OBJECTIVE: To develop a template for uniform reporting of standardized measuring and describing of care provided in the emergency department (ED). METHODS: An international group of experts in emergency medicine, with broad experience from different clinical settings, met in Utstein, Norway. Through a consensus process, a limited number of measures that would accurately describe an ED were chosen and a template was developed. RESULTS: The final measures to be reported and their definitions were grouped into six categories: Structure, Staffing and governance, Population, Process times, Hospital and healthcare system and Outcomes. The template for Utstein-style uniform reporting is presented. CONCLUSION: The suggested template is intended for use in studies carried out in EDs to improve comparability and knowledge translation.

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)0.010
metaresearch head score (Gemma)0.011
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.371
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0100.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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)0.0010.000

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 head0.161
GPT teacher head0.416
Teacher spread0.255 · 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.

Study designNot applicable
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

Citations27
Published2018
Admission routes1
Has abstractyes

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