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Record W1967929524 · doi:10.1097/ta.0b013e318265cec2

Institutional and provider factors impeding access to trauma center care

2012· article· en· W1967929524 on OpenAlexafffund
David Gómez, Barbara Haas, Charles de Mestral, Sunjay Sharma, Marvin Hsiao, Brandon Zagorski, Gordon D. Rubenfeld, Joel G. Ray, Avery B. Nathens

Bibliographic record

VenueThe Journal of Trauma: Injury, Infection, and Critical Care · 2012
Typearticle
Languageen
FieldMedicine
TopicTrauma and Emergency Care Studies
Canadian institutionsToronto Public HealthUniversity of Toronto
FundersCanadian Institutes of Health Research
KeywordsStaffingMedicineEmergency departmentTrauma centerInterquartile rangeOdds ratioConfidence intervalEmergency medicineRetrospective cohort studyResource (disambiguation)PopulationMedical emergencyInternal medicineNursingEnvironmental health

Abstract

fetched live from OpenAlex

BACKGROUND: More than a third of patients with severe injury who receive initial care at nontrauma centers (NTCs) are not transferred to trauma center care. In those who are transferred, significant delays have been described. The availability of specialists, imaging modalities, or critical care resources might significantly affect transfer practices. METHODS: We undertook a population-based retrospective cohort study of adult patients with severe injury who were transported from the scene to an NTC. NTCs were characterized based on the availability of general and orthopedic surgeons, computed tomographic scanners, intensive care units, and emergency department staffing. NTCs that had all of the resources were characterized as resource rich, while those with none were characterized as resource limited. We evaluated the relationships between NTC resources and the likelihood and timeliness of interfacility transfer through the use of hierarchical regression modeling. RESULTS: We identified 15,906 patients with severe injury across 192 NTCs (22% were resource limited, 57% were resource intermediate, and 21% were resource rich). Patients at resource rich centers, as compared with those at resource limited centers, were less likely to be transferred (27% vs. 50%, p < 0.001). This association persisted after adjustment for confounders (odds ratio, 0.66; 95% confidence interval, 0.47-0.92). Among patients who were transferred, median emergency department length of stay (ED-LOS) was 3.5 hours (interquartile range, 1.7-4.6 hours). However, ED-LOS varied significantly because resource rich centers had a greater proportion of patients experiencing prolonged ED-LOS when compared with resource limited centers (31% vs. 15%, p < 0.001). This association also persisted on multivariable analysis (odds ratio, 2.02; 95% confidence interval, 1.19-3.43). CONCLUSION: Severely injured patients who received initial care in resource rich NTCs were less likely to be transferred to a trauma center compared with resource limited NTCs. Significant delays in the transfer process were identified. However, patients transferred from resource rich centers were more likely to experience prolonged ED-LOS compared with resource limited NTCs. LEVEL OF EVIDENCE: Epidemiologic study, level II.

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 score0.033
Threshold uncertainty score0.486

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 communication0.0000.001
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 head0.045
GPT teacher head0.370
Teacher spread0.325 · 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

Citations47
Published2012
Admission routes2
Has abstractyes

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