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Record W2962216622 · doi:10.5435/jaaos-d-18-00585

Cost Analysis of Treating Pediatric Supracondylar Humerus Fractures in Community Hospitals Compared With a Tertiary Care Hospital

2019· article· en· W2962216622 on OpenAlexaff
Mark Shasti, Tuo Peter Li, Alexandria L. Case, Arun R. Hariharan, Julio J. Jauregui, Joshua M. Abzug

Bibliographic record

VenueJournal of the American Academy of Orthopaedic Surgeons · 2019
Typearticle
Languageen
FieldMedicine
TopicElbow and Forearm Trauma Treatment
Canadian institutionsObject Research Systems (Canada)
Fundersnot available
KeywordsMedicineHumerusTertiary carePercutaneous pinningRetrospective cohort studyCost reductionReduction (mathematics)Health carePercutaneousEmergency medicineGeneral surgerySurgery

Abstract

fetched live from OpenAlex

OBJECTIVE: In the current healthcare environment, providing cost-efficient care is of paramount importance. One emerging strategy is to use community hospitals (CHs) rather than tertiary care hospitals (TCHs) for some procedures. This study assesses the costs of performing closed reduction percutaneous pinning (CRPP) of pediatric supracondylar humerus fractures (SCHFs) at a CH compared with a TCH. METHODS: A retrospective review of 133 consecutive SCHFs treated with CRPP at a CH versus a TCH over a 6-year period was performed. Total encounter and subcategorized costs were compared between the procedures done at a CH versus those done at a TCH. RESULTS: Performing CRPP for a SCHF at a CH compared with a TCH saved 44% in costs (P < 0.001). Cost reduction of 51% was attributable to operating room costs, 19% to anesthesia-related costs, 16% to imaging-related costs, and 7% to supplies. DISCUSSION: Performing CRPP for a SCHF at a CH compared with a TCH results in a 44% decrease in direct cost, driven largely by surgical, anesthesia, and radiology-related savings.

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)0.001
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 score0.006
Threshold uncertainty score0.609

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.013
GPT teacher head0.300
Teacher spread0.286 · 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

Citations10
Published2019
Admission routes1
Has abstractyes

Explore more

Same venueJournal of the American Academy of Orthopaedic SurgeonsSame topicElbow and Forearm Trauma TreatmentFrench-language works237,207