Metacarpal Fracture Fixation in a Minor Surgery Setting Versus Main Operating Room: A Cost-minimization Analysis
Bibliographic record
Abstract
The objective of this study was to compare the costs of performing metacarpal fracture fixation in minor surgery (MS) versus the main operating room (OR) at a tertiary care center in Calgary, Alberta, from the institutional perspective. METHODS: Data were extracted from the Operating Room Information System and the Business Advisory System by a financial analyst. All data were based on actual expenses from the 2016-2017 fiscal year (US$). Direct costs included: staffing, supply, day (outpatient) surgery unit, post-anesthesia care unit (PACU), and anesthesia (anesthesiologist and equipment) costs. Surgeon and hardware costs were deemed neutral and excluded from the analysis. RESULTS: The total cost of metacarpal fixation in MS was $250, compared to $2,226 in the OR, after surgeon and hardware costs were excluded. Staffing costs are a major contributing factor to cost by location ($75 in MS versus $233 in OR), largely attributable to 0.5 nursing staff per room in MS compared to 3 nursing staff per room in the OR. Supply costs (minor tray, $94 versus case cart, $247) are also greater for OR cases. The combined costs for DSU ($465), PACU ($435), and anesthesia ($247) totaled $1,147 and are only incurred for OR cases. CONCLUSIONS: Repair of metacarpal fractures in MS represents a substantial cost-minimization strategy from the institutional perspective. Staffing and supply costs by location and the additional combined costs of DS, PACU, and anesthesia are all contributing factors.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.004 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".