Predictors of Episode-of-Care Costs for Ankle Fractures
Bibliographic record
Abstract
Ankle fractures are one of the most resource-consuming traumatic orthopedic injuries. Few studies have successfully evaluated the episode-of-care costs (EOCC) of common traumatic orthopedic injuries. The objective of this study was to determine the EOCC associated with the surgical management of ankle fractures. A retrospective cohort study of 105 consecutive patients who underwent open reduction internal fixation of an isolated ankle fracture at a Canadian Level-1 trauma center was conducted. Episode-of-care costs were generated using an activity-based costing framework. The median global episode-of-care cost for ankle fracture surgeries performed at the studied institution was $3,487 CAD [IQR 880] ($2,685 USD [IQR 616]). Patients aged 60 to 90 years had a significantly higher median EOCC than younger patients (p = .01). Supination-adduction injuries had a significantly higher median EOCC than other injury patterns (p = .01). The median EOCC for patients who underwent surgery within 10 days of their injury ($3,347 CAD [582], $2,577 USD [448]) was significantly lower than the cost for patients who had their surgery delayed 10 days or more after the injury ($3,634 CAD [776], $2,798 USD [598]) (p = .03). Patient sex, anesthesia type, ASA score and surgeon's fellowship training did not affect the EOCC. This study provides valuable data on predictors of EOCC in the surgical management of ankle fractures. Delaying simple ankle fracture cases due to operating time constraints can increase the total cost and burden of these fractures on the healthcare system. In addition, this study provides a framework for future episode-of-care cost analysis studies in orthopedic surgery.
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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 | 0.000 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".