Regional consolidation of orthopedic surgery: impacts on hip fracture surgery access and outcomes
Bibliographic record
Abstract
BACKGROUND: Timely access to orthopedic trauma surgery is essential for optimal outcomes. Regionalization of some types of surgery has shown positive effects on access, timeliness and outcomes. We investigated how the consolidation of orthopedic surgery in 1 Canadian health region affected patients requiring hip fracture surgery. METHODS: We retrieved administrative data on all regional emergency department visits for lower-extremity injury and all linked inpatient stays from January 2010 through March 2013, identifying 1885 hip-fracture surgeries. Statistical process control and interrupted time series analysis controlling for demographics and comorbidities were used to assess impacts on access (receipt of surgery within 48-h benchmark) and surgical outcomes (complications, in-hospital/30-d mortality, length of stay). RESULTS: There was a significant increase in the proportion of patients receiving surgery within the benchmark. Complication rates did not change, but there appeared to be some decrease in mortality (significant at 6 mo). Length of stay increased at a hospital that experienced a major increase in patient volume, perhaps reflecting challenges associated with patient flow. CONCLUSION: Regionalization appeared to improve the timeliness of surgery and may have reduced mortality. The specific features of the present consolidation (including pre-existing interhospital performance variation and the introduction of daytime slates at the referral hospital) should be considered when interpreting the findings.
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 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 | 0.002 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 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".