Evaluation of a tiered operating room strategy at an academic centre: comparing high-efficiency and conventional operating rooms
Bibliographic record
Abstract
BACKGROUND: Wait times for many elective orthopedic surgical procedures in Ontario have become unacceptably long and substantially exceed the recommended guidelines. As a consequence, many patients experience chronic pain, disability and other poor health outcomes. The purpose of this study was to test a novel, resource-saving redesign of outpatient operating room (OR) services, based on tiered grouping of surgical cases, to maximize health benefits for patients while improving efficiency and decreasing wait times. METHODS: This prospective cohort study enrolled adult patients scheduled to undergo unilateral lower limb procedures that had a low requirement for surgical resources and did not require admission to the hospital (ambulatory surgical services) at an academic hospital. Patients were randomly assigned to a conventional OR group or a high-efficiency (tiered) OR group, in which the intensity of surgical, anesthesia and nursing resources was matched to the procedure and the patient's health status. The tiered OR made use of local anesthesia and a block room rather than general anesthesia. Primary outcomes were costs of surgical services provided and patient health outcomes; secondary outcomes were patient and staff satisfaction with each OR setup. RESULTS: The costs associated with the high-efficiency OR were 60% lower than those associated with the conventional OR (this was primarily due to the streamlining of OR care and elimination of the need to use a postanesthetic care unit), with the same or equivalent patient health outcomes. No differences in patient and staff satisfaction were found between the 2 setups. CONCLUSION: The use of tiered, ambulatory services for elective orthopedic surgery does not compromise health outcomes and patient satisfaction, and it is associated with substantial cost savings.
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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 | 0.006 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| 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".