Comparing surgical trays with redundant instruments with trays with reduced instruments: a cost analysis
Bibliographic record
Abstract
BACKGROUND: When prearranged standard surgical trays contain instruments that are repeatedly unused, the redundancy can result in unnecessary health care costs. Our objective was to estimate potential savings by performing an economic evaluation comparing the cost of surgical trays with redundant instruments with surgical trays with reduced instruments ("reduced trays"). METHODS: We performed a cost-analysis from the hospital perspective over a 1-year period. Using a mathematical model, we compared the direct costs of trays containing redundant instruments to reduced trays for 5 otolaryngology procedures. We incorporated data from several sources including local hospital data on surgical volume, the number of instruments on redundant and reduced trays, wages of personnel and time required to pack instruments. From the literature, we incorporated instrument depreciation costs and the time required to decontaminate an instrument. We performed 1-way sensitivity analyses on all variables, including surgical volume. Costs were estimated in 2013 Canadian dollars. RESULTS: The cost of redundant trays was $21 806 and the cost of reduced trays was $8803, for a 1-year cost saving of $13 003. In sensitivity analyses, cost savings ranged from $3262 to $21 395, based on the surgical volume at the institution. Variation in surgical volume resulted in a wider range of estimates, with a minimum of $3253 for low-volume to a maximum of $52 012 for high-volume institutions. INTERPRETATION: Our study suggests moderate savings may be achieved by reducing surgical tray redundancy and, if applied to other surgical specialties, may result in savings to Canadian health care systems.
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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 | 0.014 | 0.036 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.013 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".