A Methodological Guide to Performing a Cost-Utility Study Comparing Surgical Techniques
Bibliographic record
Abstract
BACKGROUND: When recommending the adoption of a new surgical intervention as opposed to maintaining an old one, surgeons need to consider the opportunity cost, which is the value of the forgone benefits. To inform these decisions, surgeons can use economic analyses of surgical practices. Unfortunately, economic analyses conducted alongside randomized controlled trials in surgery are rare. OBJECTIVES: The objective of the present study was to use data from a small randomized controlled trial to illustrate the methodology for a cost-utility analysis comparing two techniques of carpal tunnel release: open release without ('usual' technique) and with ('novel' technique) ligament reconstruction. METHODS: Eighteen eligible patients were entered into this prospective study. Fifteen were followed to six weeks postoperatively. One day preoperatively, and five days, three weeks and six weeks postoperatively, patients completed a self-administered Health Utilities Index Mark 2-3 questionnaire (utilities) and a case report form from which resource utilization (cost) was collected. Utilities were expressed as quality-adjusted life weeks, a fraction of quality-adjusted life years. RESULTS: The mean total cost of the usual technique was lower than the novel technique, and the mean quality-adjusted life week was higher, favouring the usual technique. Indirect costs were four to nine times higher than direct costs in both techniques. CONCLUSION: The novel technique was more costly and less effective, and fell in the 'lose-lose' quadrant of the cost-effectiveness plane; it was rejected in favour of the usual technique. This methodology should be applied when deciding whether to adopt novel surgical techniques in plastic surgery to optimize scarce health care resources.
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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 | 0.311 | 0.504 |
| Meta-epidemiology (narrow) | 0.004 | 0.003 |
| Meta-epidemiology (broad) | 0.006 | 0.011 |
| Bibliometrics | 0.012 | 0.013 |
| Science and technology studies | 0.002 | 0.006 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.008 | 0.005 |
| Research integrity | 0.005 | 0.014 |
| Insufficient payload (model declined to judge) | 0.025 | 0.005 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".