Economic Analysis of Reprocessing Single-Use Medical Devices: A Systematic Literature Review
Bibliographic record
Abstract
BACKGROUND: Although an increasing number of medical devices are labeled "for single use only," cleaning and reuse of single-use medical devices continues, because of the economic incentive. We conducted a survey of the economic literature to obtain the current evidence available and to assess the costs and benefits of reusing single-use medical devices. METHODS: A comprehensive literature search was carried out to identify articles that compared single use and reuse of single-use medical devices and that met specific scientific criteria, including evaluation of economic outcomes. Each selected article was independently reviewed by 2 reviewers to extract cost and clinical outcome data and to assess the quality of the study. RESULTS: Nine published articles met the selection criteria. The savings were about 49% of the direct cost. These savings would be offset by adverse-event costs, but none were detected. However, quality of the studies was generally poor. CONCLUSIONS: There is little available evidence of quality in the published literature to assess the practice of reuse of single-use medical devices. Moreover, data on clinical outcomes are missing and, where available, cannot be attributed specifically to the reuse of single-use medical devices.
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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 | 0.063 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.008 |
| Bibliometrics | 0.011 | 0.011 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| 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".