Comparative cost-efficiency of the EVOTECH endoscope cleaner and reprocessor versus manual cleaning plus automated endoscope reprocessing in a real-world Canadian hospital endoscopy setting
Bibliographic record
Abstract
BACKGROUND: Reprocessing of endoscopes generally requires labour-intensive manual cleaning followed by high-level disinfection in an automated endoscope reprocessor (AER). EVOTECH Endoscope Cleaner and Reprocessor (ECR) is approved for fully automated cleaning and disinfection whereas AERs require manual cleaning prior to the high-level disinfection procedure. The purpose of this economic evaluation was to determine the cost-efficiency of the ECR versus AER methods of endoscopy reprocessing in an actual practice setting. METHODS: A time and motion study was conducted at a Canadian hospital to collect data on the personnel resources and consumable supplies costs associated with the use of EVOTECH ECR versus manual cleaning followed by AER with Medivators DSD-201. Reprocessing of all endoscopes was observed and timed for both reprocessor types over three days. Laboratory staff members were interviewed regarding the consumption and cost of all disposable supplies and equipment. Exact Wilcoxon rank sum test was used for assessing differences in total cycle reprocessing time. RESULTS: Endoscope reprocessing was significantly shorter with the ECR than with manual cleaning followed by AER. The differences in median time were 12.46 minutes per colonoscope (p < 0.0001), 6.31 minutes per gastroscope (p < 0.0001), and 5.66 minutes per bronchoscope (p = 0.0040). Almost 2 hours of direct labour time was saved daily with the ECR. The total per cycle cost of consumables and labour for maintenance was slightly higher for EVOTECH ECR versus manual cleaning followed by AER ($8.91 versus $8.31, respectively). Including the cost of direct labour time consumed in reprocessing scopes, the per cycle and annual costs of using the EVOTECH ECR was less than the cost of manual cleaning followed by AER disinfection ($11.50 versus $11.88). CONCLUSIONS: The EVOTECH ECR was more efficient and less costly to use for the reprocessing of endoscopes than manual cleaning followed by AER disinfection. Although the cost of consumable supplies required to reprocess endoscopes with EVOTECH ECR was slightly higher, the value of the labour time saved with EVOTECH ECR more than offset the additional consumables cost. The increased efficiency with EVOTECH ECR could lead to even further cost-savings by shifting endoscopy laboratory personnel responsibilities but further study is required.
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 | 0.004 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".