Planning for Replacement of GI Endoscopy Equipment in a Regional Setting
Bibliographic record
Abstract
The management of endoscopic equipment is commonly facilitated under a comprehensive equipment/consumable service contract. Contract can present challenges at renewal/termination time. Analysis of status and implications of different replacement options is necessary. This paper presents the results of our investigation into the status of endoscopy equipment in preparation for end of contract. The different options that were analyzed will be presented and provide a learning opportunity for other Clinical Engineering programs.An environmental scan of endoscopes and ancillary equipment within the Winnipeg Regional Health Authority facilities was conducted. The scan involved consultation with site equipment managers, manufacturers and third party repair companies. This information was reconciled with inventory in the hospital databases. The collected information was analyzed through various statistical parameters to delineate the various dimensions regarding distribution, status and impact of different replacement models/scenarios.The results of the scan provided an important insight into the current practice of endoscope management as well as the clinical, technical and economic impact of a possible vendor change. Inter-departmental equipment sharing was one of the aspects to consider. Technical implications included propriety equipment connections, which may necessitate complete replacement; approximately 70% worth of endoscopic equipment. The results provided invaluable input to inform an RFP preparation. An environmental scan is an important prerequisite for an evidence-informed replacement plan. This study considered some of the most relevant factors and provided invaluable information for stakeholders to prepare a comprehensive RFP. The study provides a learning opportunity for other CE programs in a similar situation.
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 | 0.005 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".