Repair Costs for Endobronchial Ultrasound Bronchoscopes
Bibliographic record
Abstract
BACKGROUND: The development of endobronchial ultrasound (EBUS) has revolutionized the diagnostic approach to lung cancer and mediastinal lymphadenopathy. The capital costs associated with implementing EBUS are easily obtained from manufacturers, but the ongoing maintenance and repair costs are unknown. OBJECTIVE: The purpose of this study was to delineate the maintenance and repair costs associated with EBUS. METHODS: For the period between October 2005 and June 30, 2009, the number of procedures and the maintenance and repair costs for both EBUS and flexible bronchoscopes were recorded. Two BF-160UCF-OL8 (Olympus, Canada) linear convex EBUS bronchoscopes were used for EBUS procedures during the course of the study. Total costs were calculated on a yearly basis and on a per procedure basis for EBUS and standard bronchoscopes and are presented in Canadian and US dollars ($1 CAN=$0.88 USD). RESULTS: During the period of October 2005 and June 2009, a total of 949 linear convex EBUS procedures and 2767 flexible bronchoscopies were carried out. During this period, 13 separate repair issues were encountered with the EBUS bronchoscopes and control unit. The total cost for maintenance and repair of the EBUS and flexible bronchoscopes was $110,151.46 ($96,933.28 USD) and $67,301.49 ($59,225.31 USD), respectively. The average cost per procedure for EBUS and flexible bronchoscopy was $116.00 ($102.08 USD) and $24.32 ($21.42 USD), respectively. CONCLUSIONS: The cost of EBUS repairs per procedure is significant and illustrates the importance of understanding the ongoing maintenance issues inherent in these delicate pieces of medical equipment.
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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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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".