The Costs of Industry-Sponsored Medical Device Clinical Trials in Alberta
Bibliographic record
Abstract
OBJECTIVE: Our objective was to describe the costs of industry-sponsored clinical trials for medical devices in Northern Alberta, Canada. METHODS: We used centralized data to identify all industry-sponsored medical device clinical trials initiated in Northern Alberta from 2012 to 2016. For each arm of each trial, we calculated the price of devices provided by the sponsor and the cost of clinical and administrative services that were incurred to clinically operationalize the treatment. RESULTS: Our sample consisted of 18 device trials initiated between January 2012 and January 2016. The overall cost (Canadian dollars [$Can], year 2018 values) per enrolee was $Can18,243 for the experimental arm and $Can13,827 for the control arm. Devices were the highest cost component, at $Can13,446 per enrollee in the experimental arm. Clinical costs in the control arms were higher on average ($Can7202 vs. 2504) than those in the experimental arms. CONCLUSION: Data from industry-sponsored clinical trials can provide important information on the full costs of device-related interventions. As device costs rise, and as policy makers require more evidence on device-related treatments, the cost of medical device-driven interventions should be documented along with their effectiveness.
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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 | 0.025 | 0.073 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".