Evaluation of Clinical Innovation: A Gray Zone in the Ethics of Modern Clinical Practice?
Bibliographic record
Abstract
BACKGROUND: Various stakeholders can have differing opinions regarding ethical review when introducing new procedures with patients. OBJECTIVE: This pilot study examines the way in which Research Ethics Boards (REBs; Institutional Review Boards) and clinical biochemists (CBs; laboratory medicine specialists) differ in their interpretation of what is research and what should be considered common practice versus innovation versus experimentation when introducing new procedures with patients. It also explores whether these groups agree on who is responsible for the ethical review of new procedures. METHODS: A validated case scenario for the introduction of a new diagnostic test into clinical practice was sent to CBs and REBs across Canada. Participants were asked to determine whether the scenario constituted research; whether the test procedure should be considered as experimental, innovative, or commonly accepted care; and whether the project required approval by a REB and, if not, who should be responsible for ethical review. RESULTS: Results showed 81% of 37 CBs and 52% of 27 REBs identified the scenario as research. Responsibility for ethical review was assigned to REBs by 44% of REBs and 54% of CBs. Of all participants, 53% classified the test procedure as 'innovative', 8% as 'experimental', whereas 17% classified it as 'commonly accepted'. CONCLUSIONS: This pilot study indicates a substantial variation in the ethical assessment of innovation in clinical care. This suggests the need to further elaborate on the types of innovation in health care and categorize the nature of the risks associated with each.
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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 | 0.422 | 0.391 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.009 | 0.124 |
| Scholarly communication | 0.019 | 0.014 |
| Open science | 0.003 | 0.019 |
| Research integrity | 0.007 | 0.011 |
| 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".