Choosing Wisely: The Canadian Rheumatology Association’s List of 5 Items Physicians and Patients Should Question
Bibliographic record
Abstract
OBJECTIVE: To develop a list of 5 tests or treatments used in rheumatology that have evidence indicating that they may be unnecessary and thus should be reevaluated by rheumatology healthcare providers and patients. METHODS: Using the Delphi method, a committee of 16 rheumatologists from across Canada and an allied health professional generated a list of tests, procedures, or treatments in rheumatology that may be unnecessary, nonspecific, or insensitive. Items with high content agreement and perceived relevance advanced to a survey of Canadian Rheumatology Association (CRA) members. CRA members ranked these top items based on content agreement, effect, and item ranking. A methodology subcommittee discussed the items in light of their relevance to rheumatology, potential effect on patients, and the member survey results. Five candidate items selected were then subjected to a literature review. A group of patient collaborators with rheumatic diseases also reviewed these items. RESULTS: Sixty-four unique items were proposed and after 3 Delphi rounds, this list was narrowed down to 13 items. In the member-wide survey, 172 rheumatologists responded (36% of those contacted). The respondent characteristics were similar to the membership at large in terms of sex and geographical distribution. Five topics (antinuclear antibodies testing, HLA-B27 testing, bone density testing, bone scans, and bisphosphonate use) with high ratings on agreement and effect were chosen for literature review. CONCLUSION: The list of 5 items has identified starting points to promote discussion about practices that should be questioned to assist rheumatology healthcare providers in delivering high-quality care.
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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 | 0.033 | 0.083 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.008 | 0.004 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.006 | 0.005 |
| Insufficient payload (model declined to judge) | 0.012 | 0.003 |
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".