Geriatric Choosing Wisely choice of recommendations in France: a pragmatic approach based on clinical audits
Bibliographic record
Abstract
BACKGROUND: The international Choosing Wisely campaign seeks to improve the appropriateness of care, notably through large campaigns among physicians and users designed to raise awareness of the risks inherent in overmedication. METHODS: In deploying the Choosing Wisely campaign, the French Society of Geriatrics and Gerontology chose early operationalization via a tool for clinical audit over a limited area before progressive dissemination. This enabled validation of four consensual recommendations concerning the management of urinary tract infections, the prolonged use of anxiolytics, the use of neuroleptics in dementia syndromes, and the use of statins in primary prevention. The fifth recommendation concerns the importance of a dialogue on the level of care. It was written by patient representatives directly involved in the campaign. RESULTS: The first cross-regional campaign in France involved 5337 chart screenings in 43 health facilities. Analysis of the results showed an important variability in practices between institutions and significant percentage of inappropriate prescriptions, notably of psychotropic medication. DISCUSSION: The high rate of participation of target institutions shows that geriatrics professionals are interested in the evaluation and optimization of professional practices. Frequent overuse of psychotropic medication highlights the need of campaigns to raise awareness and encourage deprescribing.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.010 | 0.039 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".