Choosing Wisely: An idea worth sustaining
Bibliographic record
Abstract
OBJECTIVES: To evaluate the sustainability potential of Choosing Wisely (CW) to address unnecessary medical care at Ontario community hospitals. DATA SOURCES/STUDY SETTING: Ontario community hospitals and their affiliated family health teams (FHTs). STUDY DESIGN: A mixed-methods study involving the administration of a validated sustainability survey to CW implementation teams followed by their participation in focus groups. DATA COLLECTION/EXTRACTION METHODS: Survey data were collected using an Excel file with an embedded, automated scoring system. We collated individual survey scores and generated aggregate team scores. We also performed descriptive statistics for quantitative data (frequencies, means). Qualitative data were triangulated with quantitative assessments to support data interpretations using the meta-matrix method. PRINCIPAL FINDINGS: Fifteen CW implementation teams across four Ontario community hospitals and six affiliated primary care FHTs participated. CW priority areas investigated were de-prescribing of proton pump inhibitors (PPIs) and reducing Pre-Op testing and BUN/Urea lab testing. Survey results showed steady improvements in sustainability scores from baseline to final follow-up among most implementation teams: 10% increase for PPI de-prescribing (six FHTs) and 2% increase (three hospital teams); 18% increase in BUN/Urea lab testing (three hospital teams). Regardless of site or CW priority area, common facilitators were fit with existing processes and workflows, leadership support, and optimized team communication; common challenges were lack of awareness and buy-in, leadership engagement or a champion, and lack of fit with existing workflow and culture. All teams identified at least one challenge for which they co-designed and implemented a plan to maximize the sustainability potential of their CW initiative. CONCLUSIONS: Evaluating the sustainability potential of an innovation such as Choosing Wisely is critical to ensuring that they have the best potential for impact. Our work highlights that implementation teams can be empowered to influence implementation efforts and to realize positive outcomes for their health care services and patients.
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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 | 0.074 | 0.088 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.008 | 0.058 |
| Scholarly communication | 0.016 | 0.028 |
| Open science | 0.004 | 0.011 |
| Research integrity | 0.006 | 0.008 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".