Clinical impact of Choosing Wisely Canada hepatology recommendations: an interrupted time-series analysis using data from GEMINI
Bibliographic record
Abstract
INTRODUCTION: Choosing Wisely Canada (CWC) Hepatology published recommendations in 2017 aiming to reduce low-value care and testing, including serum ammonia tests for hepatic encephalopathy (HE) and transfusion of blood products for minor invasive procedures. We explored the impact of these recommendations in reducing rates of low-value testing and care. METHODS: We included all medicine inpatients from 23 hospitals in Ontario, Canada from the GEMINI database between April 2015 and March 2022. Weekly rates of low-value care were measured before and after the CWC Hepatology recommendations (19 July 2017). Interrupted time-series regression models were used to assess time trends for rates of low-value care. Subgroup analysis was completed on hospitalisations under hepatology or gastroenterology services. RESULTS: Of 59 155 patients identified with liver disease, 17 906 developed HE and 11 676 cirrhosis patients underwent minor invasive procedures. In the HE cohort, there was no immediate change in the rate of ammonia tests with recommendations, but the overall rate decreased by 0.002 tests per hospitalisation per week (95% CI -0.00413 to -0.000009). With recommendations, we observed an increase in the rate of 0.242 (95% CI 0.010 to 0.474 transfusions/hospitalisation), but no significant difference in the rate change nor in the rate of platelet and vitamin K transfusions. There was no significant change in the rate of platelet and vitamin K transfusions. Hospitalisations under hepatology or gastroenterology services also did not have a change in rates of low-value care overall, except for ammonia tests where the rate decreased by 0.012 tests (95% CI -0.0177 to -0.00626 tests/hospitalisation) per week after recommendations. CONCLUSIONS: The CWC recommendations were associated with a reduction in the rate of serum ammonia tests, but not with transfusion of blood products. Thus, there remains an opportunity to reduce low-value care and application of clinical guidelines.
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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 | 0.013 | 0.056 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".