The impact of the Choosing Wisely Canada campaign on the simultaneous use of angiotensin-converting-enzyme inhibitors and angiotensin receptor blockers: interrupted time-series analysis
Bibliographic record
Abstract
BACKGROUND: Choosing Wisely is a high-profile campaign seeking to reduce the use of low-value care. We investigated the impact of a Choosing Wisely Canada recommendation against using a combination of angiotensin-converting-enzyme (ACE) inhibitors and angiotensin receptor blockers (ARBs) for the management of hypertension, heart failure or diabetic nephropathy on population-level use of these medications in British Columbia, Canada. METHODS: We identified all people (any age) who were continuously registered with BC's Medical Service Plan between 2010 and 2017 with the targeted conditions. Using prescription claims data and an interrupted time-series analysis, we estimated the number of people on combination therapy per month, the proportion of days covered (PDC) by combination therapy per month and proportion of all combination prescriptions started per month in the 2 years before and after the introduction of the recommendation on Oct. 29, 2014. RESULTS: Of 1 104 593 people (mean age 65 yr, standard deviation 16 yr) in our study cohort, 4.6% were exposed to combination therapy, largely prescribed by family physicians (84%). The number of people on combination therapy and the PDC were declining before the recommendation, but the proportion of combination prescriptions started in the 2 years before the recommendation was increasing. After the recommendation, we observed no statistically significant changes in any outcome. The pre-existing downward trend of the monthly number of people decelerated (16.8, 95% confidence interval [CI] 14.0 to 19.5) and the proportion of prescriptions started increased (0.13%, 95% CI 0.08% to 0.18%). INTERPRETATION: The Choosing Wisely Canada recommendation against using a combination of ACE inhibitors and ARBs was not associated with reduced combination therapy use in the targeted conditions. The observed pre-existing declines in this practice questions the process of selecting recommendations, and the optimal implementation and value of Choosing Wisely campaigns without other reinforcing interventions.
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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 | 0.007 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 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".