Community Pharmacy–Based Inducement Programs Associated With Better Medication Adherence: A Cohort Study
Bibliographic record
Abstract
BACKGROUND: Inducement programs can promote customer loyalty; however, the clinical effects of these programs are unknown. OBJECTIVE: To examine relationships among inducement program use, medication adherence, and health outcomes. METHODS: Alberta residents with ≥ 1 physician visit for diabetes or hypertension between April 2008 and March 2014 were eligible for this study and included if they were new statin users and alive at least 455 days after the first statin dispensation. Group assignment was based on whether all statin dispensations in the first year were obtained from pharmacies with or without inducement programs. Discontinuation was defined as no statin dispensations between 275 and 455 days after the first statin dispensation. Acute coronary syndrome (ACS) hospitalizations or deaths were identified between 456 days and 3 years after the first statin dispensation. Multivariable regression analyses were conducted to examine relationships among inducement program use, discontinuation, and ACS events. RESULTS: Among the 159 998 new statin users, mean age was 60.2 (±13.7) years and 67 534 (42%) were women. Statin discontinuation occurred in 22 455 (28.9%) of 77 803 inducement group participants and 25 816 (31.4%) of 82 195 noninducement group participants (adjusted odds ratio = 0.88; 95% CI = 0.86-0.90). Risk of an ACS event was similar between groups (adjusted hazard ratio = 1.00; 95% CI 0.92-1.08); however, discontinuing statin therapy was associated with a higher risk of an ACS event (adjusted hazard ratio = 1.27; 95% CI = 1.16-1.39). CONCLUSIONS: Inducement programs are associated with better adherence and not directly associated with risk of health outcomes.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".