The Influence of Socioeconomic Status on Selection of Anticoagulation for Atrial Fibrillation
Bibliographic record
Abstract
IMPORTANCE: Without third-party insurance, access to marketed drugs is limited to those who can afford to pay. We examined this phenomenon in the context of anticoagulation for patients with nonvalvular atrial fibrillation (NVAF). OBJECTIVE: To determine whether, among older Ontarians receiving anticoagulation for NVAF, patients of higher socioeconomic status (SES) were more likely to switch from warfarin to dabigatran prior to its addition to the provincial formulary. DESIGN, SETTING AND PARTICIPANTS: Population-based retrospective cohort study of Ontarians aged 66 years and older, between 2008 and 2012. EXPOSURE: Socioeconomic status, as approximated by median neighborhood income. MAIN OUTCOMES AND MEASURE: We identified two groups of older adults with nonvalvular atrial fibrillation: those who appeared to switch from warfarin to dabigatran after its market approval but prior to its inclusion on the provincial formulary ("switchers"), and those with ongoing warfarin use during the same interval ("non-switchers"). RESULTS: We studied 34,797 patients, including 3183 "switchers" and 31,614 "non-switchers". We found that higher SES was associated with switching to dabigatran prior to its coverage on the provincial formulary (p<0.0001). In multivariable analysis, subjects in the highest quintile were 50% more likely to switch to dabigatran than those in the lowest income quintile (11.3% vs. 7.3%; adjusted odds ratio 1.50; 95% CI 1.32 to 1.68). Following dabigatran's addition to the formulary, the income gradient disappeared. CONCLUSIONS AND RELEVANCE: We documented socioeconomic inequality in access to dabigatran among patients receiving warfarin for NVAF. This disparity was eliminated following the drug's addition to the provincial formulary, highlighting the importance of timely reimbursement decisions.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".