Evidence-Based Cardiovascular Disease Medicines' Availability in Low-Cost Generic Drug Programs in the United States
Bibliographic record
Abstract
BACKGROUND: Low-cost generic programs (LCGPs) that expand access to affordable cardiovascular disease (CVD) medicines can assist patients in achieving desired cardiovascular outcomes. It is important that LCGPs offer CVD medicines that promote evidence-based prescribing. OBJECTIVE: To evaluate LCGPs' coverage of evidence-based CVD medications using a clinical framework that examines coverage of core treatments, coverage of options with the highest-quality evidence, and the variety of medication options and strengths that create choices and allow dosing titration. DESIGN: Cross-sectional study. SETTING: Publicly available LCGPs in March and April 2023 in the United States. PARTICIPANTS: 19 LCGPs. MEASUREMENTS: Proportion of LCGPs that offered evidence-based CVD medicines within a clinical framework for 6 CVDs (atrial fibrillation, heart failure, hyperlipidemia, hypertension, post-acute coronary syndrome secondary prevention, and stable angina) according to 4 availability metrics (breadth, choice, high-quality evidence, and titratability). RESULTS: The availability of CVD medication varied by program, drug, and CVD condition. Some programs had more breadth and choice of coverage for most CVDs (H-E-B, Kroger, Mark Cuban Cost Plus Drug Company, and Walmart), whereas many had more focused coverage and others markedly limited offerings. Nearly all LCGPs offered angiotensin-converting enzyme inhibitors, β-blockers, thiazides, and moderate-intensity statins, but availability was low for higher-cost or lower-use generics (antiplatelets and antiarrhythmics). Core pharmacotherapy coverage and choices were limited for atrial fibrillation and heart failure but widely available for hypertension and hyperlipidemia. LIMITATION: In-depth cost analysis was not investigated. CONCLUSION: Coverage of evidence-based medications for the 6 CVDs investigated varied by LCGP and condition. Because high availability of core CVD pharmacotherapy can enhance optimal disease state management, LCGPs should identify existing limitations in their coverage and continuously revise their formularies to improve the comprehensiveness of CVD medication coverage. PRIMARY FUNDING SOURCE: None.
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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 | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| 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".