Abstract 11314: Essential and Evidence-Based Cardiovascular Disease Medicine Availability in Low-Cost Generic Drug Plans
Bibliographic record
Abstract
Introduction: Patients’ lack of access to affordable cardiovascular disease (CVD) medicines poses a crucial barrier to achieving desired cardiovascular outcomes. Many pharmacies have launched low-cost generic programs (LCGP) to expand medication accessibility. It is uncertain whether LCGPs include CVD drugs recommended by World Health Organization Essential Medicines List (WHO EML) and promote evidence-based prescribing. Our study aimed to estimate the availability of essential and guideline-recommended CVD medicines on LCGP in the United States (US). Methods: We selected 6 CVD conditions: atrial fibrillation (AF), heart failure (HF), hyperlipidemia (HLD), hypertension (HTN), stable angina (SA), and secondary prevention (SPX). LCGPs in the US with publicly available formularies were identified in February 2022. We used the 22 nd WHO EML edition and Class 1A recommendations (1ARec) from current CVD guidelines as reference standards. Availability was estimated using the proportion of coverage for each LCGP overall, and by condition. Results: Nineteen LCGPs were included. There were 122 WHO EML and 155 1ARec CVD drugs. No LCGPs offered at least 50% of WHO EML and 1ARec. Both WHO EML and 1ARec analyses showed that 9 of 19 LCGPs covered at least 30% of listed medications. Out of the 19 LCGPs, the proportion of essential and evidence-based CVD medicine availability was highest at Kroger (46.3% and 47.9%) and lowest at Costco (5.0% and 6.1%), respectively. Higher availability was observed for HLD medications: only TOPS and the Mark Cuban Plan had at least 80% of WHO EML available, and only the Mark Cuban Plan had at least 80% of 1ARec medications covered. HTN drugs were least available for both. Conclusion: The accessibility of CVD medicines is low in LCGP formularies with variation in availability by pharmacy and condition. To optimize the accessibility of CVD medicines and health outcomes, pharmacies with LCGPs should offer more essential and evidence-based CVD medicines.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.009 | 0.040 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.005 | 0.009 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".