State AIDS Drug Assistance Programs
Bibliographic record
Abstract
BACKGROUND: The 54 state AIDS Drug Assistance Programs (ADAP) provide medications to HIV-infected persons with limited resources. Eligibility and coverage vary, raising concerns about health inequities. OBJECTIVE: To compare the relative clinical and economic performance of ADAP programs. RESEARCH DESIGN: A state-transition simulation model of HIV disease was used to explore the clinical consequences and lifetime costs associated with selected state policies. Clinical data came from the Multicenter AIDS Cohort Study, AIDS Clinical Trials Group Protocol 320, and other published randomized trials. Cost data came from the national AIDS Cost and Services Utilization Survey, and the 1999 Red Book. ADAP data came from National Association of State and Territorial AIDS Directors reports and interviews. MEASURES: Projected life expectancy, quality-adjusted life expectancy, total lifetime direct medical costs, cost-effectiveness in dollars per quality-adjusted life year (QALY) gained. RESULTS: ADAPs vary considerably in terms of formulary policies, health outcomes, expected costs, and cost-efficiency. Conservative projections, based on a cohort with starting mean CD4 count of 250 cells/microL, yield life expectancies ranging from 5.36 to 6.81 life years (4.69-6.01 quality-adjusted life years [QALYs]). Total per person lifetime direct medical costs range from $81,200 to $112,700; higher costs reflect increased spending on medications. Expected costs per QALY gained range from $7000 to $28,000. Under pessimistic assumptions regarding initial CD4 counts, drug efficacy, and discounting, the most comprehensive policy remains below $33,000/QALY. CONCLUSIONS: Even the most comprehensive ADAPs constitute a cost-effective use of HIV care resources. A uniform, national ADAP formulary warrants consideration.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.068 | 0.007 |
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".