Determinants of the Cost of Health Services Used by Veterans With HIV
Bibliographic record
Abstract
BACKGROUND: The effect of adherence, treatment failure, and comorbidities on the cost of HIV care is not well understood. OBJECTIVE: To characterize the cost of HIV care including combination antiretroviral treatment (ART). RESEARCH DESIGN: Observational study of administrative data. SUBJECTS: Total 1896 randomly selected HIV-infected patients and 288 trial participants with multidrug-resistant HIV seen at the US Veterans Health Administration (VHA). MEASURES: Comorbidities, cost, pharmacy, and laboratory data. RESULTS: Many HIV-infected patients (24.5%) of the random sample did not receive ART. Outpatient pharmacy accounted for 62.8% of the costs of patients highly adherent with ART, 32.2% of the cost of those with lower adherence, and 6.2% of the cost of those not receiving ART. Compared with patients not receiving ART, high adherence was associated with lower hospital cost, but no greater total cost. Individuals with a low CD4 count (<50 cells/mm) incurred 1.9 times the cost of patients with counts >500. Most patients had medical, psychiatric, or substance abuse comorbidities. These conditions were associated with greater cost. Trial participants were less likely to have psychiatric and substance abuse comorbidities than the random sample of VHA patients with HIV. CONCLUSIONS: Patients receiving combination ART had higher medication costs but lower acute hospital cost. Poor control of HIV was associated with higher cost. The cost of psychiatric, substance abuse, rehabilitation, and long-term care and medications other than ART, often overlooked in HIV studies, was substantial.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".