Patient perspectives on de‐simplifying their single‐tablet co‐formulated antiretroviral therapy for societal cost savings
Bibliographic record
Abstract
OBJECTIVES: The incremental costs of expanding antiretroviral (ARV) drug treatment to all HIV-infected patients are substantial, so cost-saving initiatives are important. Our objectives were to determine the acceptability and financial impact of de-simplifying (i.e. switching) more expensive single-tablet formulations (STFs) to less expensive generic-based multi-tablet components. We determined physician and patient perceptions and acceptance of STF de-simplification within the context of a publicly funded ARV budget. METHODS: Programme costs were calculated for patients on ARVs followed at the Southern Alberta Clinic, Canada during 2016 (Cdn$). We focused on patients receiving Triumeq® and determined the savings if patients de-simplified to eligible generic co-formulations. We surveyed all prescribing physicians and a convenience sample of patients taking Triumeq® to see if, for budgetary purposes, they felt that de-simplification would be acceptable. RESULTS: Of 1780 patients receiving ARVs, 62% (n = 1038) were on STF; 58% (n = 607) of patients on STF were on Triumeq®. The total annual cost of ARVs was $26 222 760. The cost for Triumeq® was $8 292 600. If every patient on Triumeq® switched to generic abacavir/lamivudine and Tivicay® (dolutegravir), total costs would decrease by $4 325 040. All physicians (n = 13) felt that de-simplifying could be safely achieved. Forty-eight per cent of 221 patients surveyed were agreeable to de-simplifying for altruistic reasons, 27% said no, and 25% said maybe. CONCLUSIONS: De-simplifying Triumeq® generates large cost savings. Additional savings could be achieved by de-simplifying other STFs. Both physicians and patients agreed that selective de-simplification was acceptable; however, it may not be acceptable to every patient. Monitoring the medical and cost impacts of de-simplification strategies seems warranted.
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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 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".