Cost-effectiveness of treating influenzalike illness with oseltamivir in the United States
Bibliographic record
Abstract
PURPOSE: The cost-effectiveness of treating influenzalike illness (ILI) with oseltamivir in the United States was assessed. METHODS: A decision-analysis model was developed with a one-year time horizon to assess the cost-effectiveness of oseltamivir compared with usual care from societal and payer perspectives for four patient populations: high-risk adults, healthy adults, elderly adults, and children. The model used efficacy data from oseltamivir clinical trials and other published literature and assumed oseltamivir was effective only in individuals infected with influenza virus not resistant to oseltamivir and treated within 48 hours of symptom onset. Direct medical costs were based on resources used; indirect costs were estimated based on time lost from work due to illness and premature mortality. Base-case estimates were tested in one-way sensitivity and variability analyses. RESULTS: From a societal perspective, oseltamivir was cost-effective across all populations modeled, with an incremental cost per quality-adjusted life-year gained of $5,388, $6,317, $7,652, and $16,176 for high-risk adults, children, elderly adults, and healthy adults, respectively. Results were similar from a payer perspective. When indirect costs were included (for all populations except elderly adults), oseltamivir was cost saving. In sensitivity analyses, oseltamivir remained cost-effective across all patient populations for all values tested, except the probability of developing influenza-related pneumonia. Variability analyses showed that oseltamivir remained cost-effective under most scenarios tested. CONCLUSION: Base-case results and sensitivity analyses from a decision-analysis model found that treatment of ILI with oseltamivir was cost-effective compared with usual care from U.S. payer and societal perspectives in all patient populations studied when only direct costs were considered.
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 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 | 0.005 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".