Exploring the Potential Cost-Effectiveness of Patient Decision Aids for Use in Adults with Obstructive Sleep Apnea
Bibliographic record
Abstract
BACKGROUND: There is increasing evidence highlighting the effectiveness of patient decision aids (PtDAs), but evidence supporting their cost-effectiveness is lacking. We consider patients with obstructive sleep apnea (OSA), in whom a PtDA may decrease nonadherence to treatment by empowering patients to receive the option that is most congruent with their own values. OBJECTIVE: To determine the potential costs and benefits of delivering a PtDA to patients with moderate OSA. METHODS: A Markov cohort decision-analytic model was developed for patients with moderate OSA, comparing a PtDA to usual care over 5 years from a societal perspective. Data for patient preference for treatment options was taken from a recent randomized crossover trial, event data (cardiovascular, motor vehicle accidents) came from national databases and published literature. Potential improvements in adherence are unknown, so we considered a realistic range of values. Outcome measures were 5-year costs (in 2010 Canadian dollars), quality-adjusted life years (QALYs), and the incremental cost-effectiveness ratio (ICER). RESULTS: When adherence to treatment was unchanged, the PtDA strategy was dominated by incurring lower QALYs and higher costs. When nonadherence was decreased by 20% in the PtDA arm (corresponding to an increase in adherence from 63% to 70% for continuous positive airway pressure and from 77% to 82% for mandibular advancement splints in year 1), the ICER fell to $62,414/QALY. Costs associated with the treatment devices and delivering the PtDA had the greatest effect on cost-effectiveness. LIMITATIONS: The model relies on surrogate measures and opinions for key parameters. CONCLUSIONS: The cost-effectiveness of PtDAs will depend on contextual factors, but a framework is described for properly considering their long-term cost-effectiveness. A number of important questions around the appropriateness of benefit measurement for PtDA trials are highlighted.
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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 | 0.002 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".