<scp>Cost‐effectiveness</scp> of telephone cognitive behavioral therapy for <scp>osteoarthritis‐related</scp> insomnia
Bibliographic record
Abstract
BACKGROUND: Osteoarthritis-related insomnia is the most common form of comorbid insomnia among older Americans. A randomized clinical trial found that six sessions of telephone-delivered cognitive behavioral therapy for insomnia (CBT-I) improved sleep outcomes in this population. Using these data, we evaluated the incremental cost-effectiveness of CBT-I from a healthcare sector perspective. METHODS: The study was based on 325 community-dwelling older adults with insomnia and osteoarthritis pain enrolled with Kaiser Permanente of Washington State. We measured quality-adjusted life years (QALYs) using the EuroQol 5-dimension scale. Arthritis-specific quality of life was measured using the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC). Insomnia-specific quality of life was measured using the Insomnia Severity Index (ISI) and nights without clinical insomnia (i.e., "insomnia-free nights"). Total healthcare costs included intervention and healthcare utilization costs. RESULTS: Over the 12 months after randomization, CBT-I improved ISI and WOMAC by -2.6 points (95% CI: -2.9 to -2.4) and -2.6 points (95% CI: -3.4 to -1.8), respectively. The ISI improvement translated into 89 additional insomnia-free nights (95% CI: 79 to 98) over the 12 months. CBT-I did not significantly reduce total healthcare costs (-$1072 [95% CI: -$1968 to $92]). Improvements in condition-specific measures were not reflected in QALYs gained (-0.01 [95% CI: -0.01 to 0.01]); at a willingness-to-pay of $150,000 per QALY, CBT-I resulted in a positive net monetary benefit of $369 with substantial uncertainty (95% CI: -$1737 to $2270). CONCLUSION: CBT-I improved sleep and arthritis function without increasing costs. These findings support the consideration of telephone CBT-I for treating insomnia among older adults with comorbid OA. Our findings also suggest potential limitations of the general quality of life measures in assessing interventions designed to improve sleep and arthritis outcomes.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 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".