Cost‐Utility Analysis of a Multidisciplinary Strategy to Manage Osteoarthritis of the Knee: Economic Evaluation of a Cluster Randomized Controlled Trial Study
Bibliographic record
Abstract
OBJECTIVE: To determine if a pharmacist-initiated multidisciplinary strategy provides value for money compared to usual care in participants with previously undiagnosed knee osteoarthritis. METHODS: Pharmacies were randomly allocated to provide either 1) usual care and a pamphlet or 2) intervention care, which consisted of education, pain medication management by a pharmacist, physiotherapy-guided exercise, and communication with the primary care physician. Costs and quality-adjusted life-years (QALYs) were determined for patients assigned to each treatment and incremental cost-effectiveness ratios (ICERs) were determined. RESULTS: From the Ministry of Health perspective, the average patient in the intervention group generated slightly higher costs compared with usual care. Similar findings were obtained when using the societal perspective. The intervention resulted in ICERs of $232 (95% confidence interval [95% CI] -1,530, 2,154) per QALY gained from the Ministry of Health perspective and $14,395 (95% CI 7,826, 23,132) per QALY gained from the societal perspective, compared with usual care. CONCLUSION: A pharmacist-initiated, multidisciplinary program was good value for money from both the societal and Ministry of Health perspectives.
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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 | 0.010 | 0.016 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.008 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 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".