Utilization and cost comparison of current and optimal prescribing of nonsteroidal antiinflammatory drugs in Quebec, Canada.
Bibliographic record
Abstract
OBJECTIVE: Clinical practice guidelines recommend prophylactic use of gastroprotective agents (GPA) with nonselective nonsteroidal antiinflammatory drugs (nsNSAID) for patients at risk of gastrointestinal (GI) complications. We estimated the costs of cyclooxygenase-2 selective inhibitors, nsNSAID, and concurrent GPA prescribed in 2002 in Quebec, Canada, and compared these to estimated costs if prescribing followed guideline recommendations. METHODS: We used the Quebec government medical and pharmaceutical claims database (RAMQ). All prescriptions for NSAID and concurrent GPA dispensed between January 1 and December 31, 2002, were evaluated for continuously covered beneficiaries 18 years of age or older. Prescriptions were stratified by patient GI risk factors determined at the dispensing date of each prescription into low-, moderate-, elevated-, and high-risk categories. Five scenarios of "appropriate" NSAID therapy were identified using clinical practice guidelines. The potential effect on the prescription drug budget of implementing each of these scenarios was estimated. RESULTS: In total, 503,671 patients filled 1,863,171 prescriptions for NSAID, representing 41.1 million days of treatment with total expenditures of about dollar 94 million CDN for NSAID and concurrent GPA. Average actual daily costs for coxibs (rofecoxib and celecoxib), celecoxib, nsNSAID, and concurrent GPA were dollar 1.94, dollar 2.06, dollar 1.19, and dollar 2.30, respectively. Prescribing nsNSAID with GPA to all patients at moderate and elevated risks while prescribing NSAID without GPA to patients at low risk, and celecoxib with a GPA to patients at very high risk would have cost dollar 36.4 million more, mainly due to the additional cost of GPA. CONCLUSION: Compared to actual prescribing patterns, a prescribing strategy consistent with clinical practice guidelines can increase drug acquisition costs to the healthcare payer.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".