Quality care in seniors with new‐onset rheumatoid arthritis: A Canadian perspective
Bibliographic record
Abstract
OBJECTIVE: To estimate the percentage of seniors with rheumatoid arthritis (RA) receiving disease-modifying antirheumatic drugs (DMARDs) within the first year of diagnosis. METHODS: We assembled an incident RA cohort from Ontario physician billing data for 1997-2006. We used a standard algorithm to identify 24,942 seniors with RA based on ≥ 2 billing codes ≥ 60 days apart but within 5 years. Drug exposures were obtained from pharmacy claims data. We followed subjects for 1 year, assessing if they had been exposed (defined as ≥ 1 prescription) to 1 or more DMARDs within the first year of RA diagnosis. We assessed secular trends and differences for subjects who had received rheumatology care (defined as ≥ 1 rheumatology encounter) versus those who had not. RESULTS: In total, only 39% of the 24,942 seniors with new-onset RA identified over 1997-2006 were exposed to DMARD therapy within 1 year of diagnosis. This increased from 30% in 1997 to 53% in 2006. Patients whose care involved a rheumatologist were more likely to be exposed to DMARDs than those who had no rheumatology care. In 2006, 67% of subjects receiving rheumatology care were exposed to DMARDs versus 21% of those with no rheumatology care. CONCLUSION: Improvements in RA care have occurred, but more efforts are needed. Subjects receiving rheumatology care are much more likely to receive DMARDs as compared to those with no rheumatology care. This emphasizes the key role of rheumatologists.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.003 |
| Insufficient payload (model declined to judge) | 0.001 | 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".