A <scp>Population‐Based</scp> Study Evaluating Retention in Rheumatology Care Among Patients With Rheumatoid Arthritis
Bibliographic record
Abstract
OBJECTIVE: The study objective was to assess adherence to system-level performance measures measuring retention in rheumatology care and disease modifying anti-rheumatic drug (DMARD) treatment in rheumatoid arthritis (RA). METHODS: We used a validated health administrative data case definition to identify individuals with RA in Ontario, Canada, between 2002 and 2014 who had at least 5 years of potential follow-up prior to 2019. During the first 5 years following diagnosis, we assessed whether patients were seen by a rheumatologist yearly and the proportion dispensed a DMARD yearly (in those aged ≥66 for whom medication data were available). Multivariable logistic regression analyses were used to estimate the odds of remaining under rheumatologist care. RESULTS: The cohort included 50,883 patients with RA (26.1% aged 66 years and older). Over half (57.7%) saw a rheumatologist yearly in all 5 years of follow-up. Sharp declines in the percentage of patients with an annual visit were observed in each subsequent year after diagnosis, although a linear trend to improved retention in rheumatology care was seen over the study period (P < 0.0001). For individuals aged 66 years or older (n = 13,293), 82.1% under rheumatologist care during all 5 years after diagnosis were dispensed a DMARD annually compared with 31.0% of those not retained under rheumatology care. Older age, male sex, lower socioeconomic status, higher comorbidity score, and having an older rheumatologist decreased the odds of remaining under rheumatology care. CONCLUSION: System-level improvement initiatives should focus on maintaining ongoing access to rheumatology specialty care. Further investigation into causes of loss to rheumatology follow-up is needed.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".