Investigating Associations Between Access to Rheumatology Care, Treatment, Continuous Care, and Healthcare Utilization and Costs Among Older Individuals With Rheumatoid Arthritis
Bibliographic record
Abstract
OBJECTIVE: To examine the association between rheumatologist access, early treatment, and ongoing care of older-onset rheumatoid arthritis (RA) and healthcare utilization and costs following diagnosis. METHODS: We analyzed data from a population-based inception cohort of individuals aged > 65 years with RA in Ontario, Canada, diagnosed between 2002 and 2014 with follow-up to 2019. We assessed 4 performance measures in the first 4 years following diagnosis, including access to rheumatology care, yearly follow-up, timely treatment, and ongoing treatment with a disease-modifying antirheumatic drug. We examined annual healthcare utilization, mean direct healthcare costs, and whether the performance measures were associated with costs in year 5. RESULTS: A total of 13,293 individuals met inclusion criteria. The mean age was 73.7 (SD 5.7) years and 68% were female. Total mean direct healthcare cost per individual increased annually and was CAD $13,929 in year 5. All 4 performance measures were met for 35% of individuals. In multivariable analyses, costs for not meeting access to rheumatology care and timely treatment performance measures were 20% (95% CI 8-32) and 6% (95% CI 1-12) higher, respectively, than where those measures were met. The main driver of cost savings among individuals meeting all 4 performance measures were from lower complex continuing care, home care, and long-term care costs, as well as fewer hospitalizations and emergency visits. CONCLUSION: Access to rheumatologists for RA diagnosis, timely treatment, and ongoing care are associated with lower total healthcare costs at 5 years. Investments in improving access to care may be associated with long-term health system savings.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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 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".