The Effects of Continuity of Rheumatology Care on Emergency Department Utilization and Hospitalizations for Individuals With Early Rheumatoid Arthritis: A Population-Based Study
Bibliographic record
Abstract
OBJECTIVE: To determine if continuity of rheumatology care influences rates of emergency department (ED) visits and hospitalizations in patients with rheumatoid arthritis (RA). METHODS: A closed inception cohort of patients with RA diagnosed between 2000 and 2009 were followed until December 31, 2019. During the first 5 years following diagnosis, we categorized patients into 3 rheumatology care continuity groups (high, intermediate, and not retained in rheumatology care). Using a landmark analysis, we compared rates of ED visits and hospitalizations during follow-up. Multivariable Poisson regression models were used to estimate rate ratios (RRs), adjusting for demographics, comorbidities, and health services access and supply measures. RESULTS: The cohort included 38,528 patients, of which 57.7% (n = 22,221) were classified in the high rheumatology continuity group, 17.2% (n = 6636) were in the intermediate group, and 25.1% (n = 9671) were not retained in rheumatology care. Relative to the high continuity group, both the intermediate and nonretention groups had higher ED rates (RR 1.14, 95% CI 1.08-1.20, and RR 1.12, 95% CI 1.08-1.16, respectively). The intermediate group also experienced higher adjusted hospitalization rates (207.4, 95% CI 203.0-211.8 per 1000 person-years [PY]) than the high continuity group (193.5, 95% CI 191.4-195.6 per 1000 PY). CONCLUSION: Patients with RA with higher continuity of rheumatology care had lower rates of ED visits and hospitalizations compared to those who did not receive continuous rheumatology care during the first 5 years of follow-up. These findings provide evidence to support the value of early and continuous rheumatology care for reducing hospitalizations and ED visits.
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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 | 0.002 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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 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".