Evaluation of Real-World Healthcare Resource Utilization and Associated Costs in Children with Juvenile Idiopathic Arthritis: A Canadian Retrospective Cohort Study
Bibliographic record
Abstract
INTRODUCTION: Juvenile idiopathic arthritis (JIA) is a chronic rheumatic disease, whose multifaceted care path can lead to significant expenditure for the healthcare system. We aim to assess the real-world healthcare resource use (HCRU) and associated cost for children with JIA in a single center in Canada. METHODS: A single-center consecutive cohort of newly diagnosed patients with JIA attending the pediatric rheumatology clinic from 2011 to 2019 was identified using an administrative data algorithm and electronic medical charts. HCRU was estimated from six administrative health databases that included hospital admissions, emergency, outpatient care, practitioners' visits, medication, and laboratory and imaging tests. Costs were assigned using appropriate sources. We reported the yearly overall and JIA-associated HCRU and costs 5 years prior to and 6 years after the first visit to the pediatric rheumatologist. The Zhao and Tian estimator was used to calculate cumulative mean costs over a 6-year timeframe. Results were stratified by disease subtype. RESULTS: A total of 389 patients were identified. The yearly total overall mean costs per patient ranged between $804 and $4460 during the 5 years prior to the first visit to the pediatric rheumatologist and $8529 and $10,651 for the 6 years after. Medication cost, driven by use of biologic therapies, and outpatient visits were the greatest contributor to the total cost. The overall cumulative mean cost for 6 years of care was $48,649 per patient, while the JIA-associated cumulative mean cost was $26,820 per patient. During the first year of rheumatology care, systemic onset JIA had the highest cumulative mean overall cost, while oligoarticular JIA had the lowest cumulative mean cost. CONCLUSION: The care pathway for children with JIA can be expensive, and complex-and varies by JIA subtype. Although the yearly total mean cost per patient was constant, the distribution of costs changes over time with the introduction of biologic therapies later in the care pathway. This study provides a better understanding of the JIA costs profile and can help inform future economic studies.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.008 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".