A Canadian Advanced Physiotherapist Practitioner Shared-Care Model in Pediatric Rheumatology Offers Safe and Quality Care in the Management of Juvenile Idiopathic Arthritis—Comparing Key Performance Indicators with the PR-COIN Registry
Bibliographic record
Abstract
Background/Objectives: Canadian Advanced Physiotherapist Practitioner (APP) roles have existed for over 25 years in pediatric rheumatology. The APP can manage many common pediatric rheumatic conditions most often in Shared-Care Models (SCMs) with pediatric rheumatologists (PRs). The quality of care children receive in an APP SCM compared to traditional care is unknown. The Pediatric Rheumatology Care and Outcomes Improvement Network (PR-COIN) tracks quality measures as Key Performance Indicators (KPIs) in juvenile idiopathic arthritis (JIA) care. This study aimed to analyze the frequency of KPIs documented in a pediatric rheumatology APP SCM from a single center and compare to PR-COIN’s performance targets to assess the quality and safety of care. Methods: A retrospective chart review of JIA cases managed in a pediatric rheumatology APP SCM over a 2-year period was conducted. KPIs for disease activity, safety monitoring and access to care were evaluated. Frequency of KPI documentation by the APP were compared to target performance goals (≥40, ≥70 or ≥80% documentation rate depending on KPI) and with PR-COIN data from the Same Center (SC) (three rheumatologists) and PR-COIN (15 centers). Results: Documented KPIs were compared between the APP SCM, SC and PR-COIN registry (138; 140; 11,431 eligible visits, respectively) between June 2022–May 2024. Demographics were similar between groups. Increased percentages of patients with polyarticular rheumatoid factor positive and psoriatic subtypes were seen by APP compared to SC and PR-COIN. Documentation frequency of all disease activity and safety monitoring KPI performance goals were either higher in the APP SCM or comparable to SC and PR-COIN. Conclusions: The pediatric rheumatology APP SCM exceeded PR-COIN performance goals for KPI documentation, establishing a high level of quality and safety of care for children with JIA when managed in this model of care. Next steps include replicating this study in other pediatric rheumatology centers with an APP SCM.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".