Effectiveness of an Outreach Model of Care for Rheumatology Specialty Clinics to an On-Reserve First Nations Community
Bibliographic record
Abstract
A model of care consisting of rheumatology specialty services embedded in the primary care system on a First Nations reserve was instituted to reduce barriers to care and improve inflammatory arthritis outcomes for patients. We assessed the effectiveness of this model of care on disease activity measures and patient-reported outcomes over 7 years. Patients were enrolled in a longitudinal cohort at the Siksika Nation in Alberta. Clinical characteristics, treatment recommendations and disease activity measures were systematically recorded over follow-up. Mixed-model regression was performed to determine rates of change for continuous measures. 59 participants (78% female; M = 47 years, SD = 13), predominantly with rheumatoid arthritis (RA; n = 36), were followed for an average of 29 months (SD = 23). Swollen and tender joint counts decreased significantly (change per month: -0.20, 95% CI -0.29 to -0.10, and -0.20, 95%CI -0.34 to -0.06, respectively) but pain, physician global and function scores did not significantly improve (all p > 0.05). Patient global evaluation scores worsened over time (change per month 0.08, 95%CI 0.029 to 0.131, p = 0.002). Inflammatory markers improved at a slower rate in patients with incident compared to incident disease. Disease-modifying agents were escalated for moderate or high disease activity at 64% of RA visits, with justifications for not escalating or application of local treatment approaches in all but one instance. Despite improvement in swollen and tender joint counts and adherence to current treatment paradigms, patient-reported outcomes did not significantly improve during follow-up. Further innovation is required to meet relevant outcomes.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| 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".