Appointments by Choice: An Implementation Pilot Study for Patient-Initiated Follow-Up Care in Rheumatoid Arthritis
Bibliographic record
Abstract
Objectives The aim of the study was to conduct an implementation pilot for Appointments by Choice (ABC), a new patient-initiated follow-up model seeking to optimize follow-up efficiency and patient-centeredness of rheumatoid arthritis (RA) care. Objectives were to evaluate patient recruitment and early implementation outcomes. Methods The implementation pilot started in January 2024 at a single rheumatology clinic in Calgary. Eligible patients had (1) established RA, (2) well-controlled disease, (3) no major medication changes, and (4) no other active complex conditions. Patients and providers used a discussion tool for shared decision-making about moving from regular care to the ABC pathway.[1] This included scheduling a new follow-up interval of 12-24+ months, a reduction compared to usual care. Between rheumatologist appointments, patient care was managed through a pharmacist-led clinic. Self-care was encouraged using a flare action plan. Baseline demographics were collected via survey and chart review. Feasibility was measured through recruitment numbers, ABC pathway adherence, flare clinic workload, and implementation adaptations using the FRAME criteria.[1] Preliminary data on ABC recruitment and feasibility were summarized using descriptive statistics. Results Over 8 months, 38/108 (35.2%) eligible individuals with RA chose to adopt the ABC pathway (Figure). 28 participants provided reasons for declining. Common reasons included lack of time/interest in research (n=6), concerns about reduced care access (n=3), and preference for usual care (n=5). Mean participant age was 59.5±11.0 years, with 82.7% identifying as White and 10.3% as Southeast Asian. Mean RA duration was 13.3±9.1 years. Only 2/38 (5.3%) participants withdrew from the study and returned to usual care, due to a major RA flare or inability to complete the baseline questionnaire. 36/38 (94.7%) remained on the pathway. The pharmacist-led flare clinic conducted 2 flare-related follow-up calls, 2 medication renewals, and 8 calls for other medical needs. One participant required an in-person follow-up. 32 implementation challenges were noted, 8 of which resulted in minor adaptations. Adaptations include opening recruitment to individuals with (1) RA with minor medication changes and (2) those with palindromic rheumatism who were on treatment and had positive serology; (3) adjusting recruitment timing to align with biologic renewal schedules, and (4) improving physician-pharmacist communication using a standardized electronic health record “smartphrase” for detailing follow-up needs. Conclusion The ABC implementation pilot has provided valuable learnings for recruitment, implementation, and ongoing care when using patient-initiated follow-up models for RA care. Post-pilot analyses will provide additional insights into ABC safety, feasibility, and potential benefits. [1.] Wiltsey Stirman S. Implementation Science 2019;14:58. Supported by a CIORA grant
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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 | 0.032 | 0.032 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".