Rheumatology Rapid Access Clinic: An Accelerated Access Model of Care
Bibliographic record
Abstract
Objectives The Canadian healthcare system is well-regarded for its dedication to provide equitable care to all residents. Despite this commitment, concerns about wait times and access to care prevail, especially for patients transitioning from primary to specialized care.[1] In particular, wait times for rheumatology consultation can be lengthy.[2] In Ontario, the average wait time for assessment of suspected inflammatory arthritis is 74 days, far exceeding the benchmark target of 4 weeks.[3] Key drivers of longer wait times include the incongruity between rheumatology workforce supply and demand, which is further exacerbated by the increasing volume of patients. The lack of access to timely rheumatology consultation is predicted to worsen in the coming years2. To address this gap in access, a Rheumatology Rapid Access Clinic (RAC) led by an Advanced Clinic Practitioner in Arthritis Care (ACPAC) trained extended role practitioner (ERP) was established at Mount Sinai Hospital (MSH). A quality improvement project was undertaken to assess the impact of the RAC on timely access to care, reduction of emergency department readmissions, and the identification of diagnostic frequencies and subsequent absorption into the hospital’s Rheumatology Division. Methods Patients presenting to the MSH Emergency Department (ED) or Family Health Team (FHT), with suspected or confirmed rheumatologic conditions, as diagnosed by the attending practitioners/physicians, were referred to the RAC based on clinical need for expedited care. An ERP conducts a comprehensive assessment, including referring for appropriate laboratory tests and imaging per established medical directives. Thereafter, a treatment plan is initiated in collaboration with the attending rheumatologist. Results During the 10-month project period (September 2023 to July 2024), the RAC assessed a total of 96 patients. Of those referred, 94.1% attended their appointments. The majority of patients were female (59.4%). The average patient age was 50.0 years. The average time from referral to the initial appointment was 9.6 working days. Approximately 9.3% of the patients returned to the MSH ED with 3 patients re-referred from the RAC for medical concerns. Gout was the most frequently assessed condition, accounting for 18% of cases. 56% of the patients were integrated into the rheumatologists’ practice for ongoing care. Conclusion A Rheumatology RAC led by an ACPAC trained ERP facilitated timely and effective assessment and treatment planning for patients referred from primary or emergent care. This approach has the potential to optimize outcomes and could serve as a model for similar settings facing challenges with access to care. [1.] Bonello JP. University of Toronto Medical Journal 2023;100:29-3. [2.] Kwok TS. Clinical Rheumatology 2023;42(4):1205-1. [3.] Widdifield J. CMAJ Open 2016;4:E205-12.
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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 | 0.005 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.005 | 0.007 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.018 | 0.003 |
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".