Models of Arthritis Care: A Systems-level Evaluation of Acceptability as a Dimension of Quality of Care
Bibliographic record
Abstract
OBJECTIVE: To describe a systems-level baseline evaluation of central intake (CI) and triage systems in arthritis care within Alberta, Canada. The specific objectives were to (1) describe a process for systems evaluation for the provision of arthritis care; (2) report the findings of the evaluation for different clinical sites that provide arthritis care; and (3) identify opportunities for improving appropriate and timely access based on the findings of the evaluation. METHODS: The study used a convergent mixed methods design. Surveys and semistructured interviews were the main data collection methods. Participants were recruited through 2 rheumatology clinics and 1 hip and knee clinic providing CI and triage, and included patients, referring physicians, specialists, and clinic staff who experienced CI processes. RESULTS: A total of 237 surveys were completed by patients (n = 169), referring physicians (n = 50), and specialists (n = 18). Interviews (n = 25) with care providers and patients provided insights to the survey data. Over 95% of referring physicians agreed that the current process of CI was satisfactory. Referring physicians and specialists reported issues with the referral process and perceived support in care for wait-listed patients. Patients reported positive experiences with access and navigation of arthritis care services but expressed concerns around communication and receiving minimal support for self-management of their arthritis before and after receiving specialist care. CONCLUSION: This baseline evaluation of CI and triage for arthritis care indicates satisfaction with the service, but areas that require further consideration are referral completion, timely waiting lists, and further supporting patients to self-manage their arthritis.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.069 | 0.069 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.005 | 0.008 |
| Scholarly communication | 0.011 | 0.004 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.001 | 0.002 |
| 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".