Priorities for High-quality Care in Rheumatoid Arthritis: Results of Patient, Health Professional, and Policy Maker Perspectives
Bibliographic record
Abstract
OBJECTIVE: To elucidate the essential elements of high-quality rheumatoid arthritis (RA) care in order to develop a vision statement and a set of strategic objectives for a national RA quality framework. METHODS: Focus groups and interviews were conducted by experienced qualitative researchers using a semistructured interview or focus group guide with healthcare professionals, patients, clinic managers, healthcare leaders, and policy makers to obtain their perspectives on elements essential to RA care. Purposive sampling provided representation of stakeholder types and regions. Recorded data was transcribed verbatim. Two teams of 2 coders independently analyzed the deidentified transcripts using thematic analysis. Strategic objectives and the vision statement were drafted based on the overarching themes from the qualitative analysis and finalized by a working group. RESULTS: A total of 54 stakeholders from 9 Canadian provinces participated in the project (3 focus groups and 19 interviews). Seven strategic objectives were derived from the qualitative analysis representing the following themes: (1) early access and timeliness of care; (2) evidence-informed, high-quality care for the ongoing management of RA and comorbidities; (3) availability of patient self-management tools and educational materials for shared decision making; (4) multidisciplinary care; (5) patient outcomes; (6) patient experience and satisfaction with care; and (7) equity, the last of which emerged as an overarching theme. The ultimate vision obtained was "ensuring patient-centered, high-quality care for people living with rheumatoid arthritis." CONCLUSION: The 7 strategic objectives that were identified highlight priorities for RA quality of care to be used in developing the National RA Quality Measurement Framework.
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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 | 0.043 | 0.044 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.009 | 0.005 |
| Scholarly communication | 0.010 | 0.005 |
| Open science | 0.002 | 0.007 |
| 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".