The patient perspective: arthritis care provided by Advanced Clinician Practitioner in Arthritis Care program-trained clinicians
Bibliographic record
Abstract
Kelly Warmington,1 Carol A Kennedy,2 Katie Lundon,3 Leslie J Soever,4 Sydney C Brooks,5 Laura A Passalent,6 Rachel Shupak,7 Rayfel Schneider,8 1Learning Institute, Hospital for Sick Children, 2Musculoskeletal Health and Outcomes Research, St Michael’s Hospital, 3Continuing Professional Development, Faculty of Medicine, University of Toronto, 4University Health Network, 5Ontario Division, Arthritis Society, 6Toronto Western Hospital, 7Division of Rheumatology, St Michael's Hospital, 8Division of Rheumatology, Hospital for Sick Children, University of Toronto, Toronto, ON, Canada Objective: To assess patient satisfaction with the arthritis care services provided by graduates of the Advanced Clinician Practitioner in Arthritis Care (ACPAC) program. Materials and methods: This was a cross-sectional evaluation using a self-report questionnaire for data collection. Participants completed the Patient–Doctor Interaction Scale, modified to capture patient–practitioner interactions. Participants completed selected items from the Group Health Association of America's Consumer Satisfaction Survey, and items capturing quality of care, appropriateness of wait times, and a comparison of extended-role practitioner (ERP) services with previously received arthritis care. Results: A total of 325 patients seen by 27 ERPs from 15 institutions completed the questionnaire. Respondents were primarily adults (85%), female (72%), and living in urban areas (79%). The mean age of participants was 54 years (range 3–92 years), and 51% were not working. Patients with inflammatory (51%) and noninflammatory conditions (31%) were represented. Mean (standard deviation) Patient–Practitioner Interaction Scale subscale scores ranged from 4.50 (0.60) to 4.63 (0.48) (1 to 5 [greater satisfaction]). Overall satisfaction with the quality of care was high (4.39 [0.77]), as was satisfaction with wait times (referral to appointment, 4.27 [0.86]; in clinic, 4.24 [0.91]). Ninety-eight percent of respondents felt the arthritis care they received was comparable to or better than that previously received from other health care professionals. Conclusion: Patients were very satisfied with and amenable to arthritis care provided by graduates of the ACPAC program. Our findings provide early support for the deployment and integration of ACPAC ERPs into the Ontario health care system and should inform future evaluation at the patient level. Keywords: arthritis, physical therapists, occupational therapy, education, continuing, patient satisfaction
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".