Patient Satisfaction with Pharmacist‐Led Collaborative Follow‐Up Care in an Ambulatory Rheumatology Clinic
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
OBJECTIVES: Patient satisfaction is known to increase with pharmacist intervention in general outpatient clinics and with nurse-led care in rheumatology clinics. The aim of the present study was to describe and compare patient satisfaction with two different types of care: a pharmacist physician collaborative model and a traditional physician model in a rheumatology clinic setting. METHODS: A cross-sectional survey of inflammatory arthritis patients seen during a follow-up visit in Edmonton, Alberta, Canada, was conducted over a ten-week period. Patient satisfaction was measured using a modified version of the validated Leeds Satisfaction Questionnaire, which uses a five-point Likert scale to measure six dimensions of satisfaction, and compared between the collaborative care and traditional physician models. RESULTS: A total of 62 patients completed the questionnaire (21 collaborative care and 41 traditional physician model). The average age of respondents was 52 years and the majority were female. The mean score for satisfaction across the six dimensions was 4.56 in the collaborative care group and 4.30 in the traditional physician group (p = 0.02). Patient satisfaction in the collaborative care group was consistently higher across all dimensions. No difference was noted between participants seen for the first time compared with those seen two or more times by the pharmacist. CONCLUSIONS: A collaborative care model can exceed the already high expectations for care of patients with inflammatory arthritis. Our findings support the role of pharmacists using a collaborative care approach to care for patients in rheumatology clinics.
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.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it