Evaluation of an Advanced-Practice Physical Therapist in a Specialty Shoulder Clinic: Diagnostic Agreement and Effect on Wait Times
Why this work is in the frame
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Bibliographic record
Abstract
PURPOSE: To examine the role of an advanced-practice physiotherapist (APP) with respect to (1) agreement with an orthopaedic surgeon on diagnosis and management of patients with shoulder problems; (2) wait times; and (3) satisfaction with care. METHODS: This prospective study involved patients with shoulder complaints who were referred to a shoulder specialist in a tertiary care centre. Agreement was examined on seven major diagnostic categories, need for further examination and surgery, and type of surgical procedure. Wait times were compared between the APP- and surgeon-led clinics from referral date to date of initial consultation, date of final diagnostic test, and date of confirmed diagnosis and planned treatment. A modified and validated version of the Visit-Specific Satisfaction Instrument assessed satisfaction in seven domains. Kappa (κ) coefficients and bias- and prevalence-adjusted kappa (PABAK) values were calculated, and strength of agreement was categorized. Wait time and satisfaction data were examined using non-parametric statistics. RESULTS: Agreement on major diagnostic categories varied from 0.68 (good) to 0.96 (excellent). Agreement with respect to indication for surgery was κ=0.75, p<0.001; 95% CI, 0.62-0.88 (good). Wait time for APP assessment was significantly shorter than wait time for surgeon consultation at all time points (p<0.001); the surgeon's wait time was significantly reduced over 3 years. High satisfaction was reported in all components of care received from both health care providers. CONCLUSIONS: Using experienced physiotherapists in an extended role reduces wait times without compromising patient clinical management and overall satisfaction.
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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 | 0.002 | 0.001 |
| 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