An advanced clinician practitioner in arthritis care can improve access to rheumatology care in community-based practice
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
OBJECTIVE: To facilitate access and improve wait times to a rheumatologist's consultation, this study aimed to 1) determine the ability of an advanced clinician practitioner in arthritis care (ACPAC)-trained extended role practitioner (ERP) to triage patients with suspected inflammatory arthritis (IA) for priority assessment by a rheumatologist and 2) determine the impact of an ERP on access-to-care as measured by time-to-rheumatologist-assessment and time-to-treatment-decision. MATERIALS AND METHODS: A community-based ACPAC-trained ERP triaged new referrals for suspected IA. Patients with suspected IA were booked to see the rheumatologist on a priority basis. Diagnostic accuracy of the ERP to correctly identify priority patients; the level of agreement between ERP and rheumatologist (Kappa coefficient and percent agreement); and the time-to-treatment-decision for confirmed cases of IA were investigated. Retrospective chart review then compared time-to-rheumatologist-assessment and time-to-treatment-decision in the solo-rheumatologist versus the ERP-triage model. RESULTS: One hundred twenty-one patients were triaged. The ERP designated 54 patients for priority assessment. The rheumatologist confirmed IA in 49/54 (90.7% positive predictive value [PPV]). Of the 121 patients, 67 patients were designated as nonpriority by the ERP, and none were determined to have IA by the rheumatologist (100% negative predictive value [NPV]). Excellent agreement was found between the ERP and the rheumatologist (Kappa coefficient 0.92, 95% CI: 0.84-0.99). In the ERP-triage model, time-from-referral-to-treatment-decision for patients with IA was 73.7 days (SD 40.4, range 12-183) compared with 124.6 days (SD 61.7, range 26-359) in the solo-rheumatologist model (40% reduction in time-to-treatment-decision). CONCLUSION: A well-trained and experienced ERP can shorten the time-to-Rheumatologist-assessment and time-to-treatment-decision for patients with suspected IA.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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 it