Description of a New Rapid-Access Clinic for Parkinson’s Disease Patients: the Navigator Model (P7.287)
Bibliographic record
Abstract
OBJECTIVE Improve accessibility and quality of care for Parkinson’s disease (PD) outpatients. BACKGROUND In Canada, the time to access a movement disorders clinic (MDC) can be up to one year for PD patients. The navigation model is a new paradigm of care based on pivot nurses acting as point of entry and main contact persons for the patient. This model, developed for oncology patients, has shown better accessibility, survival and satisfaction. To our knowledge, no such program exists for PD patients. DESIGN/METHODS A navigator based MDC has been created at the MUHC and consists of two PD-trained nurses, 5 MD neurologists, a secretary, physiotherapist, occupational and speech therapists. The nurses call and triage all referred patients within a few weeks, and at first visit, initiate information collection with a bio-psycho-social perspective prior to being seen by the neurologist. Between visits, the patients can call the pivot nurses for any inquiry. Sixty new patients with suspected PD from January 2013 to September 2014 were randomly chosen and included in this review. RESULTS Patients waited 9.6 ± 0.9 weeks between referral and triage, and 17.5 ± 9.9 weeks between referral and first visit. 40.0 [percnt] were referred to physiotherapy, 41.7[percnt] to occupational therapy and 25.0[percnt] to speech therapy. 30.0[percnt] of the patients used 2.2 ± 1.6 phone calls (or emails) for follow-ups with the nurses. The main issues reported were non-motor symptoms (28.8[percnt] of all calls) followed by PD medication side effects (22.0[percnt] of all calls). A satisfaction survey to evaluate the novel model is in process. CONCLUSIONS This review describes for the first time a navigation program for PD patients. This model helps improve accessibility to a MDC for PD-suspected patients and offers a proactive approach to provide early intervention for PD daily issues and better access to the interdisciplinary team.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".