Models of Care in Multiple Sclerosis: A Survey of Canadian Health Providers
Bibliographic record
Abstract
Objective: Little work has evaluated integrated models of care in multiple sclerosis (MS) and the composition of MS care teams across Canada is largely unknown. We aimed to gather information regarding existing models of MS care across Canada, and to assess the perceptions of health care providers (HCPs) regarding the models of care required to fully meet the needs of the person with MS. Methods: We conducted an anonymous online survey targeting Canadian HCPs working in MS Clinics, and neurologists delivering MS care whether or not they were based in an MS Clinic. We queried the types of HCPs delivering care within formal MS Clinics, wait times for HCPs, the perceived importance of different types of HCPs for good quality care, assessments conducted, and whether clinic databases were used. We summarized survey responses using descriptive statistics. Results: Of the 716 HCPs to whom the survey was distributed, 100 (13.9%) people responded. Of the 100 respondents, 85 (85%) indicated that their clinical practice included people with MS and responded to specific questions about clinical care. The most common types of providers within MS Clinics with integrated models of care were neurologists and MS nurses. Of 23 responding MS Clinics, 10 (43.5%) indicated that there were not enough neurologists, and 16 (69.6%) indicated that there were not enough non-neurologist HCPs to provide adequate care. More than 50% of clinics reported wait times exceeding 3 months for physiatrists, physiotherapists, psychiatrists, psychologists, neuropsychologists and urologists; in some clinics wait times for these providers exceeded 1 year. Multiple disciplines were identified as important or very important for delivering good quality MS care. Over 90% of respondents thought it was important for neurologists, nurse practitioners, MS nurses and psychiatrists to be co-located within MS Clinics. Conclusion: Canadian HCPs viewed the ideal MS service as being multidisciplinary in nature and ideally integrated. Efforts are needed to improve timely access to specialized MS care in Canada, and to evaluate how outcomes are influenced by access to care.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.005 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 source (direct Gemma or distilled Codex), 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".