Exploring Access to Disease-Modifying Therapies and Support Services for People Living with Multiple Sclerosis in Saskatchewan
Bibliographic record
Abstract
Background: Saskatchewan has one of the highest global MS prevalence rates, with approximately 3,700 cases per 1.174 million people. In 2017, an integrated care pathway (ICP) was introduced to improve MS care delivery, but its effectiveness remains unclear. Given the importance of disease-modifying therapies (DMTs) in reducing disability progression and improving quality of life (QoL), patient access to DMTs and supportive care within the ICP context must be explored. Study Aim: This study aimed to: (1) examine accessibility to DMTs and essential DMT support services and resources in Saskatchewan. (2) explore the barriers of people with MS (Pw-MS) are facing in accessing these services and resources. (3) understand if access time to first DMT prescription and first DMT follow-up appointment was associated with the sociodemographic variables and self-reported QoL. Methods: A web-based exploratory descriptive survey was piloted among Pw-MS diagnosed between May 1, 2017, and January 1, 2020, and registered at the MS clinic. The survey included 26 sociodemographic/MS-related items and 40 items assessing access and barriers based on Levesque’s framework. Access was measured as time-to-prescription, time-to-follow-up, and a curated access survey. Descriptive and inferential statistics explored relationships between access times, sociodemographic factors, and QoL. Results: Sixty-eight participants (44 female, 24 male), mean age 35.81 (SD 10.20) at diagnosis, met inclusion criteria. ICP targets for prescription and follow-up were met, with access aligning with affordability, appropriateness, and acceptability. Barriers were noted in availability and patient perception. A significant negative correlation (p = .001) was found between time-to-DMT prescription and QoL, suggesting timely DMT access may improve QoL. Conclusion: An ICP for MS may enhance DMT access and supportive care, with early DMT initiation potentially linked to improved QoL.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".