Consolidation of Publicly Funded Outpatient Musculoskeletal Physiotherapy Services in Winnipeg, Manitoba: Effects on Accessibility and Service Delivery
Bibliographic record
Abstract
Purpose: In 2017, publicly funded outpatient musculoskeletal physiotherapy services in Winnipeg, Manitoba, were consolidated by closing seven hospital-based departments and limiting access to patients who met specific diagnostic criteria. Our purpose was to compare service delivery metrics and patient demographics before and after service consolidation. Method: We used an exploratory, retrospective cohort study design. Service delivery metrics and patient demographics were obtained from the regional database and compared using inferential statistics. Results: Initial physiotherapy assessments conducted per month decreased by 85.4% (absolute numbers decreased from 18,261 initial assessments in 23 months pre-consolidation to 6,715 in 61 months post-consolidation). Treatment duration (days from assessment to discharge) increased, whereas the number of appointments per patient and wait times decreased (all p < 0.001). The mean age of patients decreased by 5.2 years ( p < 0.001). More patients with wrist/hand conditions and fewer patients with surgical knee and hip conditions were seen post-consolidation. Patients attending at both time points generally came from the same neighborhoods, and measures of deprivation and marginalization were intermediate or higher on Canadian Index of Multiple Deprivation scales. Conclusions: Closing publicly funded outpatient physiotherapy services and changing eligibility limited access for many patients who may no longer be able to access necessary care if they cannot afford private services.
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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 | 0.002 | 0.008 |
| 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 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".