Ambulatory physician care for musculoskeletal disorders in Canada.
Bibliographic record
Abstract
OBJECTIVE: To examine patterns of ambulatory physician visits for musculoskeletal disorders (MSD) in Canada. METHODS: Physician claims data from 7 provinces were analyzed for ambulatory visits made by adults age >or= 15 years to primary care physicians and specialists (all medical specialists, rheumatologists, internists, all surgical specialists, orthopedic surgeons) for MSD (arthritis and related conditions, bone disorders, back disorders, ill defined symptoms) during fiscal year 1998-99. Person-visit rates and total and mean number of visits to all physicians for MSD were calculated by condition group. The percentages of patients with MSD seeing physicians of different specialties were also calculated. Provincial data were combined to calculate national estimates. RESULTS: Over 15.5 million physician visits were made for MSD during 1998-99. About 24% of Canadians made at least one physician visit for MSD: 16% for arthritis and related conditions, 2% for bone disorders, 7% for back disorders, and 6% for ill defined symptoms. Person-visit rates for MSD varied by province, were highest among older Canadians, and were greater for women than men. Primary care physicians were commonly seen, particularly for back disorders. Consultation with surgical and medical specialists was less common and varied by province and by condition. CONCLUSION: MSD place a significant burden on Canada's ambulatory healthcare system. As the population ages, there will be an escalating demand for care. Careful planning will be required to ensure that those affected have access to the care they require. A limitation in using administrative data to examine health service utilization is that MSD diagnostic codes require validation.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".