A population-based study of ambulatory and surgical services provided by orthopaedic surgeons for musculoskeletal conditions
Bibliographic record
Abstract
BACKGROUND: The ongoing process of population aging is associated with an increase in prevalence of musculoskeletal conditions with a concomitant increase in the demand of orthopaedic services. Shortages of orthopaedic services have been documented in Canada and elsewhere. This population-based study describes the number of patients seen by orthopaedic surgeons in office and hospital settings to set the scene for the development of strategies that could maximize the availability of orthopaedic resources. METHODS: Administrative data from the Ontario Health Insurance Plan and Canadian Institute for Health Information hospital separation databases for the 2005/06 fiscal year were used to identify individuals accessing orthopaedic services in Ontario, Canada. The number of patients with encounters with orthopaedic surgeons, the number of encounters and the number of surgeries carried out by orthopaedic surgeons were estimated according to condition groups, service location, patient's age and sex. RESULTS: In 2005/06, over 520,000 Ontarians (41 per 1,000 population) had over 1.3 million encounters with orthopaedic surgeons. Of those 86% were ambulatory encounters and 14% were in hospital encounters. The majority of ambulatory encounters were for an injury or related condition (44%) followed by arthritis and related conditions (37%). Osteoarthritis accounted for 16% of all ambulatory encounters. Orthopaedic surgeons carried out over 140,000 surgeries in 2005/06: joint replacement accounted for 25% of all orthopaedic surgeries, whereas closed repair accounted for 16% and reductions accounted for 21%. Half of the orthopaedic surgeries were for arthritis and related conditions. CONCLUSION: The large volume of ambulatory care points to the significant contribution of orthopaedic surgeons to the medical management of chronic musculoskeletal conditions including arthritis and injuries. The findings highlight that surgery is only one component of the work of orthopaedic surgeons in the management of these conditions. Policy makers and orthopaedic surgeons need to be creative in developing strategies to accommodate the growing workload of orthopaedic surgeons without sacrificing quality of care of patients with musculoskeletal conditions.
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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 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".