Health care utilization for musculoskeletal disorders
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
OBJECTIVE: To examine patterns of ambulatory care and hospital utilization for people with musculoskeletal disorders (MSDs), including arthritis and related conditions, bone and spinal conditions, trauma and related conditions, and unspecified MSDs. METHODS: Administrative data from the Ontario Health Insurance Plan database for ambulatory care physician visits, the National Ambulatory Care Reporting System database for day (outpatient) surgeries and emergency department visits, and the Discharge Abstract Database for hospital discharges were used to examine health care utilization for MSDs in fiscal year 2006-2007. Person visit rates (number of people with physician visits or hospital encounters per population) were calculated. RESULTS: Overall, 22.3% of Ontario's population (2.8 million persons) saw a physician for an MSD in ambulatory settings. Person visit rates were highest for arthritis and related conditions (107.7 per 1,000 population), followed by trauma and related conditions (89.6 per 1,000 population), unspecified MSDs (71.0 per 1,000 population), and bone and spinal conditions (62.4 per 1,000 population). The majority of visits were to primary care physicians, with 83.2% of those with visits for all MSDs seeing a primary care physician at least once. Overall, 33.0% of people with a physician visit for an MSD saw a specialist, with orthopedic surgeons being the most commonly consulted type of specialist. In hospital settings, person visit rates for MSDs were highest in the emergency department, followed by day surgeries and inpatient hospitalizations. CONCLUSION: The findings of our study highlight the magnitude of health care utilization for MSDs and the central role of primary care physicians in the management of these conditions.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it