Impact of a change in physician reimbursement on bone mineral density testing in Ontario, Canada: a population-based study
Bibliographic record
Abstract
BACKGROUND: On Apr. 1, 2008, a revision was made to the fee schedule for bone mineral density testing with dual-energy x-ray absorptiometry (DXA) in the province of Ontario, Canada, reducing the frequency of repeat screening in individuals at low risk of osteoporosis. We evaluated whether the change in physician reimbursement successfully promoted appropriate bone mineral density testing, with reduced use among women at low risk and increased use among women and men at higher risk of osteoporosis-related fracture. METHODS: We analyzed data from administrative databases on physician billings, hospital discharges and emergency department visits. We included all physician claims for DXA in the province to assess patterns in bone mineral density testing from Apr. 1, 2002, to Mar. 31, 2011. People at risk of an osteoporosis-related fracture were defined as women and men aged 65 years or more and those who had a recent (< 6 mo) fracture after age 40 years. Joinpoint regression analysis was used to examine trends in DXA testing. RESULTS: Before the policy change, the overall number of DXA tests increased from 433 419 in 2002/03 to 507 658 in 2007/08; after revision of the fee schedule, the number decreased to 422 915 by 2010/11. Most of this reduction was due to a decrease in the age-standardized rate of DXA testing among women deemed to be at low risk, from 5.7 per 100 population in 2008/09 to 1.8 per 100 in 2010/11. In the high-risk group of people aged 65 or more, the age-standardized rate of testing increased after the policy change among men but decreased among women. Among those at high risk because of a recent clinical fracture, the age-standardized rate of DXA testing increased for both sexes and then decreased after the policy change. INTERPRETATION: A change in reimbursement designed to restrict access to bone mineral density testing among low-risk women was associated with an overall reduction in testing. Efforts to communicate guidelines for bone mineral density testing with greater clarity, particularly as they relate to high-risk individuals, need to be explored.
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.
How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: yes | Observational | low |
| gpt | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: yes | Observational | low |
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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedLabeled directly by 2 models reading the full record.
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".