Equity in the Treatment of Fragility Fractures within Secondary Fracture Prevention Programs
Bibliographic record
Abstract
Background: Fragility fractures are a major health concern associated with pain, decreased quality of life, and increased mortality. Health inequities, influenced by various social determinants of health and clinical variables, may contribute to unequal access to care and outcomes. Understanding and mitigating these inequities is imperative for enhancing fracture management effectiveness and ensuring equitable care for all fragility fracture patients. Methods: In study 1, a systematic review was conducted to evaluate the performance of secondary fracture prevention programs in comparison to pharmacological treatment targets (proportion of patients who received and initiated prescribed medication), focusing specifically on patients with an indication for medication. The review also examined treatment outcomes based on age, sex, race, education, socioeconomic status, geographic location, and chronic conditions. In study 2, we used data from the Ontario’s Fracture Screening and Prevention Program (FSPP) to investigate the association between the number of chronic conditions and the prescription and initiation of bone-active medication in high risk fragility fracture patients using logistic regression analysis. Study 3 assessed gender-based differences in the prescription and initiation of bone-active medication among high risk fracture patients screened through the FSPP. We used a propensity scoring method to create a composite gender score using the FSPP dataset. Results: The systematic review reported a pooled prescription rate of 77% and an initiation rate of 71%. Across all studies, age, sex, and socioeconomic status were equity-related variables reported in relation to treatment outcomes. Study 2 revealed that the FSPP resulted in higher odds of prescription and initiation of pharmacological treatment in patients with two chronic conditions compared to those with no chronic conditions. Potential inequities in these treatment outcomes were found with a threshold of three or more chronic conditions. Study 3 revealed an association between gender and receiving a medication prescription. It indicated that patients with higher gender scores, suggesting characteristics more aligned with females, were more likely to receive a prescription for bone-active medications. Conclusion: These findings underscore the importance of addressing health inequities to ensure that all individuals, regardless of demographic or clinical factors, have equal access to effective treatment within secondary fracture prevention programs. Targeted interventions and policy measures must be implemented to mitigate these disparities and promote health equity for all fragility fracture patients.
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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 | 0.026 | 0.082 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.003 |
| 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".