Patient Healthcare Trajectory and its Impact on the Cost-Effectiveness of Fracture Liaison Services
Bibliographic record
Abstract
This study aimed to assess the cost-utility of a Fracture Liaison Service (FLS) with a systematic follow-up according to patients' follow-up compliance trajectories. The Lucky Bone™ FLS is a prospective cohort study conducted on women and men (≥40 years) with fragility fractures. Dedicated personnel of the program identified fractures, investigated, treated, and followed patients systematically over 2 years. Groups of follow-up compliance trajectories were identified, and Markov decision models were used to assess the cost-utility of each follow-up trajectory group compared to usual care. A lifetime horizon from the perspective of the healthcare payer was modeled. Costs were converted to 2018 Canadian dollars and incremental cost-utility ratios (ICURs) were measured. Costs and benefits were discounted at 1.5%. A total of 532 participants were followed in the FLS (86% women, mean age of 63 years). Three trajectories were predicted and interpreted; the high followers (HFs, 48.4%), intermediate followers (IFs, 28.1%), and low followers (LFs, 23.5%). The costs of the interventions per patient varied between $300 and $446 for 2 years, according to the follow-up trajectory. The FLS had higher investigation, treatment, and persistence rates compared to usual care. Compared to usual care, the ICURs for the HF, IF, and LF trajectory groups were $4250, $21,900, and $72,800 per quality-adjusted life year (QALY) gained, respectively ($9000 per QALY gained for the overall FLS). Sensitivity analyses showed that the HF and IF trajectory groups, as well as the entire FLS, were cost-effective in >67% of simulations with respect to usual care. In summary, these results suggest that a high-intensity FLS with a systematic 2-year follow-up can be cost-effective, especially when patients attend follow-up visits. They also highlight the importance of understanding the behaviors and factors that surround follow-up compliance over time as secondary prevention means that they are at high risk of re-fracture. © 2020 American Society for Bone and Mineral Research (ASBMR).
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How this classification was reachedexpand
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 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".