Cost-effectiveness analysis of a multifactorial fall prevention intervention in older home care clients at risk for falling
Bibliographic record
Abstract
BACKGROUND: Falls among older adults can cause serious morbidity and pose economic burdens on society. Older age is a known risk factor for falls and age has been shown to influence the effectiveness of fall prevention programs. To our knowledge, no studies have explicitly investigated whether cost-effectiveness of a multifactorial fall prevention intervention (the intervention) is influenced by age. This economic evaluation explores: 1) the cost-effectiveness of a multifactorial fall prevention intervention compared to usual care for community-dwelling adults ≥ 75 years at risk of falling in Canada; and 2) the influence of age on the cost-effectiveness of the intervention. METHODS: Net benefit regression was used to examine the cost-effectiveness of the intervention with willingness-to-pay values ranging from $0-$50,000. Effects were measured as change in the number of falls, from baseline to 6-month follow-up. Costs were measured using a societal perspective. The cost-effectiveness analysis was conducted for both the total sample and by age subgroups (75-84 and 85+ years). RESULTS: For the total sample, the intervention was not economically attractive. However, the intervention was cost-effective at higher willingness-to-pay (WTP) (≥ $25,000) for adults 75-84 years and at lower WTP (< $5,000) for adults 85+ years. CONCLUSIONS: The cost-effectiveness of the intervention depends on age and decision makers' WTP to prevent falls. Understanding the influence of age on the cost-effectiveness of an intervention may help to target resources to those who benefit most. TRIAL REGISTRATION: Retrospectively registered. Clinicaltrials.gov identifier: NCT00463658 (18 April 2007).
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 | 0.000 |
| 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, 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".