Cost-effectiveness of falls prevention strategies for older adults: protocol for a living systematic review
Bibliographic record
Abstract
INTRODUCTION: One-third of adults aged 65+ fall annually. Injuries from falls can be devastating for individuals and account for 1.5% of annual healthcare spending. With the growing ageing population, falls place increased strain on scarce health resources. Prevention strategies that target individuals at high risk for falls demonstrate the best value for money; however, limited efficiency (ie, cost-effectiveness) information for fall prevention interventions hinders the implementation of effective falls prevention programmes. Living systematic reviews provide a timely up-to-date evidence-based resource to inform clinical guidelines and health policy decisions. This protocol details the methodology for a living systematic review of the efficiency (ie, cost-effectiveness) of fall prevention interventions for older adults in three settings: community-dwelling, aged care and hospitals. METHODS AND ANALYSIS: This protocol used the reporting guidelines from the Preferred Reporting Items for Systematic Reviews and Meta-Analysis Protocol. Peer-reviewed economic evaluations of controlled clinical trials or health state models will be included. Reports will be obtained through monthly systematic searches of CENTRAL (Ovid), CINAHL (EBSCO), Embase (Ovid), MEDLINE (Ovid), SCOPUS (Elsevier) and Web of Science (Clarivate) alongside snowballing and handsearching EconLit and the Tufts Cost Effectivness Analysis Registry. Screening, data extraction, quality assessment and risk of bias will be assessed by multiple reviewers. The primary outcomes will be the incremental cost-effectiveness (ie, incremental cost per fall prevented), incremental cost-utility (ie, incremental cost per quality-adjusted life year gained) or cost-benefit ratio. Additional outcomes will include falls and cost-related measures. All economic outcomes will be reported in a common year and currency. Results will be reported as a narrative synthesis; meta-analysis will be considered based on data quality, suitability and availability. ETHICS AND DISSEMINATION: Ethical approval is not required as primary human data will not be collected. Results will be disseminated through peer-reviewed publications and a dedicated website. PROSPERO REGISTRATION NUMBER: CRD42024532485.
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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 | 0.094 | 0.146 |
| Meta-epidemiology (narrow) | 0.009 | 0.007 |
| Meta-epidemiology (broad) | 0.022 | 0.028 |
| Bibliometrics | 0.013 | 0.014 |
| Science and technology studies | 0.004 | 0.006 |
| Scholarly communication | 0.010 | 0.009 |
| Open science | 0.006 | 0.007 |
| Research integrity | 0.009 | 0.011 |
| Insufficient payload (model declined to judge) | 0.088 | 0.010 |
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".