Efficiency and equity of community-based falls prevention pathways: a model-based health economic evaluation

社区防跌倒途径的效率和公平性:基于模型的健康经济学评价

阅读:1

Abstract

BACKGROUND: Three pathways exist for community-based falls prevention: reactive (R), after a fall requiring medical attention; proactive (P), after professional referral of high-risk individuals; and self-referred (SR), voluntary intervention enrolment. The UK guidelines recommend scale-up of all three ['recommended care' (RC)], but scale-up of none ['usual care' (UC)], one (R, P, SR) or two (R+P, R+SR, P+SR) are potential options. This study aims to compare the options in terms of efficiency and equity. METHODS: Cost-utility analysis from the societal perspective over a 40-year horizon identified the optimal strategy based on efficiency alone. Probabilistic sensitivity analysis accounted for parameter uncertainty. Efficiency and equity were jointly evaluated by distributional cost-effectiveness analysis. Alternative scenarios assessed changes in frailty, cognitive impairment, intervention demand and GP access. RESULTS: Public sector cost-effectiveness threshold would need to exceed £30 000 per quality-adjusted life year (QALY) gained for RC to have the highest probability of being cost-effective. R and R+SR were cost-effective, with costs per QALY gained of £2365 (R versus UC) and £5516 (R+SR versus R). RC was cost-ineffective, incurring £34 258 per QALY gained versus R+SR. Other strategies were dominated. However, if decision-makers had the same relative health inequality aversion level as the English general public, RC was optimal in terms of efficiency and equity at threshold of £30 000 per QALY gained. Scenarios of worse geriatric health favoured RC. CONCLUSIONS: Both efficiency and relative health inequality need to be considered for the UK guideline-recommended falls prevention to be optimal versus other permutations of community-based strategies.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。