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The population cost-effectiveness of delivering universal and indicated school-based interventions to prevent the onset of major depression among youth in Australia

机译:提供普遍性的人口成本效益,并指出基于学校的干预措施,以防止澳大利亚青年中的重大抑郁症发作

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摘要

Copyright © Cambridge University Press 2016. Aims. School-based psychological interventions encompass: universal interventions targeting youth in the general population; and indicated interventions targeting youth with subthreshold depression. This study aimed to: (1) examine the population cost-effectiveness of delivering universal and indicated prevention interventions to youth in the population aged 11-17 years via primary and secondary schools in Australia; and (2) compare the comparative cost-effectiveness of delivering these interventions using face-to-face and internet-based delivery mechanisms. Methods. We reviewed literature on the prevention of depression to identify all interventions targeting youth that would be suitable for implementation in Australia and had evidence of efficacy to support analysis. From this, we found evidence of effectiveness for the following intervention types: universal prevention involving group-based psychological interventions delivered to all participating school students; and indicated prevention involving group-based psychological interventions delivered to students with subthreshold depression. We constructed a Markov model to assess the cost-effectiveness of delivering universal and indicated interventions in the population relative to a 'no intervention' comparator over a 10-year time horizon. A disease model was used to simulate epidemiological transitions between three health states (i.e., healthy, diseased and dead). Intervention effect sizes were based on meta-analyses of randomised control trial data identified in the aforementioned review; while health benefits were measured as Disability-adjusted Life Years (DALYs) averted attributable to reductions in depression incidence. Net costs of delivering interventions were calculated using relevant Australian data. Uncertainty and sensitivity analyses were conducted to test model assumptions. Incremental cost-effectiveness ratios (ICERs) were measured in 2013 Australian dollars per DALY averted; with costs and benefits discounted at 3%. Results. Universal and indicated psychological interventions delivered through face-to-face modalities had ICERs below a threshold of 50 000 per DALY averted. That is, 7350 per DALY averted (95% uncertainty interval (UI): dominates - 23 070) for universal prevention, and 19 550 per DALY averted (95% UI: 3081-56 713) for indicated prevention. Baseline ICERs were generally robust to changes in model assumptions. We conducted a sensitivity analysis which found that internet-delivered prevention interventions were highly cost-effective when assuming intervention effect sizes of 100 and 50% relative to effect sizes observed for face-to-face delivered interventions. These results should, however, be interpreted with caution due to the paucity of data. Conclusions. School-based psychological interventions appear to be cost-effective. However, realising efficiency gains in the population is ultimately dependent on ensuring successful system-level implementation.
机译:版权所有©Cambridge University Press 2016。AIMS。基于学校的心理干预包括:普遍干预措施在一般人群中瞄准青年;并指出了针对青少年的干预措施与亚阈值抑郁症。本研究旨在:(1)审查通过澳大利亚小学和中学在11-17岁的人口中提供普遍和指出的青年的人口成本效益; (2)比较使用面对面和基于互联网的送货机制来提供这些干预措施的比较成本效益。方法。我们审查了预防抑郁症的文献,以确定针对青年的所有干预措施,这些干预措施将适合在澳大利亚实施,并有疗效来支持支持分析。根据这一目标,我们发现了以下干预类型的有效性的证据:普遍预防涉及到所有参与学校的小组的心理干预措施;并指出预防涉及基于小组的心理干预,向划分抑郁症的学生提供。我们构建了一个马尔可夫模型,以评估相对于10年期间的“无干预”比较者在人口中提供普遍和指出的干预措施的成本效益。疾病模型用于模拟三种健康状态(即健康,患病和死亡)之间的流行病学转变。干预效应大小是基于在上述审查中确定的随机控制试验数据的Meta分析;虽然健康益处被测量为残疾调整的终身年(DALYS)避免归因于减少抑郁发病率。使用澳大利亚数据计算提供干预措施的净成本。进行了不确定性和敏感性分析以测试模型假设。增量成本效益比率(ICERS)于2013年澳大利亚澳大利亚避免估算;成本和福利折扣为3%。结果。通过面对面方式交付的普遍性和表明心理干预率为每次达利50 000的阈值低于每达利的捷者。也就是说,每Daly避免7350(95%的不确定性间隔(UI):占主导地位 - 23 070),用于普遍预防,每DALY避免(95%UI:3081-56 713)的19550年,用于预防。基线转换器通常是对模型假设的变化的强大。我们进行了一个敏感性分析,发现当假设效果尺寸为100和50%相对于面对面的效果尺寸时,互联网交付的预防干预措施是高度成本效益。但是,这些结果应根据数据的缺乏谨慎解释。结论。基于学校的心理干预似乎具有成本效益。然而,实现人口的效率最终取决于确保成功的系统级别实施。

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