A systematic review of health economic models of opioid agonist therapies in maintenance treatment of non-prescription opioid dependence.
A systematic review of health economic models of opioid agonist therapies in maintenance treatment of non-prescription opioid dependence.
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DOI：
10.1186/s13722-017-0071-3
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发表时间：
2017-02-24
影响因子：
3.7
通讯作者：
Dunlop WC
中科院分区：
文献类型：
--
作者：
Chetty M;Kenworthy JJ;Langham S;Walker A;Dunlop WC
类阿片依赖是一种慢性疾病，造成巨大的健康、经济和社会代价。该研究的目的是对已发表的类阿片激动剂治疗非处方类阿片依赖的卫生经济学模型进行系统审查，审查所确定的不同建模方法，并为未来的建模研究提供信息。 2015年3月，在8个电子数据库中进行了文献检索，并通过手动检索参考文献列表和6个国家卫生技术评估机构网站进行了检索。如果研究：调查了依赖非处方阿片类药物并接受阿片类激动剂或维持治疗的人群;将任何药物维持干预与任何其他维持方案（包括安慰剂或无治疗）进行了比较;并且是任何类型的健康经济模型。共有18个独特的模型。这些研究使用了一系列建模方法，包括马尔可夫模型（n = 4）、蒙特卡洛模拟决策树（n = 3）、决策分析（n = 3）、动态传播模型（n = 3）、决策树（n = 1）、队列模拟（n = 1）、贝叶斯（n = 1）和蒙特卡洛模拟（n = 2）。时间范围从6个月到终生。最常见的评价是报告每质量调整生命年成本的成本-效用分析（n = 11），其次是成本-效果分析（n = 4），成本-影响分析/成本比较（n = 2）和成本-效益分析（n = 1）。大多数研究从医疗保健提供者的角度进行。只有少数几个模型包括一些更广泛的社会成本，如生产力损失或与毒品有关的犯罪、混乱和反社会行为的成本。任何模型都没有包括个人的成本以及对家庭和社交网络的影响。发现了数量相对较少、质量参差不齐的研究，并在所有研究中确定了与模型结构、投入和方法有关的优缺点。没有迹象表明一个单一的标准正在成为一种可取的办法。大多数研究忽略了社会成本，这是一个重要问题，因为药物滥用的影响远远超出了医疗服务。尽管如此，先前模型的要素可以共同构成阿片类激动剂治疗未来经济评价的框架，包括所有相关成本和结局。这可以更充分地支持治疗非处方类阿片依赖的决策和政策制定。本文的在线版本（doi：10.1186/s13722-017-0071-3）包含补充材料，可供授权用户使用。
Opioid dependence is a chronic condition with substantial health, economic and social costs. The study objective was to conduct a systematic review of published health-economic models of opioid agonist therapy for non-prescription opioid dependence, to review the different modelling approaches identified, and to inform future modelling studies. Literature searches were conducted in March 2015 in eight electronic databases, supplemented by hand-searching reference lists and searches on six National Health Technology Assessment Agency websites. Studies were included if they: investigated populations that were dependent on non-prescription opioids and were receiving opioid agonist or maintenance therapy; compared any pharmacological maintenance intervention with any other maintenance regimen (including placebo or no treatment); and were health-economic models of any type. A total of 18 unique models were included. These used a range of modelling approaches, including Markov models (n = 4), decision tree with Monte Carlo simulations (n = 3), decision analysis (n = 3), dynamic transmission models (n = 3), decision tree (n = 1), cohort simulation (n = 1), Bayesian (n = 1), and Monte Carlo simulations (n = 2). Time horizons ranged from 6 months to lifetime. The most common evaluation was cost-utility analysis reporting cost per quality-adjusted life-year (n = 11), followed by cost-effectiveness analysis (n = 4), budget-impact analysis/cost comparison (n = 2) and cost-benefit analysis (n = 1). Most studies took the healthcare provider’s perspective. Only a few models included some wider societal costs, such as productivity loss or costs of drug-related crime, disorder and antisocial behaviour. Costs to individuals and impacts on family and social networks were not included in any model. A relatively small number of studies of varying quality were found. Strengths and weaknesses relating to model structure, inputs and approach were identified across all the studies. There was no indication of a single standard emerging as a preferred approach. Most studies omitted societal costs, an important issue since the implications of drug abuse extend widely beyond healthcare services. Nevertheless, elements from previous models could together form a framework for future economic evaluations in opioid agonist therapy including all relevant costs and outcomes. This could more adequately support decision-making and policy development for treatment of non-prescription opioid dependence. The online version of this article (doi:10.1186/s13722-017-0071-3) contains supplementary material, which is available to authorized users.