STATISTICAL METHODS FOR MH COST-BENEFIT ANALYSIS

MH成本效益分析的统计方法

• 批准号: 3389878
• 负责人: CAROLE E SIEGEL
• 金额: $ 16.57万
• 依托单位: NATHAN S. KLINE INSTITUTE FOR PSYCH RES
• 依托单位国家: 美国
• 财政年份: 1993
• 资助国家: 美国
• 起止时间: 1993-05-01 至 1997-04-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/3389878
• 关键词: health care cost /financing; health care model; health care service evaluation; health science research; human data; mental health services; preference; statistics /biometry

In order for evaluation studies of mental health service interventions to be useful for purposes such as resource allocation, benefits, effects, or utilities need to be examined in conjunction with their associated costs. Since such studies can be very complex, their implementation expensive, and the results controversial, it is surprising that so little attention has been paid to methods for statistical analysis that enables meaningful inference. The global aim of this proposal is to develop a statistical framework for describing and comparing costs and benefits among programs. Specifically, 1. we will develop statistical models that characterize programs in terms of the joint distribution of cost and benefits; 2. we will develop statistical methods for contrasting, ranking and selecting programs in terms of their costs and benefits; and 3. we will test these newly developed approaches on several cost-benefit data sets and compare the results with those obtained by the use of present methods. One procedure to compare programs is based on multivariate "admissibility" criteria. Another is to rank order or select the best program based on a preference measure. Statistical procedures will be developed for testing admissibility, for testing equality of programs with respect to preference measures and for ranking and selection for various models of the distribution of costs and benefits.

为了评估心理健康服务干预措施 对于资源分配，收益，效果或 需要与其相关成本一起检查公用事业。 由于这样的研究可能非常复杂，因此它们的实施昂贵，并且 结果有争议，令人惊讶的是，很少关注 已付款用于统计分析的方法，以实现有意义的 推理。 该提案的全球目的是开发统计 描述和比较计划之间成本和收益的框架。 具体来说，1。我们将开发表征表征的统计模型 根据成本和收益的共同分配计划； 2。我们 将开发对比，排名和选择的统计方法 关于其成本和收益的计划；和3。我们将测试这些 在几个成本效益数据集上采用新开发的方法并进行比较 通过使用当前方法获得的结果。 一 比较程序的程序基于多元“可接受性” 标准。 另一个是基于A等级或选择最佳程序 偏好度量。 统计程序将开发用于测试 可接受性，以测试有关偏好的计划平等 措施以及各种模型的排名和选择 成本和收益的分配。