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Multicohort Models in Cost-Effectiveness Analysis: Why Aggregating Estimates over Multiple Cohorts Can Hide Useful Information

机译:经济效益分析中的多辅ro物模型:为什么聚集多个群组的估计可以隐藏有用的信息

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摘要

BackgroundModels used in cost-effectiveness analysis (CEA) of screening programs may include 1 or many birth cohorts of patients. As many screening programs involve multiple screens over many years for each birth cohort, the actual implementation of screening often involves multiple concurrent recipient cohorts. Consequently, some advocate modeling all recipient cohorts rather than 1 birth cohort, arguing it more accurately represents actual implementation. However, reporting the cost-effectiveness estimates for multiple cohorts on aggregate rather than per cohort will fail to account for any heterogeneity in cost-effectiveness between cohorts. Such heterogeneity may be policy relevant where there is considerable variation in cost-effectiveness between cohorts, as in the case of cancer screening programs with multiple concurrent recipient birth cohorts, each at different stages of screening at any one point in time.
机译:背景用于筛查计划的成本效益分析(CEA)的模型可能包括1个或多个患者的出生队列。由于许多筛查计划涉及每个出生队列许多年来的多次筛查,因此筛查的实际实施通常涉及多个并发接收者队列。因此,一些倡导者对所有接收者队列而不是1个出生队列建模,认为它更准确地代表了实际的实现。但是,报告多个同类群组的总体成本效益估算值,而不是按每个同类群组报告,将无法说明同类之间成本效益的异质性。当队列之间的成本效益差异很大时,这种异质性可能与政策相关,例如在具有多个同时接受者出生队列的癌症筛查计划的情况下,每个队列都在任何时间点进行筛查。

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