Nemzoff Cassandra, Sweeney Sedona, Baltussen Rob, Vassall Anna
London School of Hygiene and Tropical Medicine, London, UK.
Center for Global Development, Washington, DC, USA.
Int J Health Policy Manag. 2025;14:8562. doi: 10.34172/ijhpm.8562. Epub 2025 Mar 30.
Cost-effectiveness (CE) is a common prioritization criterion in health benefits package (HBP) design. However, to assess CE is a time- and data-demanding process, so most HBP exercises rely wholly or partially on global evidence. Extensive investment has been made in analyses, models, and tools to support cost-effectiveness analyses (CEAs) for HBPs. However, little attention has been paid to how national HBP assessors should both understand and select CE estimates. A structured, national process to select assessment methods is essential for ensuring the accuracy, ownership, and transparency of HBP design. This can be supported by "adaptive" health technology assessment (aHTA) principles, which focus on structured methodological choices based on the time, data, and capacity available. The objective of this paper was to apply aHTA framing to CEA methods selection for HBPs, and to make recommendations on how countries may consider systematically making these choices going forward.
We first reviewed the definitions and categorization of different aHTA methods. We then conducted a scoping review of previous HBP assessments to understand how CEA methods used in HBPs fit into the aHTA framework, and a follow-up survey of authors to fill gaps. Results of the literature review and survey were interpreted and narratively synthesized.
We found that previous HBP assessments used four aHTA methods, sometimes simultaneously: expert opinion (n=3/20), review (n=12/20), model adaptation (n=6/20), and new model (n=2/20). The literature review and survey found that aHTA methods for HBPs take between 1-13 months; require different data sources depending on the method(s) used; and generally, require capacity in health economics, medicine, public health, and CE modelling. We supplement our report with a discussion of key considerations for methods selection.
Trading off time, data, and capacity needs for different CE assessment methods can help to support structured, local design of HBP assessments.
成本效益（CE）是健康福利包（HBP）设计中常用的优先排序标准。然而，评估成本效益是一个耗时且需要大量数据的过程，因此大多数HBP项目完全或部分依赖于总体证据。在支持HBP成本效益分析（CEA）的分析、模型和工具方面已投入了大量资金。然而，对于国家HBP评估人员应如何理解和选择CE估计值，却很少有人关注。选择评估方法的结构化国家流程对于确保HBP设计的准确性、自主性和透明度至关重要。这可以得到“适应性”健康技术评估（aHTA）原则的支持，该原则侧重于基于可用的时间、数据和能力进行结构化的方法选择。本文的目的是将aHTA框架应用于HBP的CEA方法选择，并就各国未来如何系统地做出这些选择提出建议。
我们首先回顾了不同aHTA方法的定义和分类。然后，我们对以前的HBP评估进行了范围审查，以了解HBP中使用的CEA方法如何适应aHTA框架，并对作者进行了后续调查以填补空白。对文献综述和调查的结果进行了解释和叙述性综合。
我们发现，以前的HBP评估使用了四种aHTA方法，有时同时使用：专家意见（n=3/20）、综述（n=12/20）、模型改编（n=6/20）和新模型（n=2/20）。文献综述和调查发现，用于HBP的aHTA方法需要1-13个月；根据所使用的方法需要不同的数据来源；一般来说，需要健康经济学、医学、公共卫生和CE建模方面的能力。我们在报告中补充了对方法选择关键考虑因素的讨论。
权衡不同CE评估方法的时间、数据和能力需求有助于支持HBP评估的结构化本地设计。
