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开发健康偏好研究高效设计工具:属性分类法与属性库原型

Developing Tools for the Efficient Design of Health Preference Studies: Taxonomy of Attributes and Prototype of an Attribute Library.

作者信息

Crossnohere Norah L, Golder Jonah, de Bekker-Grob Esther W, Sepulveda Juan Marcos Gonzalez, Gunasekaran Kert, Hanna Alissa, Levitan Bennett, Liden Barry, Marshall Deborah, Poulos Christine, Reed Shelby D, Janssen Ellen M

机构信息

Division of General Internal Medicine, The Ohio State University College of Medicine, Columbus, OH, USA.

Medical Device Innovation Consortium, Arlington, VA, USA.

出版信息

Patient. 2025 Jul 3. doi: 10.1007/s40271-025-00751-9.

Abstract

Preference information describes the relative desirability or acceptability of specified alternatives that differ across health states, interventions, or services. Studies that generate preference information are being designed to support patient-centered decision making across all stages of the medical product lifecycle, as well as in healthcare more generally. Ensuring high-quality preference research with the potential for impact requires transparent and thoughtful study design, a core aspect of which often includes the development of attributes. Good practices for attribute development in preference studies have started to emerge and demonstrate that developing attributes requires substantial time and effort. Resources to more easily and systematically identify potentially relevant attributes may support the accessibility, interoperability, and reusability of attributes, in turn improving the efficiency of preference study design and comparability of findings across studies. In this paper, we first describe the need for and potential benefit of tools that promote the purposeful re-use of attributes for preference studies. We next present a taxonomy for categorizing and describing attributes that could be applied to facilitate their identification. Finally, we apply this taxonomy to a prototype "attribute library," developed as a part of a Medical Device Innovation Consortium work group, to demonstrate the potential value of these resources to support the preference research community.

摘要

偏好信息描述了在健康状态、干预措施或服务方面存在差异的特定备选方案的相对可取性或可接受性。生成偏好信息的研究旨在支持医疗产品生命周期各个阶段以及更广泛医疗保健领域以患者为中心的决策。确保高质量且具有影响力的偏好研究需要透明且周全的研究设计,其中一个核心方面通常包括属性的开发。偏好研究中属性开发的良好实践已开始出现,并表明开发属性需要大量时间和精力。更轻松、系统地识别潜在相关属性的资源可能支持属性的可获取性、互操作性和可重用性,进而提高偏好研究设计的效率以及不同研究结果的可比性。在本文中,我们首先描述促进属性在偏好研究中进行有目的的重复使用的工具的必要性和潜在益处。接下来,我们提出一种分类法,用于对可应用以促进其识别的属性进行分类和描述。最后,我们将此分类法应用于作为医疗器械创新联盟工作组一部分开发的原型“属性库”,以展示这些资源对支持偏好研究群体的潜在价值。

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