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引用次数: 0
摘要
本特刊旨在传播高价值医疗保健合作组织 (HVHC) 的经验。HVHC 是一个由成员自愿组成的组织,其基础是医疗服务系统领导者之间相互信任的工作关系。HVHC 的使命是成为一个以医疗服务提供者为基础的学习型医疗系统,致力于通过数据、证据和协作提高医疗保健价值。我们首先介绍了 HVHC 的组织和结构,以便为一系列介绍该学习型医疗系统工作的论文奠定基础。HVHC 获得了约翰和劳拉-阿诺德基金会(John and Laura Arnold Foundation)的资助,以开发一个可推广和实施的模式。3 小时败血症捆绑疗法的实施被用作一种原型、复杂的干预措施,并在 16 个成员站点进行了深入的混合方法评估。本期的前四篇文章详细描述了所遇到的各种数据和方法挑战,以及克服这些挑战的策略(见 Knowlton 等人、von Recklinghausen 等人、Welch 等人和 Taenzer 等人)。接下来,我们将说明数据信托如何支持与成员组织相关的新问题。Albritton 等人的论文探讨了观察住院对再入院率的影响。Knighton 等人的论文探讨了如何使用基于地区的健康素养测量方法来评估弱势群体的风险。最后两篇论文说明了支持高级数据科学所需的基础数据源的重要性。
A Data Driven Approach to Achieving High Value Healthcare.
The purpose of this special issue is to disseminate learning from the High Value Healthcare Collaborative (HVHC). The HVHC is a voluntary, member-led organization based on trusted, working relationships among delivery system leaders. HVHC's mission is to be a provider-based learning health system committed to improving healthcare value through data, evidence, and collaboration. We begin by describing the organization and structure of HVHC in order to lay the context for a series of papers that feature work from this learning health system. HVHC was awarded a grant from the John and Laura Arnold Foundation to develop a generalizable model for dissemination and implementation. Implementation of the 3-hour sepsis bundle was used as a prototypic, complex intervention with an in-depth mixed methods evaluation across 16 member sites. The first four articles in this issue describe, in detail, various data and methodological challenges encountered together with strategies for overcoming these (see Knowlton et al., von Recklinghausen et al., Welch et al., and Taenzer et al.). Next, we illustrate how the Data Trust can support emerging questions relevant to member organizations. The paper by Albritton et al., explores the impact of observation stays on readmission rates. Knighton et al., explore the use of an area-based measure for health literacy to assess risk in disadvantaged populations. Two final papers illustrate the importance of fundamental data sources needed to support advanced data science.