Architectural frameworks: defining the structures for implementing learning health systems.
Architectural frameworks: defining the structures for implementing learning health systems.
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DOI：
10.1186/s13012-017-0607-7
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发表时间：
2017-06-23
期刊：
影响因子：
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通讯作者：
Grudniewicz A
中科院分区：
文献类型：
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作者：
Lessard L;Michalowski W;Fung-Kee-Fung M;Jones L;Grudniewicz A
将卫生系统转变为学习型卫生系统（LHS）的愿景正在引起政府机构、卫生组织和卫生研究界越来越大的兴趣，这种系统可以快速、持续地将知识转化为更低成本的改善健康成果。虽然现有的举措表明，不同的方法可以成功地使LHS愿景成为现实，但它们的目标，重点和规模差异太大，如果不付出不必要的努力，就无法复制。事实上，缺乏有效设计和大规模实施地方卫生系统所需的结构。在本文中，我们提出了使用架构框架来开发LHS，坚持公认的愿景，同时适应其特定的组织环境。架构框架是对组织作为一个系统的高层次描述;它们在不同层次上捕获其主要组件的结构、这些组件之间的相互关系以及指导其演变的原则。由于这些框架支持LHS的分析，并允许其结果进行模拟，它们作为实施前的决策支持工具，确定潜在的障碍和系统开发的推动因素。因此，它们增加了LHS成功部署的机会。我们提出了一个架构框架LHS，结合了五个方面的目标，科学，社会，技术和道德的LHS文献中常见的。所提出的架构框架由六个决策层组成，这些决策层对这些维度进行建模。绩效层为目标建模，科学层为科学维度建模，组织层为社会维度建模，数据层和信息技术层为技术维度建模，道德和安全层为道德维度建模。我们描述了必须在每一层中做出的决策类型，并确定了支持决策的方法。在本文中，我们概述了一个高层次的建筑框架接地概念和经验的LHS文献。应用这一架构框架可以指导新的LHS的开发和实施以及现有LHS的演变，因为它允许对LHS运营基础的决策类型进行清晰和批判性的理解。需要进一步研究，以评估和完善其普遍性和方法。
The vision of transforming health systems into learning health systems (LHSs) that rapidly and continuously transform knowledge into improved health outcomes at lower cost is generating increased interest in government agencies, health organizations, and health research communities. While existing initiatives demonstrate that different approaches can succeed in making the LHS vision a reality, they are too varied in their goals, focus, and scale to be reproduced without undue effort. Indeed, the structures necessary to effectively design and implement LHSs on a larger scale are lacking. In this paper, we propose the use of architectural frameworks to develop LHSs that adhere to a recognized vision while being adapted to their specific organizational context. Architectural frameworks are high-level descriptions of an organization as a system; they capture the structure of its main components at varied levels, the interrelationships among these components, and the principles that guide their evolution. Because these frameworks support the analysis of LHSs and allow their outcomes to be simulated, they act as pre-implementation decision-support tools that identify potential barriers and enablers of system development. They thus increase the chances of successful LHS deployment. We present an architectural framework for LHSs that incorporates five dimensions—goals, scientific, social, technical, and ethical—commonly found in the LHS literature. The proposed architectural framework is comprised of six decision layers that model these dimensions. The performance layer models goals, the scientific layer models the scientific dimension, the organizational layer models the social dimension, the data layer and information technology layer model the technical dimension, and the ethics and security layer models the ethical dimension. We describe the types of decisions that must be made within each layer and identify methods to support decision-making. In this paper, we outline a high-level architectural framework grounded in conceptual and empirical LHS literature. Applying this architectural framework can guide the development and implementation of new LHSs and the evolution of existing ones, as it allows for clear and critical understanding of the types of decisions that underlie LHS operations. Further research is required to assess and refine its generalizability and methods.