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pSCANNER:以患者为中心的可扩展全国有效性研究网络。

pSCANNER: patient-centered Scalable National Network for Effectiveness Research.

机构信息

Division of Biomedical Informatics, Department of Medicine and Clinical Translational Research Institute, University of California San Diego, La Jolla, California, USA Division of Health Services Research & Development, Veterans Affairs, San Diego Healthcare System, La Jolla, California, USA.

Division of Health Services Research & Development, Veterans Affairs, San Diego Healthcare System, La Jolla, California, USA Division of Internal Medicine, Department of Medicine, University of California San Diego, La Jolla, California, USA.

出版信息

J Am Med Inform Assoc. 2014 Jul-Aug;21(4):621-6. doi: 10.1136/amiajnl-2014-002751. Epub 2014 Apr 29.

Abstract

This article describes the patient-centered Scalable National Network for Effectiveness Research (pSCANNER), which is part of the recently formed PCORnet, a national network composed of learning healthcare systems and patient-powered research networks funded by the Patient Centered Outcomes Research Institute (PCORI). It is designed to be a stakeholder-governed federated network that uses a distributed architecture to integrate data from three existing networks covering over 21 million patients in all 50 states: (1) VA Informatics and Computing Infrastructure (VINCI), with data from Veteran Health Administration's 151 inpatient and 909 ambulatory care and community-based outpatient clinics; (2) the University of California Research exchange (UC-ReX) network, with data from UC Davis, Irvine, Los Angeles, San Francisco, and San Diego; and (3) SCANNER, a consortium of UCSD, Tennessee VA, and three federally qualified health systems in the Los Angeles area supplemented with claims and health information exchange data, led by the University of Southern California. Initial use cases will focus on three conditions: (1) congestive heart failure; (2) Kawasaki disease; (3) obesity. Stakeholders, such as patients, clinicians, and health service researchers, will be engaged to prioritize research questions to be answered through the network. We will use a privacy-preserving distributed computation model with synchronous and asynchronous modes. The distributed system will be based on a common data model that allows the construction and evaluation of distributed multivariate models for a variety of statistical analyses.

摘要

本文介绍了以患者为中心的可扩展国家有效性研究网络(pSCANNER),它是最近成立的 PCORnet 的一部分,PCORnet 是一个由学习型医疗保健系统和由患者驱动的研究网络组成的全国网络,由患者为中心的结果研究所(PCORI)资助。它旨在成为一个由利益相关者管理的联邦网络,使用分布式架构整合来自三个现有网络的数据,这些网络覆盖了全美 50 个州的 2100 多万患者:(1)VA 信息学和计算基础设施(VINCI),数据来自退伍军人健康管理局的 151 家住院和 909 家门诊和社区门诊;(2)加州大学研究交换(UC-ReX)网络,数据来自加州大学戴维斯分校、欧文分校、洛杉矶分校、旧金山分校和圣地亚哥分校;(3)SCANNER,由圣地亚哥加州大学、田纳西州退伍军人事务部和洛杉矶地区的三个合格的联邦卫生系统组成的联盟,辅以索赔和健康信息交换数据,由南加州大学领导。最初的用例将集中在三种情况:(1)充血性心力衰竭;(2)川崎病;(3)肥胖症。将让患者、临床医生和卫生服务研究人员等利益相关者参与进来,确定通过该网络回答的优先研究问题。我们将使用具有同步和异步模式的隐私保护分布式计算模型。分布式系统将基于一个通用数据模型,允许构建和评估各种统计分析的分布式多元模型。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e9b5/4078293/bf634efa0e1b/amiajnl-2014-002751f01.jpg

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