在危机期间调动数据:利用多机构真实世界数据建立快速证据管道

IF 2 4区 医学 Q3 HEALTH POLICY & SERVICES
Jayson S. Marwaha , Maren Downing , John Halamka , Amy Abernethy , Joseph B. Franklin , Brian Anderson , Isaac Kohane , Kavishwar Wagholikar , John Brownstein , Melissa Haendel , Gabriel A. Brat
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引用次数: 0

摘要

COVID-19 大流行引起了人们对使用真实世界数据 (RWD) 的极大兴趣。2020 年,公共和私营部门成立了许多联盟,目标是从 RWD 中快速生成高质量的证据,以指导医疗决策、公共卫生优先事项等。我们收集了五个大型联盟在 COVID-19 大流行期间快速生成多机构证据的经验。这些经验包括五个方面:联合体的组成、管理结构和优先事项的协调、数据共享、数据分析和证据传播。这篇文章的目的是为未来的公共卫生问题提供建立大规模多机构 RWD 分析管道的指导。每个联盟的组成在很大程度上都受到了现有合作的影响。每个联盟都有一套核心的证据生成优先事项,但出现了不同的管理方法。各联盟以独特的方式克服了因不同贡献者而导致的临床数据获取受限的挑战。虽然所有联盟都采用了不同的方法来构建和分析患者队列,从集中式方法到联合式方法,但所有方法都被证明能有效生成有意义的真实世界证据。尽管各联盟采用的数据共享和分析方法略有不同,但它们都成功地快速回答了有关 COVID-19 诊断和治疗的问题。以科学严谨和透明的方式利用 RWD,可以补充更高层次的证据,并作为临床试验的重要辅助手段,快速指导政策和关键护理,尤其是在大流行应对中。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Mobilizing data during a crisis: Building rapid evidence pipelines using multi-institutional real world data

The COVID-19 pandemic generated tremendous interest in using real world data (RWD). Many consortia across the public and private sectors formed in 2020 with the goal of rapidly producing high-quality evidence from RWD to guide medical decision-making, public health priorities, and more. Experiences were gathered from five large consortia on rapid multi-institutional evidence generation during the COVID-19 pandemic. Insights have been compiled across five dimensions: consortium composition, governance structure and alignment of priorities, data sharing, data analysis, and evidence dissemination. The purpose of this piece is to offer guidance on building large-scale multi-institutional RWD analysis pipelines for future public health issues.

The composition of each consortium was largely influenced by existing collaborations. A central set of priorities for evidence generation guided each consortium, however different approaches to governance emerged. Challenges surrounding limited access to clinical data due to various contributors were overcome in unique ways. While all consortia used different methods to construct and analyze patient cohorts ranging from centralized to federated approaches, all proved effective for generating meaningful real-world evidence. Actionable recommendations for clinical practice and public health agencies were made from translating insights from consortium analyses.

Each consortium was successful in rapidly answering questions about COVID-19 diagnosis and treatment despite all taking slightly different approaches to data sharing and analysis. Leveraging RWD, leveraged in a manner that applies scientific rigor and transparency, can complement higher-level evidence and serve as an important adjunct to clinical trials to quickly guide policy and critical care, especially for a pandemic response.

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来源期刊
CiteScore
4.90
自引率
0.00%
发文量
37
期刊介绍: HealthCare: The Journal of Delivery Science and Innovation is a quarterly journal. The journal promotes cutting edge research on innovation in healthcare delivery, including improvements in systems, processes, management, and applied information technology. The journal welcomes submissions of original research articles, case studies capturing "policy to practice" or "implementation of best practices", commentaries, and critical reviews of relevant novel programs and products. The scope of the journal includes topics directly related to delivering healthcare, such as: ● Care redesign ● Applied health IT ● Payment innovation ● Managerial innovation ● Quality improvement (QI) research ● New training and education models ● Comparative delivery innovation
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