Williams Michelle, Richesson Rachel L, Bray Bruce E, Greenes Robert A, McIntosh Leslie D, Middleton Blackford, Perry Gerald, Platt Jodyn, Shaffer Christopher
Department of Learning Health Sciences University of Michigan Medical School Ann Arbor Michigan USA.
University of Utah School of Medicine Salt Lake City Utah USA.
Learn Health Syst. 2020 Dec 23;5(1):e10255. doi: 10.1002/lrh2.10255. eCollection 2021 Jan.
The volume of biomedical knowledge is growing exponentially and much of this knowledge is represented in computer executable formats, such as models, algorithms, and programmatic code. There is a growing need to apply this knowledge to improve health in Learning Health Systems, health delivery organizations, and other settings. However, most organizations do not yet have the infrastructure required to consume and apply computable knowledge, and national policies and standards adoption are not sufficient to ensure that it is discoverable and used safely and fairly, nor is there widespread experience in the process of knowledge implementation as clinical decision support. The Mobilizing Computable Biomedical Knowledge (MCBK) community was formed in 2016 to address these needs. This report summarizes the main outputs of the third annual MCBK public meeting, which was held virtually from June 30 to July 1, 2020 and brought together over 200 participants from various domains to frame and address important dimensions for mobilizing CBK.
生物医学知识的体量正呈指数级增长，且其中许多知识都以计算机可执行格式呈现，如模型、算法和程序代码。在学习型健康系统、医疗服务组织及其他环境中，应用这些知识以改善健康状况的需求日益增长。然而，大多数组织尚不具备使用和应用可计算知识所需的基础设施，国家政策和标准的采用也不足以确保其可被发现并安全、公平地使用，在将知识作为临床决策支持进行实施的过程中，也缺乏广泛的经验。“调动可计算生物医学知识”（MCBK）社群于2016年成立，以满足这些需求。本报告总结了第三届MCBK年度公开会议的主要成果，该会议于2020年6月30日至7月1日以线上形式举行，汇聚了来自不同领域的200多名参与者，以规划和探讨调动可计算生物医学知识的重要方面。
