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使科学可计算化:开发统计学、研究设计和偏倚风险的代码系统。

Making science computable: Developing code systems for statistics, study design, and risk of bias.

机构信息

Computable Publishing LLC, Ipswich, MA, United States.

Sejong University, Seoul, South Korea.

出版信息

J Biomed Inform. 2021 Mar;115:103685. doi: 10.1016/j.jbi.2021.103685. Epub 2021 Jan 21.

Abstract

The COVID-19 crisis led a group of scientific and informatics experts to accelerate development of an infrastructure for electronic data exchange for the identification, processing, and reporting of scientific findings. The Fast Healthcare Interoperability Resources (FHIR®) standard which is overcoming the interoperability problems in health information exchange was extended to evidence-based medicine (EBM) knowledge with the EBMonFHIR project. A 13-step Code System Development Protocol was created in September 2020 to support global development of terminologies for exchange of scientific evidence. For Step 1, we assembled expert working groups with 55 people from 26 countries by October 2020. For Step 2, we identified 23 commonly used tools and systems for which the first version of code systems will be developed. For Step 3, a total of 368 non-redundant concepts were drafted to become display terms for four code systems (Statistic Type, Statistic Model, Study Design, Risk of Bias). Steps 4 through 13 will guide ongoing development and maintenance of these terminologies for scientific exchange. When completed, the code systems will facilitate identifying, processing, and reporting research results and the reliability of those results. More efficient and detailed scientific communication will reduce cost and burden and improve health outcomes, quality of life, and patient, caregiver, and healthcare professional satisfaction. We hope the achievements reached thus far will outlive COVID-19 and provide an infrastructure to make science computable for future generations. Anyone may join the effort at https://www.gps.health/covid19_knowledge_accelerator.html.

摘要

COVID-19 危机促使一群科学和信息学专家加速开发用于识别、处理和报告科学发现的电子数据交换基础设施。Fast Healthcare Interoperability Resources(FHIR®)标准通过 EBMonFHIR 项目扩展到循证医学(EBM)知识,克服了医疗信息交换中的互操作性问题。2020 年 9 月创建了一个 13 步的代码系统开发协议,以支持全球开发用于交换科学证据的术语。在第 1 步中,我们于 2020 年 10 月之前组织了来自 26 个国家的 55 名专家工作组。在第 2 步中,我们确定了 23 种常用工具和系统,将为其开发第一个版本的代码系统。在第 3 步中,共起草了 368 个非冗余概念,成为四个代码系统(统计类型、统计模型、研究设计、偏倚风险)的显示术语。步骤 4 到 13 将指导这些科学交换术语的持续开发和维护。完成后,代码系统将有助于识别、处理和报告研究结果及其结果的可靠性。更高效和详细的科学交流将降低成本和负担,改善健康结果、生活质量以及患者、护理人员和医疗保健专业人员的满意度。我们希望迄今为止取得的成就将超越 COVID-19,并为未来几代人提供一个使科学可计算的基础设施。任何人都可以在 https://www.gps.health/covid19_knowledge_accelerator.html 上加入这一努力。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5e3d/9387176/822501ff3a6f/ga1_lrg.jpg

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