面向医疗临床科研的大数据平台
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Big Data Platform for Clinical Scientific Research
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    摘要:

    目前我国医疗信息化建设已有一定历史,各医院积累了大量电子病历临床数据,但数据结构多样。如何利用这些数据以辅助临床诊疗、科研、节约医疗资源、提升医疗效率和医疗质量,成为各医疗科研机构普遍关注的问题。该文提出了一种面向临床科研的大数据平台,构建多源数据采集方式解决信息基础设施不一致的问题:统一化存储方式应对不同数据类型、分布式计算平台提升效率与可拓展性,并对敏感数据去隐私处理;同时,构建临床科研平台辅助临床科研人员进行科研分析。根 据架构搭建集群,在专病分析流程上将原本人工约 4 个月的工作简化到 15 秒左右;数据处理效率方面,由已有平台的 5 天导入 16 692 条数据提升到 10 分钟导入 15 217 026 条数据,速度与数量有了显著提升。该平台有助于完成临床数据采集,建立专病数据库、临床科研、辅助临床诊疗的闭环,为临床科研提供高效一体化的数据平台支持。

    Abstract:

    By far, China’s medical informatization construction has been a while. Each hospital has accumulated a large amount of electronic medical clinical data, but the data structure is highly diverse. To better assist clinical diagnosis and treatment, research, save medical resources, improve medical efficiency and medical treatment quality has become a common requirement in various medical institutions. This paper proposes a big data platform for clinical research, solving the inconsistency of multi-hospital information infrastructure by constructing multi-source data collection methods, unified data storage methods to cope with different data types, and distributed data computing platforms to improve efficiency and scalability. We construct a clinical research platform to assist clinical researchers in scientific research. According to the proposed architecture, the cluster was simplified to about 15 seconds in the special disease analysis process. The data processing efficiency was compared with the existing platform. The 5 days of time for importing of 16 692 data records is reduced to 10 minutes that we can import 15 217 026 data records, significantly improving speed and quantity. This platform helps complete clinical data collection, establish a special disease database, clinical research, and assist in the closed loop of clinical diagnosis and treatment, providing an efficient and integrated data platform support for clinical research.

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引文格式
王持,李超,陈旭,等.面向医疗临床科研的大数据平台 [J].集成技术,2019,8(5):86-96

Citing format
WANG Chi, LI Chao, CHEN Xu, et al. Big Data Platform for Clinical Scientific Research[J]. Journal of Integration Technology,2019,8(5):86-96

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  • 在线发布日期: 2019-10-09
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