Big Data Platform for Clinical Scientific Research


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    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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WANG Chi, LI Chao, CHEN Xu, HONG Ping, ZHENG Wenli, SHEN Yao, QI Kaiyue, GUO Minyi. Big Data Platform for Clinical Scientific Research[J]. Journal of Integration Technology,2019,8(5):86-96

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  • Online: October 09,2019
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