文献类型：期刊文献

中文题名：Constructing Large Scale Cohort for Clinical Study on Heart Failure with Electronic Health Record in Regional Healthcare Platform:Challenges and Strategies in Data Reuse

英文题名：Constructing Large Scale Cohort for Clinical Study on Heart Failure with Electronic Health Record in Regional Healthcare Platform:Challenges and Strategies in Data Reuse

作者：Daowen Liu[1];Liqi Lei[1];Tong Ruan[1];Ping He[2]

机构：[1]School of Information Science and Engineering,East China University of Science and Technology,Shanghai 200237,China;[2]Shanghai Hospital Development Center,Shanghai 200041,China

年份：2019

卷号：34

期号：2

起止页码：90

中文期刊名：Chinese Medical Sciences Journal

外文期刊名：中国医学科学杂志（英文版）

收录：CSTPCD;;Scopus;CSCD:【CSCD2019_2020】；PubMed;

基金：Supported by the National Major Scientific and Technological Special Project for"Significant New Drugs Development’’(No.2018ZX09201008);Special Fund Project for Information Development from Shanghai Municipal Commission of Economy and Information(No.201701013)

语种：英文

中文关键词：electronic;health;records;clinical;terminology;knowledge;graph;clinical;special;disease;case;repository;evaluation;of;data;quality;large;scale;cohort;study

外文关键词：electronic health records;clinical terminology knowledge graph;clinical special disease case repository;evaluation of data quality;large scale cohort study

摘要：Regional healthcare platforms collect clinical data from hospitals in specific areas for the purpose of healthcare management.It is a common requirement to reuse the data for clinical research.However,we have to face challenges like the inconsistence of terminology in electronic health records (EHR) and the complexities in data quality and data formats in regional healthcare platform.In this paper,we propose methodology and process on constructing large scale cohorts which forms the basis of causality and comparative effectiveness relationship in epidemiology.We firstly constructed a Chinese terminology knowledge graph to deal with the diversity of vocabularies on regional platform.Secondly,we built special disease case repositories (i.e.,heart failure repository) that utilize the graph to search the related patients and to normalize the data.Based on the requirements of the clinical research which aimed to explore the effectiveness of taking statin on 180-days readmission in patients with heart failure,we built a large-scale retrospective cohort with 29647 cases of heart failure patients from the heart failure repository.After the propensity score matching,the study group (n=6346) and the control group (n=6346) with parallel clinical characteristics were acquired.Logistic regression analysis showed that taking statins had a negative correlation with 180-days readmission in heart failure patients.This paper presents the workflow and application example of big data mining based on regional EHR data.
Regional healthcare platforms collect clinical data from hospitals in specific areas for the purpose of healthcare management. It is a common requirement to reuse the data for clinical research. However, we have to face challenges like the inconsistence of terminology in electronic health records(EHR) and the complexities in data quality and data formats in regional healthcare platform. In this paper, we propose methodology and process on constructing large scale cohorts which forms the basis of causality and comparative effectiveness relationship in epidemiology. We firstly constructed a Chinese terminology knowledge graph to deal with the diversity of vocabularies on regional platform. Secondly, we built special disease case repositories(i.e., heart failure repository) that utilize the graph to search the related patients and to normalize the data. Based on the requirements of the clinical research which aimed to explore the effectiveness of taking statin on 180-days readmission in patients with heart failure, we built a large-scale retrospective cohort with 29647 cases of heart failure patients from the heart failure repository. After the propensity score matching, the study group(n=6346) and the control group(n=6346) with parallel clinical characteristics were acquired. Logistic regression analysis showed that taking statins had a negative correlation with 180-days readmission in heart failure patients. This paper presents the workflow and application example of big data mining based on regional EHR data.