Missing data in emergency care: a pitfall in the interpretation of analysis and research based on electronic patient records

被引:2
作者
Coats, Timothy J. [1 ]
Mirkes, Evgeny M. [1 ,2 ]
机构
[1] Univ Leicester, Leicester, England
[2] Univ Leicester, Sch Comp & Math Sci, Leicester, England
关键词
Data Interpretation; Statistical; Routinely Collected Health Data;
D O I
10.1136/emermed-2024-214097
中图分类号
R4 [临床医学];
学科分类号
1002 ; 100602 ;
摘要
Electronic patient records (EPRs) are potentially valuable sources of data for service development or research but often contain large amounts of missing data. Using complete case analysis or imputation of missing data seem like simple solutions, and are increasingly easy to perform in software packages, but can easily distort data and give misleading results if used without an understanding of missingness. So, knowing about patterns of missingness, and when to get expert data science (data engineering and analytics) help, will be a fundamental future skill for emergency physicians. This will maximise the good and minimise the harm of the easy availability of large patient datasets created by the introduction of EPRs.
引用
收藏
页码:563 / 566
页数:4
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