Invited Commentary: Observational Research in the Age of the Electronic Health Record

被引：15

作者：

Chute, Christopher G. ^{[1
]}

机构：

[1] Mayo Clin, Coll Med, Dept Hlth Sci Res, Rochester, MN 55905 USA

来源：

AMERICAN JOURNAL OF EPIDEMIOLOGY | 2014年 / 179卷 / 06期

关键词：

clinical case retrieval; electronic medical records; high-throughput clinical phenotyping; natural language processing; MEDICAL-RECORD; EMERGE NETWORK; ACCURACY;

D O I：

10.1093/aje/kwt443

中图分类号：

R1 [预防医学、卫生学];

学科分类号：

1004 ; 120402 ;

摘要：

Historically, clinical epidemiologic research has been constrained by the costs and time associated with manually identifying cases and abstracting clinical data. In this issue, Carrell et al. (Am J Epidemiol. 2014;179(6);749-758) report on their impressive success using natural language processing techniques to correctly identify cases of cancer recurrence among women with previous breast cancer. They report a 10-fold decrease in the need for chart abstraction, though with an 8% loss in case detection. This commentary outlines some recent history associated with the development of "high-throughput clinical phenotyping" of electronic health records and speculates on the impact such computational capabilities may have for observational research and patient consent.

引用

页码：759 / 761

页数：3

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