Evaluation of alternative standardized terminologies for medical conditions within a network of observational healthcare databases

被引:59
作者
Reich, Christian [1 ]
Ryan, Patrick B. [1 ,2 ]
Stang, Paul E. [1 ,2 ]
Rocca, Mitra [3 ]
机构
[1] Fdn Natl Inst Hlth, Observat Med Outcomes Partnership, Bethesda, MD 20814 USA
[2] Janssen Res & Dev LLC, Titusville, NJ 08560 USA
[3] US FDA, Off Translat Sci, CDER, Silver Spring, MD 20933 USA
基金
美国国家卫生研究院;
关键词
Terminology standards; Coding scheme; Vocabulary; Taxonomy; Mapping; ICD-9-CM; COMMON DATA MODEL; SAFETY SURVEILLANCE; LANGUAGE SYSTEM; FRAMEWORK;
D O I
10.1016/j.jbi.2012.05.002
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
Large electronic databases of health care information, such as administrative claims and electronic health records, are available and are being used in a number of public health settings, including drug safety surveillance. However, because of a lack of standardization, clinical terminologies may differ across databases. With the aid of existing resources and expert coders, we have developed mapping tables to convert ICD-9-CM diagnosis codes used in some existing databases to SNOMED-CT and MedDRA. In addition, previously developed definitions for specific health outcomes of interest were mapped to the same standardized vocabularies. We evaluated how vocabulary mapping affected (1) the retention of clinical data from two test databases, (2) the semantic space of outcome definitions, (3) the prevalence of each outcome in the test databases, and (4) the reliability of analytic methods designed to detect drug-outcome associations in the test databases. Although vocabulary mapping affected the semantic space of some outcome definitions, as well as the prevalence of some outcomes in the test databases, it had only minor effects on the analysis of drug-outcome associations. Furthermore, both SNOMED-CT and MedDRA were viable for use as standardized vocabularies in systems designed to perform active medical product surveillance using disparate sources of observational data. (c) 2012 Elsevier Inc. All rights reserved.
引用
收藏
页码:689 / 696
页数:8
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