Stergachis A S
Center for Health Studies, Group Health Cooperative of Puget Sound, Seattle, WA 98121.
Drug Intell Clin Pharm. 1988 Feb;22(2):157-61. doi: 10.1177/106002808802200216.
Large automated databases are the source of information for many record linkage studies, including postmarketing drug surveillance. Despite this reliance on prerecorded data, there have been few attempts to assess data quality and validity. This article presents some of the basic data quality and validity issues in applying record linkage methods to postmarketing surveillance. Studies based on prerecorded data, as in most record linkage studies, have all the inherent problems of the data from which they are derived. Sources of threats to the validity of record linkage studies include the completeness of data, the ability to accurately identify and follow the records of individuals through time and place, and the validity of data. This article also describes techniques for evaluating data quality and validity. Postmarketing surveillance could benefit from more attention to identifying and solving the problems associated with record linkage studies.
大型自动化数据库是许多记录链接研究的信息来源,包括上市后药物监测。尽管依赖预先记录的数据,但很少有人尝试评估数据质量和有效性。本文介绍了将记录链接方法应用于上市后监测时的一些基本数据质量和有效性问题。与大多数记录链接研究一样,基于预先记录数据的研究存在其所源自数据的所有固有问题。记录链接研究有效性的威胁来源包括数据的完整性、随时间和地点准确识别和跟踪个人记录的能力以及数据的有效性。本文还描述了评估数据质量和有效性的技术。上市后监测可能会从更多关注识别和解决与记录链接研究相关的问题中受益。