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退伍军人健康管理局企业数据仓库的身高和体重数据:卫生服务研究的机遇与挑战

VHA Corporate Data Warehouse height and weight data: opportunities and challenges for health services research.

作者信息

Noël Polly Hitchcock, Copeland Laurel A, Perrin Ruth A, Lancaster A Elizabeth, Pugh Mary Jo, Wang Chen-Pin, Bollinger Mary J, Hazuda Helen P

机构信息

Department of Veterans Affairs (VA), South Texas Veterans Health Care System, 7400 Merton Minter Blvd (11c6), San Antonio, TX 78229-4404, USA.

出版信息

J Rehabil Res Dev. 2010;47(8):739-50. doi: 10.1682/jrrd.2009.08.0110.

Abstract

Within the Veterans Health Administration (VHA), anthropometric measurements entered into the electronic medical record are stored in local information systems, the national Corporate Data Warehouse (CDW), and in some regional data warehouses. This article describes efforts to examine the quality of weight and height data within the CDW and to compare CDW data with data from warehouses maintained by several of VHA's regional groupings of healthcare facilities (Veterans Integrated Service Networks [VISNs]). We found significantly fewer recorded heights than weights in both the CDW and VISN data sources. In spite of occasional anomalies, the concordance in the number and value of records in the CDW and the VISN warehouses was generally 97% to 99% or greater. Implausible variation in same-day and same-year heights and weights was noted, suggesting measurement or data-entry errors. Our work suggests that the CDW, over time and through validation, has become a generally reliable source of anthropometric data. Researchers should assess the reliability of data contained within any source and apply strategies to minimize the impact of data errors appropriate to their study population.

摘要

在退伍军人健康管理局(VHA)内部,录入电子病历的人体测量数据存储在本地信息系统、国家企业数据仓库(CDW)以及一些区域数据仓库中。本文介绍了为检查CDW中体重和身高数据的质量以及将CDW数据与VHA的几个医疗保健设施区域分组(退伍军人综合服务网络[VISN])维护的仓库中的数据进行比较所做的工作。我们发现,在CDW和VISN数据源中,记录的身高明显少于体重。尽管偶尔会出现异常情况,但CDW和VISN仓库中记录的数量和值的一致性通常在97%至99%或更高。注意到同一天和同一年的身高和体重存在不合理的差异,这表明存在测量或数据录入错误。我们的工作表明,随着时间的推移并通过验证,CDW已成为人体测量数据的一个普遍可靠的来源。研究人员应评估任何来源中所含数据的可靠性,并应用适当的策略来尽量减少数据错误对其研究人群的影响。

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