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Adding value to clinical data by linkage to a public death registry.

机译:通过链接向公共死亡登记处添加到临床数据的价值。

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We describe the methodology and impact of merging detailed statewide mortality data into the master patient index tables of the clinical data repository (CDR) of the University of Virginia Health System (UVAHS). We employ three broadly inclusive linkage passes (designed to result in large numbers of false positives) to match the patients in the CDR to those in the statewide files using the following criteria: a) Social Security Number; b) Patient Last Name and Birth Date; c) Patient Last Name and Patient First Name. The results from these initial matches are refined by calculation and assignment of a total score comprised of partial scores depending on the quality of matching between the various identifiers. In order to validate our scoring algorithm, we used those patients known to have died at UVAHS over the eight year period as an internal control. We conclude that we are able to update our CDR with 97% of the deaths from the state source using this scheme. We illustrate the potential of the resulting system to assist caregivers in identification of at-risk patient groups by description of those patients in the CDR who were found to have committed suicide. We suggest that our approach represents an efficient and inexpensive way to enrich hospital data with important outcomes information.
机译:我们描述了将详细的州所有死亡率数据合并到弗吉尼亚大学卫生系统(UVAHS)的临床数据储存库(CDR)的主患者指数表中的方法和影响。我们使用三次广泛包容的联系(旨在导致大量的误报),将CDR中的患者匹配到使用以下标准的国家/地区文件中的患者:a)社会安全号码; b)患者姓氏和出生日期; c)患者姓氏和患者名字。根据各种标识符与各种标识符之间的匹配质量计算,由这些初始匹配的结果通过计算和分配组成的总分数。为了验证我们的评分算法,我们使用那些已知的患者在八年期间在UVAH中死亡,作为内部控制。我们得出结论,我们能够使用此计划将我们的CDR与国家来源的97%的死亡更新。我们说明了所得系统的潜力,以帮助护理人员通过对被发现犯下自杀的CDR中的那些患者的描述来鉴定风险患者群体。我们建议我们的方法代表了以重要的结果信息丰富医院数据的高效且廉价的方式。

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