From the Slone Epidemiology Center, Boston University, Boston, MA.
Department of Epidemiology, Emory University, Atlanta, GA.
Epidemiology. 2021 May 1;32(3):434-438. doi: 10.1097/EDE.0000000000001327.
LexisNexis Accurint is a database of ~84 billion public records that includes an individual's location of residence. Its ability to track residences longitudinally has not been validated. This study used the Georgia Cancer Registry's (GCR's) Cancer Recurrence and Information Surveillance Program (CRISP) to validate the U.S. state of residence and to examine characteristics of patients not included or who had an inaccurate entry in LexisNexis.
The GCR is routinely linked to the National Death Index (NDI), providing information regarding the state of residence in which the patient died. We compared the state of residence reported in LexisNexis with the NDI gold standard state of residence at death. Multivariate logistic regression analyses estimated associations between demographic information and: (1) having a mismatch between LexisNexis and NDI and (2) being missed in LexisNexis.
Of the 69,494 patients in the CRISP cohort, 65,890 (95%) were found in LexisNexis and 9,597 (14%) had died. Among a subset of patients who were deceased, the sensitivity of LexisNexis for identifying persons who left Georgia was 42% and the specificity was 89%. Minority groups were more likely to be missed in the LexisNexis database as well as to have discordance between LexisNexis and NDI state of residence at death.
LexisNexis Accurint failed to identify the emigration of more than half of deceased CRISP patients who had left Georgia but correctly identified most who had remained. The validity of the state of residence is important for studies using LexisNexis as a tool for follow-up.
LexisNexis Accurint 是一个包含约 840 亿公共记录的数据库,其中包括个人的居住地点。其对居住地进行纵向追踪的能力尚未得到验证。本研究使用佐治亚州癌症登记处(GCR)的癌症复发和信息监测计划(CRISP)来验证美国的居住州,并检查未包含在 LexisNexis 中的患者或其条目不准确的患者的特征。
GCR 通常与国家死亡索引(NDI)相链接,提供有关患者死亡时居住地的信息。我们将 LexisNexis 报告的居住州与 NDI 死亡时的黄金标准居住州进行了比较。多变量逻辑回归分析估计了人口统计学信息与以下方面之间的关联:(1)LexisNexis 与 NDI 之间的不匹配和(2)在 LexisNexis 中遗漏。
在 CRISP 队列的 69494 名患者中,有 65890 名(95%)在 LexisNexis 中找到,有 9597 名(14%)死亡。在一组死亡患者中,LexisNexis 识别离开佐治亚州的人的敏感性为 42%,特异性为 89%。少数群体更有可能在 LexisNexis 数据库中被遗漏,并且 LexisNexis 与 NDI 死亡时的居住地之间也存在不一致。
LexisNexis Accurint 未能识别离开佐治亚州的超过一半的 CRISP 死亡患者的移民情况,但正确识别了大多数仍留在该州的患者。使用 LexisNexis 作为随访工具时,居住地的准确性很重要。