Emerging from the database shadows: characterizing undocumented immigrants in a large cohort of HIV-infected persons.
Emerging from the database shadows: characterizing undocumented immigrants in a large cohort of HIV-infected persons.
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DOI：
10.1080/09540121.2017.1307921
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发表时间：
2017-12
期刊：
影响因子：
1.7
通讯作者：
Patel VV
中科院分区：
文献类型：
--
作者：
Ross J;Hanna DB;Felsen UR;Cunningham CO;Patel VV
尽管社会和结构因素可能使无证移民面临艾滋病毒结果不佳的风险，但人们对艾滋病毒如何影响无证移民知之甚少。我们的艾滋病毒感染的无证移民的临床流行病学的理解是有限的，在大数据集确定移民身份的挑战。我们开发了一种算法，使用社会安全号码（SSN）和保险数据来预测无证移民身份。我们回顾性地将该算法应用于一组在大型城市医疗保健系统接受治疗的HIV感染成年人，他们在1997年1月至2013年12月期间至少参加过一次HIV相关门诊，将患者分类为“筛选无证”或“记录”。然后，我们审查了筛选的无证患者的医疗记录，将那些记录中包含无证移民身份证据的患者归类为“无证病历”（无证病历）。双变量的关联措施被用来确定与无证移民身份相关的人口统计学和临床特征。在7，593例患者中，205例（2.7%）被算法归类为未记录。与有记录的患者相比，无记录的患者在进入护理时更年轻（平均38.5岁对40.6岁，p<0.05），女性的可能性较小（33.2%对43.1%，p<0.01），不太可能报告注射毒品是其主要艾滋病毒风险因素（3.4%对18.0%，p<0.001），并且在进入护理时具有较低的中值CD 4计数（288个细胞/mm 3对339个细胞/mm 3，p<0.01）。在病历审查后，我们重新分类104例患者（50.7%）的图表无证。人口统计学和临床特征的图表无证并没有显着不同筛选无证。我们的算法使我们能够在艾滋病毒感染人群中识别和临床表征无证移民，尽管它高估了无证患者的患病率。
Little is known about how HIV affects undocumented immigrants despite social and structural factors that may place them at risk of poor HIV outcomes. Our understanding of the clinical epidemiology of HIV-infected undocumented immigrants is limited by the challenges of determining immigration status in large data sets. We developed an algorithm to predict undocumented immigration status using social security number (SSN) and insurance data. We retrospectively applied this algorithm to a cohort of HIV-infected adults receiving care at a large urban healthcare system who attended at least one HIV-related outpatient visit between January 1997 and December 2013, classifying patients as “screened undocumented” or “documented”. We then reviewed the medical records of screened undocumented patients, classifying those whose records contained evidence of undocumented immigration status as “undocumented per medical chart” (charted undocumented). Bivariate measures of association were used to identify demographic and clinical characteristics associated with undocumented immigrant status. Of 7,593 patients, 205 (2.7%) were classified as undocumented by the algorithm. Compared to documented patients, undocumented patients were younger at entry to care (mean 38.5 years vs. 40.6 years, p<0.05), less likely to be female (33.2% vs. 43.1%, p<0.01), less likely to report injection drug use as their primary HIV risk factor (3.4% vs. 18.0%, p<0.001), and had lower median CD4 count at entry to care (288 cells/mm3 vs. 339 cells/mm3, p<0.01). After medical record review, we re-classified 104 patients (50.7%) as charted undocumented. Demographic and clinical characteristics of charted undocumented did not differ substantially from screened undocumented. Our algorithm allowed us to identify and clinically characterize undocumented immigrants within an HIV-infected population, though it overestimated the prevalence of patients who were undocumented.
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影响因子：
4.4
作者：
Maldonado, Cynthia Z.;Rodriguez, Robert M.;Lovato, Luis M.
通讯作者：
Lovato, Luis M.
影响因子：
3
作者：
Elixhauser, A;Steiner, C;Coffey, RN
通讯作者：
Coffey, RN
DOI：
10.1086/597587
发表时间：
2009-05-01
期刊：
Clinical infectious diseases : an official publication of the Infectious Diseases Society of America
影响因子：
--
作者：
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通讯作者：
Macklin R
影响因子：
1.9
作者：
Carten, Monica L.;Castillo-Mancilla, Jose R.;Johnson, Steven C.
通讯作者：
Johnson, Steven C.
影响因子：
1.9
作者：
Crawford, Tim;Caldwell, Glyn;Thornton, Alice
通讯作者：
Thornton, Alice