Development and validation of a computer-based algorithm to identify foreign-born patients with HIV infection from the electronic medical record

Levison, Julie H.; Triant, Virginia A.; Losina, Elena; Keefe, Kimberly W.; Freedberg, Kenneth A.; Regan, Susan

doi:10.4338/aci-2014-02-ra-0013

Cited by 11 publications

(4 citation statements)

References 16 publications

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“…Foreign-born patients are also difficult to identify and study on a population level, as country of origin is typically excluded from the EMR. We employed a validated algorithm to identify, characterize, and follow HIV-infected foreign-born patients in a large urban healthcare system (Levison et al, 2014). Compared with US-born, newly-infected foreign-born individuals presented to HIV primary care with lower CD4 counts, levels comparable to many resource-limited settings (Braitstein et al, 2006; Nash et al, 2008).…”

Section: Discussionmentioning

confidence: 99%

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Foreign-born status as a predictor of engagement in HIV care in a large US metropolitan health system

et al. 2016

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We sought to determine linkage to and retention in HIV care after HIV diagnosis in foreign-born compared with US-born individuals. From a clinical data registry, we identified 619 patients aged ≥18 years with a new HIV diagnosis between 2000 and 2012. Timely linkage to care was the proportion of patients with an ICD-9 code for HIV infection (V08 or 042) associated with a primary care or infectious disease physician within 90 days of the index positive HIV test. Retention in HIV care was the presence of an HIV primary care visit in each 6-month period of the 24-month measurement period from the index HIV test. We used Cox regression analysis with adjustment for hypothesized confounders (age, gender, race/ethnicity, substance abuse, year and location of HIV diagnosis). Foreign-born comprised 36% (225/619) of the cohort. Index CD4 count was 225/μl (IQR 67–439/μl) in foreign-born compared with 328/μl (IQR 121–527/μl) in US-born (p<0.001). The proportion linked to care was 87% (196/225) in foreign-born compared with 77% (302/394) in US-born (p=0.002). The adjusted hazard ratio of linkage to HIV care in foreign-born compared with US-born was 1.28 (95% confidence interval [CI], 1.05–1.56). Once linked, there was no difference in retention in care or virologic suppression at 24 months. These results show that despite late presentation to HIV care, foreign-born persons can subsequently engage in HIV care as well as US-born. Interventions that promote HIV screening in foreign-born persons are a promising way to improve outcomes in these populations.

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Section: Discussionmentioning

confidence: 99%

“…Place of birth was determined using a previously validated algorithm that combines a coded field for primary language spoken with computer-aided review of free text notes (Levison et al, 2014). We considered a patient US-born if place of birth was documented as US mainland, Puerto Rico, or other US territory (U. S. Census Bureau).…”

Section: Methodsmentioning

confidence: 99%

Foreign-born status as a predictor of engagement in HIV care in a large US metropolitan health system

et al. 2016

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“…We included all patients 18 years of age and older who had an IGRA collected in an outpatient setting between January 2010 and July 2017 and had a non-English primary language, as a surrogate for non-US-born status, which has been validated and shown to be a specific marker [ 13 ]. We excluded individuals whose primary languages represented countries with low TB incidence (<10 per 100 000 person-years), determined by World Health Organization TB Country Profiles [ 14 ].…”

Section: Methodsmentioning

confidence: 99%

Risk Factors for Indeterminate Outcome on Interferon Gamma Release Assay in Non-US-Born Persons Screened for Latent Tuberculosis Infection

Sharninghausen

Shapiro

Koelle

et al. 2018

Open Forum Infectious Diseases

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BackgroundNon-US-born individuals account for the majority of active tuberculosis (TB) in the United States. Interferon gamma release assay (IGRA) is the preferred diagnostic test for latent TB but can produce an indeterminate result. We investigated the prevalence and predictors of an indeterminate IGRA (IND-IGRA) in a diverse cohort of non-US-born individuals and evaluated outcomes after IND-IGRA.MethodsWe identified patient age ≥18 years who had an outpatient IGRA between 2010 and 2017 in our health system and whose primary language was not English. We used univariate and multivariable logistic regression to examine the association of IND-IGRA with a variety of clinical factors.ResultsOf 3128 outpatients with ≥1 IGRA done, 33% were Asian, 30% Hispanic, and 29% black; 44% were men, and the median age was 50 years. An initial IND-IGRA occurred in 118 (3.8%; 95% confidence interval [CI], 3.1%–4.5%); notably, Asian race (55%) and rheumatologic conditions (25%) were prevalent in this group. In multivariable analysis, Asian race was independently associated with IND-IGRA (adjusted odds ratio [aOR], 2.9; 95% CI, 1.9–4.3), in addition to the presence of anemia and hypoalbuminemia (aOR for interaction, 4.3; 95% CI, 1.3–14.3). Only 55% of patients with an initial IND-IGRA underwent repeat testing; of those who did, 66% had a determinate result.ConclusionsAsian race and anemia/hypoalbuminemia were independent risk factors for an indeterminate IGRA outcome in foreign-born patients screened in the United States. Our study underscores the importance of following through on indeterminate results in these key subgroups.

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“…Recent studies have sought to improve the performance of ICD code-based algorithms on EHR data by developing phenotyping algorithms that mirror the testing and diagnostic guidelines from the US Centers for Disease Control and Prevention (CDC) [12]. These algorithms use data such as laboratory test results and prescriptions for HIV-specific medications, as well as ICD codes, to identify people with HIV from EHR records [13][14][15][16][17][18], and demonstrate good sensitivity and specificity. However, they were developed using data from single health care systems or the Department of Veterans' Affairs, which could limit their generalizability.…”

Section: Introductionmentioning

confidence: 99%

A Phenotyping Algorithm to Identify People With HIV in Electronic Health Record Data (HIV-Phen): Development and Evaluation Study

May¹,

Giordano²,

Gottlieb³

2021

JMIR Form Res

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Background Identification of people with HIV from electronic health record (EHR) data is an essential first step in the study of important HIV outcomes, such as risk assessment. This task has been historically performed via manual chart review, but the increased availability of large clinical data sets has led to the emergence of phenotyping algorithms to automate this process. Existing algorithms for identifying people with HIV rely on a combination of International Classification of Disease codes and laboratory tests or closely mimic clinical testing guidelines for HIV diagnosis. However, we found that existing algorithms in the literature missed a significant proportion of people with HIV in our data. Objective The aim of this study is to develop and evaluate HIV-Phen, an updated criteria-based HIV phenotyping algorithm. Methods We developed an algorithm using HIV-specific laboratory tests and medications and compared it with previously published algorithms in national and local data sets to identify cohorts of people with HIV. Cohort demographics were compared with those reported in the national and local surveillance data. Chart reviews were performed on a subsample of patients from the local database to calculate the sensitivity, specificity, positive predictive value, negative predictive value, and accuracy of the algorithm. Results Our new algorithm identified substantially more people with HIV in both national (up to an 85.75% increase) and local (up to an 83.20% increase) EHR databases than the previously published algorithms. The demographic characteristics of people with HIV identified using our algorithm were similar to those reported in national and local HIV surveillance data. Our algorithm demonstrated improved sensitivity over existing algorithms (98% vs 56%-92%) while maintaining a similar overall accuracy (96% vs 80%-96%). Conclusions We developed and evaluated an updated criteria-based phenotyping algorithm for identifying people with HIV in EHR data that demonstrates improved sensitivity over existing algorithms.

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Development and validation of a computer-based algorithm to identify foreign-born patients with HIV infection from the electronic medical record

Abstract: A computer-based algorithm classified foreign-born status in a large HIV-infected cohort efficiently and accurately. This approach can be used to improve EMR-based outcomes research.

Cited by 11 publications

References 16 publications

Foreign-born status as a predictor of engagement in HIV care in a large US metropolitan health system

Foreign-born status as a predictor of engagement in HIV care in a large US metropolitan health system

Risk Factors for Indeterminate Outcome on Interferon Gamma Release Assay in Non-US-Born Persons Screened for Latent Tuberculosis Infection

A Phenotyping Algorithm to Identify People With HIV in Electronic Health Record Data (HIV-Phen): Development and Evaluation Study

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