Abstract
BackgroundTriangulation of data from multiple sources such as clinical cohort and surveillance data can help improve our ability to describe care patterns, service utilization, comorbidities, and ultimately measure and monitor clinical outcomes among persons living with HIV infection.ObjectivesThe objective of this study was to determine whether linkage of clinical cohort data and routinely collected HIV surveillance data would enhance the completeness and accuracy of each database and improve the understanding of care patterns and clinical outcomes.MethodsWe linked data from the District of Columbia (DC) Cohort, a large HIV observational clinical cohort, with Washington, DC, Department of Health (DOH) surveillance data between January 2011 and June 2015. We determined percent concordance between select variables in the pre- and postlinked databases using kappa test statistics. We compared retention in care (RIC), viral suppression (VS), sexually transmitted diseases (STDs), and non-HIV comorbid conditions (eg, hypertension) and compared HIV clinic visit patterns determined using the prelinked database (DC Cohort) versus the postlinked database (DC Cohort + DOH) using chi-square testing. Additionally, we compared sociodemographic characteristics, RIC, and VS among participants receiving HIV care at ≥3 sites versus <3 sites using chi-square testing.ResultsOf the 6054 DC Cohort participants, 5521 (91.19%) were included in the postlinked database and enrolled at a single DC Cohort site. The majority of the participants was male, black, and had men who have sex with men (MSM) as their HIV risk factor. In the postlinked database, 619 STD diagnoses previously unknown to the DC Cohort were identified. Additionally, the proportion of participants with RIC was higher compared with the prelinked database (59.83%, 2678/4476 vs 64.95%, 2907/4476; P<.001) and the proportion with VS was lower (87.85%, 2277/2592 vs 85.15%, 2391/2808; P<.001). Almost a quarter of participants (23.06%, 1279/5521) were identified as receiving HIV care at ≥2 sites (postlinked database). The participants using ≥3 care sites were more likely to achieve RIC (80.7%, 234/290 vs 62.61%, 2197/3509) but less likely to achieve VS (72.3%, 154/213 vs 89.51%, 1869/2088). The participants using ≥3 care sites were more likely to have unstable housing (15.1%, 64/424 vs 8.96%, 380/4242), public insurance (86.1%, 365/424 vs 57.57%, 2442/4242), comorbid conditions (eg, hypertension) (37.7%, 160/424 vs 22.98%, 975/4242), and have acquired immunodeficiency syndrome (77.8%, 330/424 vs 61.20%, 2596/4242) (all P<.001).ConclusionsLinking surveillance and clinical data resulted in the improved completeness of each database and a larger volume of available data to evaluate HIV outcomes, allowing for refinement of HIV care continuum estimates. The postlinked database also highlighted important differences between participants who sought HIV care at multiple clinical sites. Our findings suggest that combined datasets can enhance evaluation of HIV-related outcomes across an entire metropolitan area. Future research will evaluate how to best utilize this information to improve outcomes in addition to monitoring them.
Highlights
A central feature of the updated 2020 National HIV/AIDS Strategy is to measure progress along the HIV care continuum to ensure that target goals are met for each stage
Among the 4476 participants who were actively enrolled in the study with at least 1 year of follow-up as of June 15, 2014, when measuring the care continuum using the prelinked District of Columbia (DC) Cohort database compared with the postlinked database, we found that retention in care was higher (59.83% (2678/4476) vs 64.95% (2907/4476); the proportion with viral suppression was lower (87.85% (2277/2592) vs 85.15% (2391/2808) (P
Given that a relatively high proportion of individuals obtaining care in DC have achieved an undetectable viral load (VL) [33], this likely reflects that reportable, all VL values may not be as routinely reported to the DC Department of Health (DOH) surveillance program, whereas cluster of differentiation 4 (CD4) results are included in surveillance data regardless of the numeric value [34]
Summary
A central feature of the updated 2020 National HIV/AIDS (human immunodeficiency virus/acquired immunodeficiency syndrome) Strategy is to measure progress along the HIV care continuum to ensure that target goals are met for each stage. The ability to monitor progress in meeting these goals is often hampered by varying methodologies for data collection, analyses, and variation in measurement approaches, with estimates often relying on either clinic-level or population-based data [1,2]. Both approaches have their advantages and disadvantages. Compared with surveillance-based data, clinic data is less informative for tracking patients who become incarcerated, move, or transfer care [3-5] These silent transfers of care and the limitation that clinic-attending populations may not represent the general population, present a challenge when trying to make robust estimates of HIV care [6-8]. Triangulation of data from multiple sources such as clinical cohort and surveillance data can help improve our ability to describe care patterns, service utilization, comorbidities, and measure and monitor clinical outcomes among persons living with HIV infection
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