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Use of national standards to monitor HIV care and treatment in a high prevalence city—Washington, DC

  • Amanda D. Castel ,

    Roles Conceptualization, Funding acquisition, Methodology, Supervision, Visualization, Writing – original draft, Writing – review & editing

    acastel@gwu.edu

    Affiliation Department of Epidemiology and Biostatistics, Milken Institute School of Public Health, George Washington University, Washington, DC., United States of America

  • Arpi Terzian,

    Roles Conceptualization, Methodology, Supervision, Writing – original draft

    Affiliation Department of Epidemiology and Biostatistics, Milken Institute School of Public Health, George Washington University, Washington, DC., United States of America

  • Rachel Hart,

    Roles Data curation, Formal analysis, Validation, Writing – original draft

    Affiliation Cerner Corporation, Kansas City, Missouri, United States of America

  • Nabil Rayeed,

    Roles Data curation, Formal analysis, Visualization, Writing – original draft, Writing – review & editing

    Affiliation Cerner Corporation, Kansas City, Missouri, United States of America

  • Mariah M. Kalmin,

    Roles Conceptualization, Project administration, Writing – original draft

    Affiliation Department of Epidemiology and Biostatistics, Milken Institute School of Public Health, George Washington University, Washington, DC., United States of America

  • Heather Young,

    Roles Conceptualization, Formal analysis, Writing – original draft

    Affiliation Department of Epidemiology and Biostatistics, Milken Institute School of Public Health, George Washington University, Washington, DC., United States of America

  • Alan E. Greenberg,

    Roles Conceptualization, Funding acquisition, Project administration, Supervision, Writing – original draft

    Affiliation Department of Epidemiology and Biostatistics, Milken Institute School of Public Health, George Washington University, Washington, DC., United States of America

  • for the DC Cohort Executive Committee

    Membership of the DC Cohort Executive Committee is provided in the Acknowledgments

Abstract

We sought to benchmark the quality of HIV care being received by persons living with HIV in care in Washington, DC and identify individual-level and structural-level differences. Data from the DC Cohort, an observational HIV cohort of persons receiving outpatient care in DC, were used to estimate the Institute of Medicine (IOM) and Department of Health and Human Services (HHS) quality of care measures. Differences in care by demographics and clinic type were assessed using χ2 tests and multivariable regression models. Among 8,047 participants, by HHS standards, 69% of participants were retained in care (RIC), 95% were prescribed antiretroviral therapy (ART), and 84% were virally suppressed (VS). By IOM standards, 84% were in continuous care; and 78% and 80% underwent regular CD4 and VL monitoring, respectively. Screening for syphilis, chlamydia, and gonorrhea was 51%, 31%, and 26%, respectively. Older participants were 1.5 times more likely to be RIC compared to younger participants (OR: 1.5; 95% CI: 1.3, 1.8). Participants enrolled in community-based clinics were more likely to be RIC (OR: 1.7; 95% CI: 1.4, 2.0) versus those enrolled at hospital-based clinics. Older participants were more likely to achieve VS than younger participants (OR: 1.8; 95% CI: 1.5, 2.2) while Black participants were less likely compared to white participants (OR: 0.4; 95% CI: 0.3, 0.5). Despite high measures of quality of care, disparities remain. Continued monitoring of the quality of HIV care and treatment can inform the development of public health programs and interventions to optimize care delivery.

Introduction

The US National HIV/AIDS Strategy has established specific targets for persons living with HIV/AIDS (PLWHA) which include having 90% of people living with HIV diagnosed, 90% retained in HIV medical care, 80% achieving viral suppression, and ensuring 95% of PLWHA have stable housing [1]. In order to measure progress in achieving those targets, established HIV clinical cohorts and federally-funded HIV/AIDS programs are able to measure the quality of HIV clinical care along the HIV care continuum, a widely-adopted public health framework summarizing sequential steps from HIV diagnosis to optimal care resulting in viral suppression [24]. Clinical cohorts such as the North American AIDS Cohort Collaboration (NA-ACCORD), as well as local and national HIV surveillance registries, use a set of core indicators including those developed by the Institute of Medicine (IOM) and the Department of Health and Human Services (HHS), to track and compare the delivery of care within and across other, similar populations of PLWHA [58].

In Washington, DC- a city with a 2.5% HIV prevalence- the measurement and assessment of care delivery at a population-level is facilitated by a unique study, the DC Cohort study. The DC Cohort is a longitudinal, observational study of PLWHA receiving HIV care at 13 of the large publicly-funded, government, and academic medical center clinics in Washington, DC [9]. The DC Cohort, which provides representative data on PLWHA persons living with HIV in DC, follows participants receiving outpatient HIV/AIDS care by combining their clinical data into a centralized database. Given the study’s unique ability to aggregate data and capture care delivery at a diverse set of HIV clinics in a highly impacted area, the Cohort has been identified as a comprehensive data source to monitor HIV care in DC [10].

Consistent with the overarching goals of the DC Cohort and in support of the Affordable Care Act (ACA) that prioritizes the delivery and tracking of high-quality patient care, the objectives of this study were to: 1) benchmark the quality of HIV care being delivered at DC Cohort sites by applying HHS and IOM quality of care indicators for retention in HIV medical care, antiretroviral therapy (ART use), HIV viral load (VL) suppression and other measures; and 2) determine whether individual-level predictors such as age, sex, race/ethnicity, HIV transmission risk and structural–level predictors such as clinic type influence quality of care measures [11, 12].

Methods

Study population

The DC Cohort began enrollment in January 2011; 8,047 consenting PLWHA who receive HIV care at one or more participating clinics, independent of DC residence status, were enrolled as of September 30, 2016. Of the 13 DC Cohort sites, eight are hospital-based and five are community-based clinics. Participants’ clinical data were abstracted from patient medical records and entered into a web-based data entry system called Discovere® (Cerner Corporation, Kansas City, MO). The study protocol, consent forms, and research instruments were approved by the George Washington University Institutional Review Board (IRB), the DC Department of Health (DOH) IRB, and the IRBs of Howard University, Georgetown University, Medstar Research Institute, and the Veterans Affairs Medical Center. Reliance agreements with the GWU IRB were established with the remaining clinical sites. Details of the DC Cohort study design have been described previously [10, 12, 13].

Outcomes

Among the HHS and IOM indicators, four out of seven HHS-defined indicators and seven out of nine IOM-defined indicators were selected based on what could feasibly be measured using existing data collected in the DC Cohort. Data were collected on participants enrolled as of September 30, 2016 and reported to the DC Cohort as of December 15, 2016. Measures were computed among those who had ≥12 months of follow-up, with the exception of the HHS indicator on retention-in-care which required ≥24 months of follow-up [2, 4]. For measures requiring care visits within a specified interval of time, in addition to documented clinical encounters, CD4 or VL test results served as proxies for HIV primary care encounters, a standard practice used by HIV cohorts and surveillance programs [1417].

In 2012, HHS developed a set of common, core measures to estimate outcomes along the HIV care continuum as part of a larger initiative to strengthen the federal response to HIV/AIDS through planning and evaluating domestic HIV/AIDS programs within and across agencies. Based on an assessment of federally-funded HIV prevention, treatment, and care services, HHS identified core indicators related to continuous HIV clinical care and access to supportive services. Selected core indicators were measured, including retention in care, ART use, viral load suppression, and housing status (Table 1) [2]. Similarly, the IOM has also developed a set of core indicators related to continuous HIV clinical care as part of an initiative to monitor the effect of both the National HIV/AIDS Policy and ACA on improving HIV care [1, 11]. Select core indicators were measured, including continuous care, regular CD4 and viral monitoring, maintenance of immune function, and screening for chlamydia, gonorrhea, and syphilis (Table 1) [4].

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Table 1. HHS and IOM quality of care indicators assessed using DC Cohort study dataa.

https://doi.org/10.1371/journal.pone.0186036.t001

Statistical analyses

Frequencies on demographic and clinical characteristics at study enrollment (‘baseline’) were computed. HIV-related clinical characteristics such as history of AIDS, baseline CD4 and VL results (defined as the closest lab result reported within six months prior and 30 days after enrollment), ART exposure status and regimen type (among those prescribed ART) were also measured. HHS and IOM indicators were computed and chi-square test statistics were used to determine differences in six selected indicators by demographic and clinical characteristics. Multivariable logistic regression models were used to estimate adjusted odds ratios (OR) and 95% confidence intervals (CI); models included age, sex at birth, race/ethnicity, HIV transmission risk group and clinic type (hospital versus community-based). Bonferroni correction was applied to account for multiple testing; p-values <0.0083 (i.e., 0.05/6) were considered as the threshold for statistical significance. All analyses were completed using SAS version 9.4 (SAS Institute, Cary, NC).

Results

Participant characteristics

Among the 8,047 participants enrolled by September 2016, 91% and 62% had at least 12 and 24 months of follow up, respectively. The proportion of participants who were non-Hispanic black was 78% and the median age was 47 years. Most were publically insured (63%); more than half were receiving HIV care at community-based clinics (53%) and 75% were DC residents (Table 2). The most common mode of HIV transmission was men who had sex with men (MSM; 39%), followed by heterosexual risk (32%).

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Table 2. Demographic and clinical characteristics at enrollment, DC Cohort Study, Washington, DC 2011–2016a,b.

https://doi.org/10.1371/journal.pone.0186036.t002

At enrollment, 52% of participants had a CD4 count above 500 cells/μl, and 42% of participants had a history of AIDS. The proportion of treatment prescribed participants was 92% at enrollment (Table 2). Seventy-three percent of participants had a VL at enrollment that was less than 200 copies/ml.

Indicator measurement

For HHS-defined indicators, 69% of participants were retained in care, 95% had been prescribed ART, and 84% were virally suppressed at the end of their first year of follow-up (Fig 1). Although at enrollment, 8% of participants were homeless or temporarily housed, during the follow up period, 11% of participants were unstably housed. For IOM-defined indicators, 84% were in continuous care. The proportion of participants who received regular CD4 and VL monitoring was 78% and 80%, respectively. Among those in continuous care, 81% achieved and maintained immune function as measured by CD4 counts ≥ 350 cells/μl. The proportion of participants screened for syphilis, chlamydia, and gonorrhea was 51%, 31%, and 26%, respectively.

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Fig 1. Proportion of DC cohort participants meeting criteria for selected HHS and IOM indicators for quality of care, DC cohort, 2011–2016.

This figure represents individuals who were enrolled in the DC Cohort as of September 30, 2016 and met the criteria for selected Department of Health and Human Services and Institute of Medicine HIV quality of care indicators. While high proportions of participants met the HIV-related indicators (69%-95%), screening for sexually transmitted infections was relatively low (26%-51%).

https://doi.org/10.1371/journal.pone.0186036.g001

Comparison of indicators by participant demographics

Differences in crude proportions for HHS-defined indicators were observed by demographic characteristics (Table 3). The proportion of participants retained in care was significantly higher among older participants (≥47 versus <47), injection drug users and those with ‘other’ risks for HIV and those who enrolled at community-based DC Cohort sites (versus hospital-based sites). After adjustment for sex, race/ethnicity, HIV risk group and clinic type, older participants were 1.5 times more likely to be retained in care compared to younger participants (OR: 1.5; 95% CI: 1.3, 1.8); those with ‘other’ HIV risk compared to MSM (OR: 2.8, 95%CI 1.8, 4.3); and those enrolled in community-based clinics were also more likely to be retained (OR: 1.7; 95% CI: 1.4, 2.0). The proportion of participants prescribed ARVs was significantly higher among older participants and males (p-value<0.0083 for both); no differences were observed by race, risk, or clinic type. After adjustment, older participants were more likely to be prescribed ARVs in multivariable analyses (OR: 1.5; 95% CI: 1.1, 2.1). The proportion of participants who were virally suppressed was significantly higher among older participants, males, whites, and MSM. After adjustment, older participants were nearly two times more likely to achieve viral suppression than their younger counterparts (OR: 1.8; 95% CI: 1.5, 2.2). In contrast, non-Hispanic blacks were 0.4 times less likely to achieve viral suppression compared with non-Hispanic whites (OR: 0.4; 95% CI: 0.3, 0.5) and persons with ‘other’ transmission risk were 0.5 times less likely than MSM (0R: 0.5; 95% CI: 0.3, 0.7); Table 3).

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Table 3. Factors associated with select HHS-defined care indicators, DC Cohort, 2011–2016a,b,c.

https://doi.org/10.1371/journal.pone.0186036.t003

Differences in crude proportions for IOM-defined indicators were observed by demographic characteristics (Table 4). The proportion receiving regular CD4 monitoring was higher among older participants, females, Blacks and those with ‘other’ risk. After adjustment, persons identified as ‘other/unknown’ race were less likely and persons identified as ‘other’ risk were more likely to undergo regular CD4 monitoring (OR: 0.6; 95% CI: 0.5, 0.9 and OR: 2.2; 95% CI: 1.4, 3.4, respectively). Significant differences were observed in regular VL monitoring by sex, race, HIV risk, and clinic type. After adjustment, persons identified with ‘other’ risk and those enrolled in community-based clinics were more likely to achieve VL monitoring (OR: 2.1; 95% CI: 1.4, 3.4 and OR: 1.3; 95% CI: 1.1, 1.5, respectively). Differences in crude proportions for maintenance of immune function were observed by sex, race, and HIV risk. After adjustment, persons identified as ‘other/unknown’ race were 0.5 times less likely to achieve maintenance of immune function compared to whites (OR: 0.5; 95% CI: 0.4, 0.8).

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Table 4. Factors associated with select IOM-defined care indicators, DC Cohort, 2011–2016a,b,c.

https://doi.org/10.1371/journal.pone.0186036.t004

Discussion

Using aggregate data from a clinic-attending population of PLWHA, we were able to create a comprehensive snapshot of a standard set of quality of care and HIV care continuum outcomes among an urban population of PLWHA to identify areas of success, gaps, and disparities in care outcomes. When comparing our HHS-defined retention-in-care estimate to other published estimates, we found that retention among DC Cohort participants was slightly lower than participants in NA-ACCORD (71–75%) but higher than that reported by the HIV Research Network and others (59%-65%) [4, 1421]. The DC Cohort IOM continuity of care estimate was relatively high at 84% and higher than local surveillance estimates of 69%; however, this measure only relies on 12 months of follow-up [22]. Thus the IOM continuity of care measure may be a better indicator for initial or short term engagement in care, whereas the HHS indicator (which requires 24 months of observation) may be more useful for assessing longer-term follow-up.

The HHS-defined prescribed ARV estimate of 95% was higher than both the NA-ACCORD estimate of 82% and Veterans Aging Cohort Study (VACS) estimate of 91% [4, 23]. Similarly, our HHS-defined viral suppression estimate of 84% exceeded the DC surveillance estimates (57%), the Center for Disease Control’s National HIV Surveillance System estimate (48%), NA-ACCORD estimates (54–78%) and other large cohort estimates (66–76%) [5, 6, 16, 19, 2426]. Further analysis to examine the role of specific ART regimens and viral suppression may be warranted to better characterize effective regimens among this population. With respect to routine immunologic and virologic monitoring, our estimates for regular CD4 and VL monitoring of 78% and 80%, respectively, were similar to the VACS estimate of 80% [23, 24]. These relatively high estimates indicate that patients enrolled in the DC Cohort are well engaged in HIV care.

In contrast, our estimates for routine screening for STIs were much lower compared to our higher rates of care continuity, ARV prescription, and viral suppression. The DC Cohort estimate for routine screening of gonorrhea (NG) and chlamydia (CT) were lower than combined testing estimates of NG/CT observed in other HIV clinical cohorts (26% and 31% versus 39–42% in other cohorts) [27, 28]. Similarly, the DC Cohort screening estimate for syphilis was lower than other HIV cohorts of persons in care (51% versus 65%) [28]. Given the recent increases in syphilis, gonorrhea, and chlamydia rates observed among PLWHA, particularly MSM, providers need to be reminded of the importance of secondary prevention and routine sexually transmitted disease screening among PLWHA [2731]. Further analyses by demographic and transmission risk characteristics are needed to identify sub-groups least likely to be screened.

The disparities in care outcomes observed with regard to age, race, and housing have previously been documented in this Cohort and in other HIV cohort analyses; with older persons, whites, and those stably housed doing better than comparison populations [5, 3236]. Similarly, the observation that perinatally infected participants, who comprise 65% of ‘other’ HIV risk, had a higher likelihood of being retained but lower likelihood of achieving viral suppression is consistent with previous Cohort findings and national trends [7, 32, 37]. Interestingly, we also observed differences by clinic type with participants at community-based clinics having more regular VL monitoring and better retention in care than those enrolled at hospital-based clinics. This observation differs from that of other studies that did not find meaningful differences in retention with respect to clinic type [38, 39]. Further exploration of patient characteristics by site, as well as characterization of care delivery such as the receipt of primary care and availability of ancillary services at each site, as well as the costs of providing these services, is necessary to fully understand the implications of these findings.

Measurement of these HHS and IOM quality of care estimates provides a baseline for the DC Cohort population and a representative snapshot of care delivery in the DC area. Continued monitoring of these outcomes in the future will allow us to compare groups and track changes over time. Monitoring of care patterns and clinical outcomes also allows for identification of disparities in the delivery and achievement of optimal care and opportunities to develop targeted programmatic interventions. Currently, all participating DC Cohort sites receive semi-annual benchmark reports which include aggregate site-specific data compared to overall Cohort data as well as lists of out-of-care patients, and patients with detectable viral loads who may need clinical intervention [10]. While this type of feedback is useful, we are currently developing more real-time clinical dashboards with select key indicators that providers can access and review, to allow for better monitoring, screening, and more timely intervention [40]. Moving forward, by collaborating with the DC DOH and the DC Cohort clinic sites, interventions may include strengthening patient navigation programs to flag patients in need of screening, who are at risk of falling out of care, or require other targeted intervention [41].

Our analysis has several limitations worth noting. Our results are only applicable to those PLWHA who were already linked to care and consented to be in the DC Cohort, thus we are unable to characterize the first few steps (i.e., HIV testing, linkage to care) of the care continuum. Additionally, our cohort generally represents those in established care; DC Cohort participants included in this analysis tended to have relatively high CD4 counts at enrollment (52%) and almost 60% had never had an AIDS diagnosis. Therefore, this limits our ability to estimate differences among those who may not be engaged in care and our findings may not be generalizable to other populations of PLWHA. Moreover, the quality of data depends on how well data are manually and electronically abstracted through disparate medical record systems; however, as part of routine DC Cohort data processes, clinical validations and data queries and audits are conducted regularly.

Despite these limitations, our initial assessments of the quality of care being provided in a large urban area with a high HIV prevalence provide evidence that care delivery among PLWHA at these participating clinics may be approaching national targets but that disparities remain at both the individual and clinic level [18]. By using these indicators as baseline measures of quality of care, we were able to identify gaps in care and, through our unique partnership with the DC DOH and the major HIV providers in the city, we intend to use this evidence-base to develop strategic and practical public health programs and interventions to optimize care delivery in Washington, DC.

Acknowledgments

The authors would like to acknowledge the members of the DC Cohort Executive Committee: Members: DC Cohort Data in this analysis were collected by the DC Cohort investigators and research staff located at: Cerner Corporation (Jeffrey Binkley, Harlen Hays, Thilakavathy Subramanian, Robert Taylor, Dana Franklin, Rachel Hart; Nabil Rayeed); Children’s National Medical Center Adolescent (Lawrence D’Angelo) and Pediatric (Natella Rakhmanina) clinics; Family and Medical Counseling Service (Angela Wood); Georgetown University (Princy Kumar); George Washington Medical Faculty Associates (David Parenti); George Washington University Department of Epidemiology and Biostatistics (James Peterson, Naji Younes, Lindsey Powers Happ, Maria Jaurretche); Howard University (Saumil Doshi); La Clinica Del Pueblo (Ricardo Fernandez); MetroHealth (Annick Hebou); National Institutes of Health (Carl Dieffenbach, Henry Masur); Unity Health Care (Gebeyehu Teferi); Veterans Affairs Medical Center (Debra Benator); Washington Hospital Center (Maria Elena Ruiz); Whitman-Walker Health (David Hardy, Deborah Goldstein). We would also like to acknowledge the Research Assistants at all of the participating sites, the DC Cohort Community Advisory Board, and staff of the DC Department of Health HIV/AIDS, Hepatitis, STD, TB Administration Strategic Information Division.

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