Abstract

Background

Healthcare transition from pediatric to adult-oriented clinical settings is often viewed as a high-risk time for care disengagement. However, there is a paucity of prospective, longitudinal research documenting human immunodeficiency virus (HIV) care outcomes after healthcare transition.

Methods

We conducted a prospective, observational cohort study of healthcare transition among youth enrolled at an HIV care center in Atlanta, Georgia. Pediatric clinic patients (average age, 24 years) were enrolled up to 3 months before the expected transition and were followed up to determine linkage, retention, and viral suppression in adult care through electronic medical record abstractions at the baseline and at 6, 12, 18, and 24 months.

Results

The majority of our cohort (n = 70) was male (88.6%) and black (92.9%) and acquired HIV horizontally (80%). Most of our cohort was linked to adult care by 12 months (84%) after enrollment. Of those who linked to adult care by 12 months, retention rates were 86% (95% confidence interval, 78%–94%) at 6 months, 76% (66%–86%) at 12 months, and 66% (55%–78%) at 18 and 24 months. Once in adult care, the proportion with viral suppression was stable (73% at baseline and 74%, 77%, 67%, and 78% at 6, 12, 18, and 24 months, respectively).

Conclusions

Although most youth successfully linked to adult care, retention rates decreased over the 24-month follow-up period. Rates of viral suppression were stable for those who remained in care. Strategies to support retention in adult care will be critical to optimizing this transition for youth with HIV.

Healthcare transition for youth with human immunodeficiency virus (HIV) is a pressing public health issue with implications for ongoing plans to end the HIV epidemic in the United States [1]. Youth aged 13–24 years comprise a significant and growing proportion of people with HIV in the United States. In 2019, 21% of new HIV diagnoses in the United States were among youth in this age group [2]. In addition to youth entering HIV care after new diagnoses, those with vertically (ie, perinatally) acquired infection are nearly universally expected to survive into adolescence and adulthood with current antiretroviral therapy. Taken together, the combination of youth with horizontally and vertically acquired infection constitutes an estimated 45 900 youth with HIV in the United States [3], who are often cared for in specialized pediatric/adolescent care settings and will eventually need to transition to adult-oriented HIV care [4]. This transition is a high-risk period for disengagement, in which youth must remain engaged in care and form new therapeutic alliances without disrupting their medication adherence or appointment attendance [5–10]. Successful healthcare transition from pediatric to adult-oriented care settings is essential to maintain continuous engagement in care, to support the ability of youth to independently manage their disease, and ultimately to decrease HIV-related morbidity and mortality rates [7, 11, 12].

The existing evidence base regarding healthcare transition for youth with HIV in the United States is predominated by qualitative and/or retrospective studies, with relatively few quantitative studies documenting clinical outcomes after transition [13]. In these quantitative studies, posttransition HIV care “success” is typically measured in terms of stages of the HIV care continuum [14], including linkage to adult care, retention in adult care, and HIV viral suppression after transition [15–18]. Existing retrospective studies have reported highly variable results with respect to the impact of healthcare transition on retention in care and viral suppression. These studies also vary considerably with respect to the patient population being studied (ie, the balance of youth with horizontally vs vertically acquired HIV) and transition processes in the involved clinics. Griffith and colleagues [15] described 89% retention and 67% viral load maintenance at 1-year follow-up in a retrospective cohort of youth (57% vertically infected; 62% female) who had transitioned to adult care in Baltimore and New York City. Ryscavage and colleagues [16], also in Baltimore, reported 86% linkage, 50% retention at 1 year and stable rates of viral suppression in a cohort of 50 youth with HIV (62% horizontally infected; 64% female). Similarly, Hussen and colleagues [17] in Atlanta reported 89% retention 1 year after transition but 56% retention after a second year of follow-up. Viral load suppression did not differ between pre- and posttransition periods in this study.

A few retrospective studies obtain larger sample sizes using public health surveillance data. Xia and colleagues [18], using HIV surveillance data in New York City, retrospectively analyzed outcomes among 735 youth, all vertically infected, who had transitioned to adult care. In contrast to other studies reported here, they documented relatively high rates of retention (85.2%, 85.9%, and 85.5% at 1, 2, or 3 years after transition, respectively) and actual improvement in viral suppression after transition. Nassau and colleagues [19] similarly conducted a retrospective cohort study using surveillance data in Philadelphia; in this cohort of 232 youth with HIV (of whom 71% had acquired HIV horizontally), 59% remained retained in care 1 year after transition, and 61.2% met criteria for viral suppression.

These retrospective studies provided an important foundation in the field by providing estimates of posttransition care engagement across the care continuum. However, retrospective studies are also limited in their assessments of healthcare transition in several ways. First, retrospective analyses often focus on those who have already transitioned to adult care and are not able to assess the frequency with which patients who are eligible to transition become lost to follow-up. Second, cross-sectional design limits the ability to make inferences about the directionality of observed associations. Finally, depending on the data source, retrospective studies may have access to less contextual data (eg, patient charts, surveys or interviews) that can help shed light on mechanisms underlying observed patterns and associations. Related to this, posttransition HIV care retention is measured using a wide spectrum of sometimes nontraditional metrics (eg, having 1 CD4+ T-cell or viral load measurement within a year [18]) in these studies, depending on available data.

There is therefore a need for further prospective study of the healthcare transition process for youth with HIV, using rigorous measures of HIV care continuum outcomes. To date, there has been one larger, multicenter prospective study examining healthcare transition in the United States, conducted through the Adolescent Medicine Trials Network for HIV/AIDS Interventions [20]. These authors found that, despite being deemed eligible for transition on enrollment in the study, only 37% of youth successfully transitioned to adult care within a 9-month follow-up period. Of note, that study focused on linkage to care as the transition end point (eg, did not report posttransition retention in care or viral suppression) and was limited by a short follow-up period. Moreover, it did not elicit reasons for nonlinkage and was thus unable to differentiate between those who had disengaged from care completely and those who remained well engaged but were simply delayed in leaving the pediatric care setting. The Pediatric HIV/AIDS Cohort Study Amp Up multicenter cohort is not focused exclusively on healthcare transition but does collect data prospectively and documented self-reported retention rates of 80% after transition to adult care in a sample of 124 youth (all of whom had vertically acquired HIV) [21].

To tailor interventions to optimize HIV care outcomes through the healthcare transition process, it is essential to improve our collective understanding of long-term HIV care continuum outcomes after entry into adult care. To this end, we aimed to prospectively evaluate HIV care engagement outcomes in a single-center youth cohort.

METHODS

Study Design

We conducted a prospective, observational cohort study of healthcare transition among youth enrolled at a large HIV care center in Atlanta, Georgia. This center contains both a pediatric clinic (serving approximately 500 patients) and adult-oriented clinics (serving >5000 patients) within the same building; they are in physically separate locations and most healthcare providers work in one section or the other. Patients are typically transitioned from the pediatric clinic to the adult-oriented clinic around their 25th birthday. Despite the physical proximity of the pre- and posttransition clinics, we have previously found evidence of transition-related disruption to care in retrospective studies conducted in this setting [10, 17]. Multidisciplinary teams plan for and coordinate healthcare transition from the pediatric clinic; however, there is no uniform protocol in this facility for transitioning patients to adult care, and details of this process vary slightly for each individual pediatric provider, adult care provider, and patient.

Seventy participants were recruited from the pediatric clinic between August 2016 and June 2018. With the permission of their treating pediatric providers, eligible participants were approached at scheduled clinical visits within 3 months before planned transfer to adult care. If they provided informed consent and were enrolled in the study, they were then followed up over the subsequent year to determine HIV care continuum outcomes through serial chart abstractions from the electronic medical record. Clinical data was abstracted at baseline (study enrollment) and at 6-, 12-, 18-, and 24-month time points. Participants also self-administered a baseline survey including demographic information as well as other psychosocial measures and received $25 for completing this enrollment visit. The study was approved by the Emory University Institutional Review Board and the Grady Research Oversight Committee.

Clinical Outcomes

Our outcomes of interest were drawn from the HIV care continuum framework [14], with a focus on linkage to adult care, retention in adult care, and viral suppression in adult care. Linkage to care was defined as attending ≥1 visit with an adult provider. We examined linkage as a binary outcome (ie, were participants linked or not? ) and also examined time to linkage (the amount of time between the last pediatric and first adult visits). Retention in care, among those who had linked to adult care, was examined in 2 ways, reflecting previously used measures [19, 22]. First, we analyzed retention as continuous engagement, defined as having ≥1 HIV primary care visit during each of the 6-month abstraction periods (0–6, 6–12, 12–18, and 18–24 months). Second, we examined retention in terms of missed clinic visits. Viral suppression was defined as an HIV RNA level <200 copies/mL for the most recent viral load measurement documented in each 6-month abstraction period.

Statistical Analysis

The cumulative time to linkage was estimated with the Kaplan-Meier method. All participants were included in this linkage analysis. The standard error of the Kaplan-Meier estimate was calculated based on Greenwood's formula and used to construct 95% confidence intervals (CIs) for the time-to-linkage curve [23].

The generalized estimating equation (GEE) approach proposed by Liang and Zeger [24] was used to estimate retention in care by each 6-month follow-up period and to account for the correlation between multiple observations from the same participant. A GEE analysis was performed for the repeated binary responses within participants for the retention data (exchangeable correlation binomial logit model). For each 6-month follow-up interval, the percentage retained in care and its 95% CI are reported. The same analysis was done for viral suppression based on data available at each of 5 time points (0, 6, 12, 18 and 24 months). The model-based estimates are unbiased with unbalanced and missing data, as long as the missing data are noninformative (missing completely at random).

The yearly incidence rates of missed visit rates were estimated by performing a GEE Poisson regression analysis of the yearly missed visit counts implemented using the SAS GENMOD procedure and an exchangeable correlation structure for the repeated counts within each subject. The incidence of missed visits per 100 person-months of follow-up and its 95% CI were calculated by year of follow-up.

RESULTS

Baseline Descriptions

We enrolled 70 participants in our prospective study. The majority were male (88.6%), black (92.9%), and horizontally infected (82.9%). At the time of their baseline visits (while still enrolled in pediatric care), 74.3% were virally suppressed. Additional demographic and clinical data are summarized in Table 1.

Table 1.

Baseline Demographic and Clinical Characteristics for 70 Youth With Human Immunodeficiency Virus

CharacteristicParticipants, No. (%)a
Demographic
ȃAge at study enrollment, mean (SD) [IQR], y24.4 (0.5) [24.0–25.0]
ȃSex
ȃȃMale62 (88.6)
ȃȃFemale8 (11.4)
ȃRace/ethnicity
ȃȃBlack/African-American65 (92.9)
ȃȃHispanic/Latino/Latina1 (1.4)
ȃȃWhite3 (4.3)
ȃȃOther4 (5.7)
ȃMode of acquisition
ȃȃHorizontal58 (82.9)
ȃȃVertical12 (17.1)
ȃSexual orientation
ȃȃStraight/heterosexual13 (18.6)
ȃȃGay/queer/bisexual/questioning57 (81.4)
ȃHighest educational level
ȃȃLess than high school diploma9 (12.9)
ȃȃHigh school diploma18 (25.7)
ȃȃSome college or technical school25 (35.7)
ȃȃTechnical school graduate5 (7.1)
ȃȃCollege graduate13 (18.6)
ȃEmployment
ȃȃUnemployed20 (28.6)
ȃȃEmployed full time28 (40.0)
ȃȃEmployed part time22 (31.4)
ȃHousehold income
ȃȃ<$10 00028 (40.0)
ȃȃ$10 000–$19 99919 (27.1)
ȃȃ$20 000–$29 99912 (17.1)
ȃȃ≥$30 00011 (15.7)
Clinical
ȃCD4+ T-cell count, mean (SD) [IQR], cells/μL494.4 (278.3) [8.0–1202]
ȃHIV RNA suppressed (<200 copies/mL)52 (74.3)
ȃSTI (gonorrhea, chlamydia, or syphilis) in last 12 mo42 (60.0)
ȃComorbid conditions
ȃȃHypertension4 (5.7)
ȃȃAsthma10 (14.3)
ȃȃDepression22 (31.4)
ȃȃAnxiety10 (14.3)
ȃAny documented history of opportunistic infection9 (12.9)
CharacteristicParticipants, No. (%)a
Demographic
ȃAge at study enrollment, mean (SD) [IQR], y24.4 (0.5) [24.0–25.0]
ȃSex
ȃȃMale62 (88.6)
ȃȃFemale8 (11.4)
ȃRace/ethnicity
ȃȃBlack/African-American65 (92.9)
ȃȃHispanic/Latino/Latina1 (1.4)
ȃȃWhite3 (4.3)
ȃȃOther4 (5.7)
ȃMode of acquisition
ȃȃHorizontal58 (82.9)
ȃȃVertical12 (17.1)
ȃSexual orientation
ȃȃStraight/heterosexual13 (18.6)
ȃȃGay/queer/bisexual/questioning57 (81.4)
ȃHighest educational level
ȃȃLess than high school diploma9 (12.9)
ȃȃHigh school diploma18 (25.7)
ȃȃSome college or technical school25 (35.7)
ȃȃTechnical school graduate5 (7.1)
ȃȃCollege graduate13 (18.6)
ȃEmployment
ȃȃUnemployed20 (28.6)
ȃȃEmployed full time28 (40.0)
ȃȃEmployed part time22 (31.4)
ȃHousehold income
ȃȃ<$10 00028 (40.0)
ȃȃ$10 000–$19 99919 (27.1)
ȃȃ$20 000–$29 99912 (17.1)
ȃȃ≥$30 00011 (15.7)
Clinical
ȃCD4+ T-cell count, mean (SD) [IQR], cells/μL494.4 (278.3) [8.0–1202]
ȃHIV RNA suppressed (<200 copies/mL)52 (74.3)
ȃSTI (gonorrhea, chlamydia, or syphilis) in last 12 mo42 (60.0)
ȃComorbid conditions
ȃȃHypertension4 (5.7)
ȃȃAsthma10 (14.3)
ȃȃDepression22 (31.4)
ȃȃAnxiety10 (14.3)
ȃAny documented history of opportunistic infection9 (12.9)

Abbreviations: HIV, human immunodeficiency virus; IQR, interquartile range; SD, standard deviation; STI, sexually transmitted infection.

Data represent no. (%) of participants unless otherwise specified.

Table 1.

Baseline Demographic and Clinical Characteristics for 70 Youth With Human Immunodeficiency Virus

CharacteristicParticipants, No. (%)a
Demographic
ȃAge at study enrollment, mean (SD) [IQR], y24.4 (0.5) [24.0–25.0]
ȃSex
ȃȃMale62 (88.6)
ȃȃFemale8 (11.4)
ȃRace/ethnicity
ȃȃBlack/African-American65 (92.9)
ȃȃHispanic/Latino/Latina1 (1.4)
ȃȃWhite3 (4.3)
ȃȃOther4 (5.7)
ȃMode of acquisition
ȃȃHorizontal58 (82.9)
ȃȃVertical12 (17.1)
ȃSexual orientation
ȃȃStraight/heterosexual13 (18.6)
ȃȃGay/queer/bisexual/questioning57 (81.4)
ȃHighest educational level
ȃȃLess than high school diploma9 (12.9)
ȃȃHigh school diploma18 (25.7)
ȃȃSome college or technical school25 (35.7)
ȃȃTechnical school graduate5 (7.1)
ȃȃCollege graduate13 (18.6)
ȃEmployment
ȃȃUnemployed20 (28.6)
ȃȃEmployed full time28 (40.0)
ȃȃEmployed part time22 (31.4)
ȃHousehold income
ȃȃ<$10 00028 (40.0)
ȃȃ$10 000–$19 99919 (27.1)
ȃȃ$20 000–$29 99912 (17.1)
ȃȃ≥$30 00011 (15.7)
Clinical
ȃCD4+ T-cell count, mean (SD) [IQR], cells/μL494.4 (278.3) [8.0–1202]
ȃHIV RNA suppressed (<200 copies/mL)52 (74.3)
ȃSTI (gonorrhea, chlamydia, or syphilis) in last 12 mo42 (60.0)
ȃComorbid conditions
ȃȃHypertension4 (5.7)
ȃȃAsthma10 (14.3)
ȃȃDepression22 (31.4)
ȃȃAnxiety10 (14.3)
ȃAny documented history of opportunistic infection9 (12.9)
CharacteristicParticipants, No. (%)a
Demographic
ȃAge at study enrollment, mean (SD) [IQR], y24.4 (0.5) [24.0–25.0]
ȃSex
ȃȃMale62 (88.6)
ȃȃFemale8 (11.4)
ȃRace/ethnicity
ȃȃBlack/African-American65 (92.9)
ȃȃHispanic/Latino/Latina1 (1.4)
ȃȃWhite3 (4.3)
ȃȃOther4 (5.7)
ȃMode of acquisition
ȃȃHorizontal58 (82.9)
ȃȃVertical12 (17.1)
ȃSexual orientation
ȃȃStraight/heterosexual13 (18.6)
ȃȃGay/queer/bisexual/questioning57 (81.4)
ȃHighest educational level
ȃȃLess than high school diploma9 (12.9)
ȃȃHigh school diploma18 (25.7)
ȃȃSome college or technical school25 (35.7)
ȃȃTechnical school graduate5 (7.1)
ȃȃCollege graduate13 (18.6)
ȃEmployment
ȃȃUnemployed20 (28.6)
ȃȃEmployed full time28 (40.0)
ȃȃEmployed part time22 (31.4)
ȃHousehold income
ȃȃ<$10 00028 (40.0)
ȃȃ$10 000–$19 99919 (27.1)
ȃȃ$20 000–$29 99912 (17.1)
ȃȃ≥$30 00011 (15.7)
Clinical
ȃCD4+ T-cell count, mean (SD) [IQR], cells/μL494.4 (278.3) [8.0–1202]
ȃHIV RNA suppressed (<200 copies/mL)52 (74.3)
ȃSTI (gonorrhea, chlamydia, or syphilis) in last 12 mo42 (60.0)
ȃComorbid conditions
ȃȃHypertension4 (5.7)
ȃȃAsthma10 (14.3)
ȃȃDepression22 (31.4)
ȃȃAnxiety10 (14.3)
ȃAny documented history of opportunistic infection9 (12.9)

Abbreviations: HIV, human immunodeficiency virus; IQR, interquartile range; SD, standard deviation; STI, sexually transmitted infection.

Data represent no. (%) of participants unless otherwise specified.

Linkage to Adult Care

Of our cohort, 74% linked to adult care within 6 months of their enrollment in the study, and 84% were linked to adult care by the 12-month follow-up. The mean time to linkage was 105.8 days (standard deviation, 72.5 days), or between 3 and 4 months. Of the 8 who were not linked within 12 months, 1 had moved outside of the health system, 2 were still being followed up by the pediatric provider at 12 months, and the other 5 had presumably disengaged from care (ie, no scheduled appointments were documented) before linking to an adult provider in the clinic. Figure 1 depicts linkage to adult care during the initial 12-month follow-up period. We examined potential associations between baseline demographic and clinical factors with time to adult care linkage; no significant differences were found based on demographic or clinical factors.

Time to linkage to the adult clinic, as assessed by the Kaplan-Meier method. Abbreviation: CI, confidence interval.
Figure 1.

Time to linkage to the adult clinic, as assessed by the Kaplan-Meier method. Abbreviation: CI, confidence interval.

Retention in Adult Care

We first examined retention in care in terms of continuous engagement, defined as having ≥1 visit in each 6-month interval after transition to adult care. Of those who linked to adult care, 86% (95% CI, 78%–94%) were retained at 6 months, 76% (66%–86%) were retained at 12 months, and 66 (55%–78%) were still engaged at the 18- and 24-month time points (Table 2 and Figure 2).

Retention in human immunodeficiency virus care for youth linked to adult care (N = 62).
Figure 2.

Retention in human immunodeficiency virus care for youth linked to adult care (N = 62).

Table 2.

Retention in Care for Participants Who Linked to Adult Care

Time in Study, moaParticipants, No. (N = 62)Participants Retained in Care, % (95% CI)
No Appointments AttendedAttended ≥1 Appointment
0–675589 (81–97)
6–12115182 (73–92)
12–18174573 (62–85)
18–24184471 (61–83)
Time in Study, moaParticipants, No. (N = 62)Participants Retained in Care, % (95% CI)
No Appointments AttendedAttended ≥1 Appointment
0–675589 (81–97)
6–12115182 (73–92)
12–18174573 (62–85)
18–24184471 (61–83)

Abbreviation: CI, confidence interval.

Time in study was defined as a categorical variable with four levels (0–6 months, 6–12 months, 12–18 months, 18–24 months). Retention in care for participants who linked to adult care was not statistically different by the four time on study categories (P = 0.08).

Table 2.

Retention in Care for Participants Who Linked to Adult Care

Time in Study, moaParticipants, No. (N = 62)Participants Retained in Care, % (95% CI)
No Appointments AttendedAttended ≥1 Appointment
0–675589 (81–97)
6–12115182 (73–92)
12–18174573 (62–85)
18–24184471 (61–83)
Time in Study, moaParticipants, No. (N = 62)Participants Retained in Care, % (95% CI)
No Appointments AttendedAttended ≥1 Appointment
0–675589 (81–97)
6–12115182 (73–92)
12–18174573 (62–85)
18–24184471 (61–83)

Abbreviation: CI, confidence interval.

Time in study was defined as a categorical variable with four levels (0–6 months, 6–12 months, 12–18 months, 18–24 months). Retention in care for participants who linked to adult care was not statistically different by the four time on study categories (P = 0.08).

We also examined missed visits, which have been proposed as another important measure of retention in care. The rates of missed visits did not differ significantly between the last year in pediatric care, the first year in adult care, and the second year in adult care (Table 3).

Table 3.

Rates of Missed Visits by Time Period

Time PeriodMissed Visits per 100 mo of Follow-up (95% CI)P Value
Missed visits
ȃLast 12 mo in pediatric clinic21.9 (18.3–26.2).16
ȃFirst 12 mo in adult clinic18.4 (14.6–23.2)
ȃSecond 12 mo in adult clinic17.2 (13.0–22.7)
Overall (all participants)19.2 (16.2–22.7)
Time PeriodMissed Visits per 100 mo of Follow-up (95% CI)P Value
Missed visits
ȃLast 12 mo in pediatric clinic21.9 (18.3–26.2).16
ȃFirst 12 mo in adult clinic18.4 (14.6–23.2)
ȃSecond 12 mo in adult clinic17.2 (13.0–22.7)
Overall (all participants)19.2 (16.2–22.7)

Abbreviation: CI, confidence interval.

Table 3.

Rates of Missed Visits by Time Period

Time PeriodMissed Visits per 100 mo of Follow-up (95% CI)P Value
Missed visits
ȃLast 12 mo in pediatric clinic21.9 (18.3–26.2).16
ȃFirst 12 mo in adult clinic18.4 (14.6–23.2)
ȃSecond 12 mo in adult clinic17.2 (13.0–22.7)
Overall (all participants)19.2 (16.2–22.7)
Time PeriodMissed Visits per 100 mo of Follow-up (95% CI)P Value
Missed visits
ȃLast 12 mo in pediatric clinic21.9 (18.3–26.2).16
ȃFirst 12 mo in adult clinic18.4 (14.6–23.2)
ȃSecond 12 mo in adult clinic17.2 (13.0–22.7)
Overall (all participants)19.2 (16.2–22.7)

Abbreviation: CI, confidence interval.

Viral Load Suppression

Of those in the sample, 74.3% were virally suppressed at baseline. Among those who linked to adult care, the proportion with viral suppression remained stable (with 82.5% suppressed at 6, 81.1% at 12, 85.7% at 18, and 87.5% at 24 months; Table 4). For this well-engaged subset of our sample, within-individual comparisons of viral suppression using McNemar's test did not detect a significant difference between pre– and post–healthcare transition viral suppression at 1-year (P = .25; data not shown) or 2-year (P = .32; data not shown) follow-up.

Table 4.

Viral Load Suppression Over Time

Time PointParticipants With or Without Viral Load Suppression, No. (%)
Not SuppressedSuppressedTotal
Baseline18 (25.7)52 (74.3)70 (100)
6 mo10 (17.5)47 (82.5)57 (100)
12 mo10 (18.9)43 (81.1)53 (100)
18 mo6 (14.3)36 (85.7)42 (100)
24 mo5 (12.5)35 (87.5)40 (100)
Time PointParticipants With or Without Viral Load Suppression, No. (%)
Not SuppressedSuppressedTotal
Baseline18 (25.7)52 (74.3)70 (100)
6 mo10 (17.5)47 (82.5)57 (100)
12 mo10 (18.9)43 (81.1)53 (100)
18 mo6 (14.3)36 (85.7)42 (100)
24 mo5 (12.5)35 (87.5)40 (100)
Table 4.

Viral Load Suppression Over Time

Time PointParticipants With or Without Viral Load Suppression, No. (%)
Not SuppressedSuppressedTotal
Baseline18 (25.7)52 (74.3)70 (100)
6 mo10 (17.5)47 (82.5)57 (100)
12 mo10 (18.9)43 (81.1)53 (100)
18 mo6 (14.3)36 (85.7)42 (100)
24 mo5 (12.5)35 (87.5)40 (100)
Time PointParticipants With or Without Viral Load Suppression, No. (%)
Not SuppressedSuppressedTotal
Baseline18 (25.7)52 (74.3)70 (100)
6 mo10 (17.5)47 (82.5)57 (100)
12 mo10 (18.9)43 (81.1)53 (100)
18 mo6 (14.3)36 (85.7)42 (100)
24 mo5 (12.5)35 (87.5)40 (100)

DISCUSSION

In our prospective, single-center cohort of youth with HIV, we found that initial linkage to adult care was high; however, rates of retention in care declined significantly over a 2-year follow-up period. Among those who were retained in adult care, rates of viral suppression did not worsen in the adult care setting. Strengths of our study include the prospective design and 2-year follow-up period, which allowed for assessment of the sustainability of retention in care. In contrast to many prior studies, our cohort primarily comprised youth with horizontally acquired infection (particularly young gay, bisexual, and other men who have sex with men), consistent with the epidemiology of HIV among youth in the United States.

Our prospective study design was particularly helpful for analyzing linkage to care, as prior retrospective studies were often limited to those who had already linked and could not assess loss to follow-up among transition-eligible youth. With respect to linkage to adult care, our findings suggest a much higher rate than the aforementioned multicenter Adolescent Medicine Trials Network for HIV/AIDS Interventions study, which only documented successful linkage to care in 39% of youth with HIV [25]; this difference is likely due in part to the longer follow-up period in our study as well as the fact that patients in our cohort can remain in the same physical building through their transition. We were also able to contribute additional context to the phenomenon of delayed linkage by documenting that, in many cases, lack of linkage was not due to falling out of care but simply to staying engaged in pediatric care longer than anticipated. Prior qualitative work invokes barriers on both the pediatric provider and patient sides that can contribute to this delay [9, 26]; multilevel interventions may be warranted to improve efficiency of the healthcare transition process.

In our setting, retention in adult care represented the most significant gap in the posttransition care continuum. This gap represents an underaddressed area in the field of healthcare transition research, which focuses overwhelmingly on pretransition preparation and processes, often with an end goal of initial linkage to adult care. There are no rigorously tested healthcare transition interventions for HIV to date; however, the protocols that have been published are more likely to focus on preparation for transition, in the pediatric setting and at the patient level [27–29]. Our results suggest that in addition to such programs, efforts to continue to support youth to stay engaged in care, particularly in the 1–2 years immediately after transfer to adult care, would be particularly useful. Griffith and colleagues [15] report on a more comprehensive transition protocol emphasizing social service support throughout and after transition; further research to test such protocols in randomized trials and scale-up in other settings is warranted. Of note, we did not collect retention data for all comers in the adult clinic during the time this study was undertaken. However, an earlier analysis conducted in our adult clinic noted similar, or even slightly poorer, rates of continuous retention in care [30]. There were differences in the way that continuous retention was measured; however, this comparison does suggest that additional supports provided in pediatric clinics might be useful for all adult patients, not only those transitioning from pediatric care.

Viral suppression is the final goal and most important stage of the HIV care continuum in terms of preventing disease, death, and HIV transmission. In our cohort, viral suppression remained similar to baseline for those who successfully remained engaged in care. This result is distinctly different from findings presented by Griffith and colleagues [15], in which viral suppression rates decreased even among those retained in care, and also from Xia and colleagues [18], who found that viral suppression improved after transition in their surveillance-based cohort in New York City. Notably, Griffith and colleagues included data from 2009 to 2015, when antiretroviral regimens were less well tolerated, which may have affected outcomes. In our study, it would have been helpful to have viral load measurements for those who were not retained in care; however, we did not have the ability in this study to track down participants lost to follow-up or to measure viral loads directly.

Several limitations to generalizability arise from the unique characteristics of our clinical study setting, with its colocated pediatric and adult care services. The Ryan White funding supporting the clinic also provides for additional social work and mental health support services that other types of clinics may not have. It is also possible that participation in our study, though it was designed as an observational and not an interventional study, could have theoretically compelled individuals to stay in care. Given these factors, we may actually be underestimating challenges to healthcare transition; rates of linkage in particular might be expected to be lower in settings where adult and pediatric care are not colocated. Furthermore, patients in our cohort transition at a relatively older age (25 years), consistent with many US sites [11] but much older than in many other settings globally—this leads to differences in familial involvement and developmental maturity that could affect healthcare transition outcomes as well. Additional limitations arise due to incomplete follow-up in patients who did not link to adult care. For most of them, we were unable to ascertain the reason for nonlinkage; some may be successfully engaged in adult care outside our healthcare system.

In conclusion, successful healthcare transition for youth with HIV is critically important for individual health and well-being, as well as for achieving the public health goals of the Ending the Epidemic initiative [1]. Interventions to enhance retention in care after transition while in adult care will be particularly important to improving HIV-related outcomes in this high priority group.

Notes

Financial support. This work was supported by the Robert Wood Johnson Foundation through the Harold Amos Medical Faculty Development Program (project 73309; career development grant to S. A. H. for this project) and by the National Institute of Allergy and Infectious Diseases at the National Institutes of Health (grant P30 AI050409) via the Emory Center for AIDS Research (assistance with funding for study conduct; Emory Center’s principal investigator, C. d. R.).

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Author notes

Potential conflicts of interest. B. C. Z. reports grants or contracts unrelated to this work from National Institute of Mental Health (grant K23MH114771) and participation as a volunteer member of the CombinADO data and safety monitoring board (UH3HD096926; principal investigator, Elaine Abrams). C. d. R. is a scientific advisor for and reports consulting fees from Resverlogix. All other authors report no potential conflicts.

All authors have submitted the ICMJE Form for Disclosure of Potential Conflicts of Interest. Conflicts that the editors consider relevant to the content of the manuscript have been disclosed.

This article is published and distributed under the terms of the Oxford University Press, Standard Journals Publication Model (https://dbpia.nl.go.kr/pages/standard-publication-reuse-rights)