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. Author manuscript; available in PMC: 2021 Nov 1.
Published in final edited form as: AIDS Care. 2019 Dec 6;32(11):1343–1352. doi: 10.1080/09540121.2019.1698704

HIV Care Cascade Before and After Hospitalization: Impact of a Multidisciplinary Inpatient Team in the US South

AE Nijhawan 1, M Bhattatiry 2, M Chansard 3, S Zhang 4, EA Halm 5
PMCID: PMC7274864  NIHMSID: NIHMS1546436  PMID: 31809594

Abstract

Hospitalization represents a unique opportunity to re-engage out-of-care individuals, improve HIV outcomes and reduce health disparities. Electronic health records of HIV-positive individuals hospitalized at an urban, public hospital between September 2013- December 2015 were reviewed. In October 2014, a multidisciplinary HIV consult team (HIV specialist, case manager, and transitional care nurse (TCN)) was implemented. Engagement in care, retention in care and virologic suppression before and after hospitalization were compared between the pre- and post-intervention periods and by treatment received. Of 1056 inpatient admissions (pre-intervention=571, post-intervention=485), the majority were among males (69%) and racial/ethnic minorities (55% Black, 23% Hispanic). Each step of the HIV care cascade increased after hospitalization for both time periods (p<0.01 for each comparison). Those who received the HIV consult (N=131) or consult +TCN (N=128) had greater increases in engagement in care (23.7% and 30.5% v. 11.1%, p=0.04 and <0.01 respectively) and virologic suppression (28.3% and 29.7% v.7.1%, p <0.01 for both) than the no intervention (N=225) subgroup. Hospitalized patients with HIV have low rates of engagement in care, retention in care and virologic suppression, though all three outcomes improved after hospitalization. A multidisciplinary transitions team improved care engagement and virologic suppression in those who received the intervention.

Keywords: Hospitalization, HIV care cascade, transition of care, retention

Introduction

Despite major decreases in mortality and morbidity since the introduction of antiretroviral therapy (ART) (Metsch et al., 2009; Zhao, Encinosa, & Hellinger, 2006), fewer than half of people living with HIV (PLWH) in the United States are engaged in ongoing medical care (Hall et al., 2012; Mugavero, 2016; Mugavero et al., 2012). Low rates of engagement and retention in HIV care result in decreased access to ART, uncontrolled HIV infection and poor health outcomes (Mugavero, 2016; Thompson et al., 2012). Certain subgroups are at higher risk for non-engagement in care, including PLWH who are black or Hispanic (CDC, 2014, 2017; Dasgupta, Oster, Li, & Hall, 2016; Horberg et al., 2015), in younger age groups (CDC, 2017; Horberg, et al., 2015) and who are living in the Southern US (Philbin et al., 2018). Various individual and structural barriers to engagement and retention in care have been identified, including housing instability (Holtzman, Brady, & Yehia, 2015), stigma (Holtzman, et al., 2015; Taylor et al., 2018), substance use disorders (Holtzman, et al., 2015), mental illness (Bengtson et al., 2018; Holtzman, et al., 2015; Yehia et al., 2015), limited social support (Taylor, et al., 2018) and transportation. New interventions in diverse settings are needed to overcome these barriers to reduce disparities in HIV outcomes.

Hospitalization represents a critical period to re-engage a vulnerable subset of PLWH (Buchacz et al., 2008; Lazar, Kersanske, Xia, Daskalakis, & Braunstein, 2017; Metsch et al., 2016) who are more likely to experience gaps in the HIV care cascade (Bell et al., 2010; E. M. Gardner and Haukoos, 2015; Kerr, Stephens, Gibson, & Duffus, 2012; Metsch, et al., 2016), but who demonstrate a high willingness to participate in re-engagement in care (Davila et al., 2017). Most interventions aiming to improve engagement in care and virologic suppression have been conducted in the outpatient setting through combinations of patient education (Cabral et al., 2018; Giordano et al., 2016), addressing specific barriers to care (Cabral, et al., 2018; Cunningham et al., 2018; L. I. Gardner et al., 2005; Giordano, et al., 2016; Irvine et al., 2015), telephone follow-up (Gentry, van-Velthoven, Tudor Car, & Car, 2013) and patient navigation (Craw et al., 2008). Several re-engagement interventions have focused on hospitalized PLWH, though with modest success (Giordano, et al., 2016; Metsch, et al., 2016). A multidisciplinary intervention, which addresses both medical and social factors associated with HIV outcomes as well as care coordination, has the potential to build on evidence-based interventions from the outpatient setting and extend this to inpatients.

In this study, we aim to (a) assess changes in the HIV care cascade (engagement in care, retention in care, virologic suppression) before and after hospitalization and (b) measure the impact of a multidisciplinary HIV inpatient intervention (medical consultation +/− transitional care nurse (TCN)) on care engagement and clinical outcomes.

Methods

We conducted a retrospective review of electronic health records (EHR) of PLWH hospitalized in the Parkland Health and Hospital System (PHHS) one year before and after the implementation of a multidisciplinary HIV inpatient team. Parkland is an 870 bed urban, public hospital and the primary safety net health system in Dallas, TX. This study was approved by the UT Southwestern Medical Center Institutional Review Board.

The multidisciplinary HIV transitions team, supported in part through the Center for Medicare and Medicaid Services (CMS) 1115 waiver program, was implemented in October 2014 with the goal of reducing 30-day hospital readmissions for HIV-positive inpatients. Members of the team address different aspects of patient care: medical (HIV specialists and advanced practice providers), social (TCNs) and care coordination (HIV case managers). The medical HIV team provides diagnostic and therapeutic recommendations and post-discharge follow-up and is activated when an HIV consult is placed by the primary treatment team. The TCN approaches patients within this consult group who are deemed high-risk for readmission (new HIV diagnosis, prior admission, psychosocial needs) to review barriers to care, complete patient education using a teach-back method and develop an individualized transitional care plan. HIV case managers provide care coordination (arrange funding, follow-up visits, referrals) for all hospitalized PLWH. Interdisciplinary team rounds are conducted each weekday. Prior to October 2014, medical consults for HIV inpatients were performed by the general infectious diseases team without formal coordination with HIV case management, and the TCN and advanced practice provider positions did not exist.

Data were obtained from the EHR (Epic systems, Verona, WI) and included all individuals with a diagnosis of HIV (as per ICD-9, ICD-10 code, positive HIV test result, or an HIV viral load ≥ 20 copies/mL); aged 18 or older; who had an inpatient admission to PHHS between 9/1/2013 and 12/30/2015 and who had had 1 or more outpatient HIV clinic visits within the hospital system prior to admission. Outpatient data (clinic visits and HIV viral loads) were obtained for one year preceding and following the inpatient admissions (i.e. 9/1/2012 through 12/30/2016).

Variables collected included: demographics (age, gender, race, ethnicity, marital status, primary language), socio-economic and behavioral variables (insurance status, homelessness, substance use, mental illness), clinical variables (CD4 count, HIV viral load) and hospitalization characteristics (primary inpatient diagnoses, length of stay, discharge status). Mental health was categorized into the following categories: depression/suicidality/mania; anxiety, schizophrenia/psychosis, other/multiple diagnoses based on ICD-9/10 classification. Substance use was determined by drug screen result.

Similar to previously published methods (Berry, Fleishman, Moore, Gebo, & Network, 2012; Berry et al., 2013), we determined the primary admitting diagnosis using the first listed ICD-9/ICD-10 code assigned at discharge, unless it was a code for HIV (042, B20, V08, Z21), in which case the second code was used. Clinical Classification Software (CCS) was used to assign primary ICD-9 and ICD-10 codes into one of 18 clinically meaningful categories (Elixhauser A, 2015) and modified as per previous studies (Berry, et al., 2012; Berry, et al., 2013). We reassigned end-organ infections to the non-AIDS-related infection category and defined a separate category for AIDS-defining illnesses (CDC, 1992).

Between March 2015 to June 2017 TCNs collected a checklist of barriers to HIV care including: incarceration, funding, mental health, substance use, social support, stigma, health literacy, homelessness, transportation, pill burden, and compatibility with provider from.

Engagement in care was defined as ≥1 HIV clinic visit within the six months prior to hospitalization or following discharge; retention in care was defined as two HIV clinic visits > 90 days apart within twelve months prior to hospitalization or following discharge; HIV virologic suppression was defined as <200 copies/mL (most recent value up to 90 days prior to admission and within 6 months after discharge).

The cohort was separated into two “treatment” groups for evaluation: those hospitalized before the team was implemented on October 1, 2014 (team=0), and those hospitalized after this date (team=1). Comparisons between groups were performed based on the Student’s t-test for continuous variables and Chi-square test for categorical variables. Nonparametric methods such as the Wilcoxon rank-sum test were employed where appropriate. The proportion of patients who were engaged in care, retained in care and had virologic suppression were determined for each group before and after hospitalization. For each binary outcome, we constructed GEE models (Zeger, Liang, & Albert, 1988) where the log link function was used. Covariates included time, intervention, and their interaction, and subject random effects were included to account for correlation among observations from the same subjects. Such models allow us to make inference about (a) the difference in each of outcome before and after hospitalization and (b) the difference in differences in each outcome between treatment groups (e.g. the difference in engagement in care before and after hospitalization compared between the pre- and post-intervention groups) based on the interaction terms.

To assess the impact of the HIV team, a “dose response, treatment received” approach focused on those who were hospitalized after the implementation of multidisciplinary team (team=1 only) and divided them into three groups: 1) not evaluated by the team (no consult), 2) evaluated by medical team but not TCN (consult only), and 3) evaluated by medical team and TCN (consult +TCN). Individuals who were approached by the TCN but who did not receive TCN services (e.g. patient refused), N=10, were included in the consult only group. Similar GEE logistic models were employed to assess the difference in outcomes (engagement, retention and suppression) before and after hospitalization between each of the three groups (no consult, consult only, and consult +TCN).

All statistical analyses were performed using SAS 9.4 (SAS Institute, Cary, NC).

Results

Overall 3245 individuals with HIV had an inpatient admission during the entire study period (9/1/2012–12/30/2016). Of these, we excluded: 250 were <18 years old, 1271 hospitalized before 9/1/2013 or after 12/30/2015, and 668 did not have any HIV clinic visit data prior to hospitalization, leaving 1056 individuals included in the final analysis (Figure 1).

Figure 1.

Figure 1.

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Flow diagram of final study cohort

The cohort was majority male (69%), non-Hispanic black (55%) and single (77%). Health insurance included Medicaid (33%), Medicare (27%), charity care (37%) and private insurance (3%). Nearly 40% had AIDS by CD4 criteria (18% CD4<50; 20% CD4 50– 200), and only 45% had an HIV viral load < 200 copies/mL. The most common causes for admission were: non AIDS-defining Infections (20%), followed by Respiratory (9%), Digestive (9%) and Circulatory (7%) systems. AIDS defining illnesses made up 5% of primary admitting diagnoses overall. The median length of hospital stay was longer in the post-intervention period (5 v 4 days, p<0.01), but otherwise baseline characteristics were similar between the two time periods (Table 1).

Table 1.

Baseline characteristics of HIV-positive patients at time of index admission

Variable Total HIV
Admissions
N=1056		 Admitted before
Transitions Team
n=571		 Admitted after
Transitions Team
n=485		 P value
N (%) n (%) n (%)
Age study start, median (range) 45 (18, 80) 46 (18, 80) 45 (19, 76) 0.65
Sex
 Male 729 (69) 388 (68) 341 (70) 0.41
 Female 327 (31) 183 (32) 144 (30)
Race/Ethnicity
 Non-Hispanic Black 582 (55) 308 (54) 274 (56) 0.55
 Non-Hispanic White 211 (20) 118 (21) 93 (19)
 Hispanic 240 (23) 135 (24) 105 (22)
 Other 23 (2) 10 (2) 13 (3)
Language
 English 914 (87) 488 (85) 426 (88) 0.43
 Spanish 122 (12) 70 (12) 52 (11)
 Other 20 (2) 13 (2) 7 (1)
Marital status
 Single 812 (77) 442 (77) 370 (76) 0.77
 Married 122 (11) 57 (10) 55 (11)
 Divorced/widowed/other 132 (13) 72 (13) 60 (12)
Insurance
 Medicaid 346 (33) 202 (35) 144 (30) 0.16
 Medicare 284 (27) 146 (26) 138 (28)
 Charity/Self-pay 392 (37) 202 (35) 190 (39)
 Private 34 (3) 21 (4) 13 (3)
Any Psychiatric Diagnoses
 Yes 252 (24) 126 (22) 126 (26) 0.14
 No 804 (76) 445 (78) 359 (74)
Psychiatric Diagnosis Class
 Depression/ Suicidality/ Mania 92 (9) 51 (9) 41 (8) 0.30
 Anxiety 42 (4) 17 (3) 25 (5)
 Schizophrenia / Psychosis 25 (2) 12 (2) 13 (3)
 Other/ Multiple Diagnoses 93 (9) 46 (8) 47 (10)
Drug Screen Result
 Positive 119 (11) 60 (11) 59 (12) 0.40
 Negative/ No Test 937 (89) 511 (89) 426 (88)
Positive Result Drug Class
 Amphetamines 16 (2) 7 (1) 9 (1) 0.61
 Benzodiazepines 5 (0) 3 (1) 2 (0)
 Cocaine 34 (3) 16 (3) 18 (4)
 Opiates 38 (4) 23 (4) 15 (3)
 Multiple Drugs 26 (2) 11 (2) 15 (3)
Any History of Homelessness
 Yes 89 (8) 43 (8) 46 (9) 0.25
 No 967 (92) 528 (92) 439 (91)
CD4
 <50 191 (18) 103 (18) 88 (18) 0.75
 51-200 214 (20) 112 (20) 102 (21)
 201-499 315 (30) 180 (32) 135 (28)
 >500 221 (21) 117 (20) 104 (21)
 Unknown/ Missing 115 (11) 59 (10) 56 (12)
Viral load (preadmission)
 <20 341 (32) 171 (30) 170 (35) 0.06
 21-200 133 (13) 83 (15) 50 (10)
 201-1000 48 (5) 31 (5) 17 (4)
 1001-10,000 51 (5) 28 (5) 23 (5)
 >10,001 200 (19) 115 (20) 85 (18)
 Unknown/ Missing 283 (27) 145 (25) 140 (29)
Length of stay, days, median (range) 4 (0, 75) 4 (0, 75) 5 (0, 66) .01
Primary admitting diagnosis
 AIDS-defining illness 54 (5) 34 (6) 20 (4) .01
 Non-ADI infections 207 (20) 99 (17) 108 (22)
 Neoplasms 40 (4) 24 (4) 16 (3)
 Endocrine/ nutrition/ metabolic/ immunity 36 (3) 24 (4) 12 (2)
 Blood blood-forming organs 15 (1) 8 (1) 7 (1)
 Mental Illness 18 (2) 11 (2) 7 (1)
 Nervous system/ sense organs 57 (5) 35 (6) 22 (5)
 Circulatory system 71 (7) 38 (7) 33 (7)
 Respiratory system 100 (9) 43 (8) 57 (12)
 Digestive system 90 (9) 47 (8) 43 (9)
 Genitourinary system 31 (3) 15 (3) 16 (3)
 Pregnancy/ childbirth/ puerperium 49 (5) 28 (5) 21 (4)
 Skin subcutaneous tissue 19 (2) 11 (2) 8 (2)
 Musculoskeletal system/ connective tissue 54 (5) 15 (3) 39 (8)
 Injury poisoning 33 (3) 24 (4) 9 (2)
 Misc. Health Status 148 (14) 92 (16) 56 (12)
 Residual Codes 34 (3) 23 (4) 11 (2)
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Self-reported barriers to care as collected by the TCN are presented in Table 2. The vast majority (85%), reported at least one barrier to care, and 39% had 3 or more barriers. Mental health (44%) and substance use (42%) were the most common, followed by funding issues (26%), lack of social support (26%) and incarceration (18%).

Table 2.

Barriers to care as recorded by Transitional Care Nurse

Proportion
with barrier
N=882
Any barrier to care 85%
    1-2 barriers 46%
    >=3 barriers 39%
Mental Health 44%
Substance Use 42%
Funding 26%
Social support 26%
Incarceration 18%
Transportation 16%
Homelessness 14%
Pill Burden 13%
Stigma 11%
Child Care 6%
Job Schedule 3%
Health Literacy 5%
Provider compatibility 2%
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Each step of the HIV care cascade increased significantly after hospitalization for both time periods (p<0.01 for each comparison). At the population level (examining all-comers regardless of treatment received), the gains in the care cascade were not significantly different after the multidisciplinary intervention team compared to before its implementation. Post-discharge engagement in care increased 17.9% (95%CI 13.1–22.6; from 67.1% (383/571) to 85.0% (485/571)) in the pre-intervention period and 19.8% (14.8–24.8; from 64.1% (311/485) to 83.9% (407/485)) in the post-intervention period, p=0.79; retention in care increased 10.7% (5.4–16.0; from 45.3% (259/571) to 56% (320/571)) v. 10.9% (5.3–16.6; from 45% (218/485) to 55.9% (271/485)), p=0.95, and viral suppression increased 15.1% (10.7–19.5; from 44.4% (254/571) to 59.5%(340/571)) v. 18.8% (13.9–23.5; from 45.3% (220/485) to 64.1% (311/485)), p=0.25 (Figure 2).

Figure 2.

Figure 2.

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HIV Care Cascade before and after Hospitalization, Stratified by Pre- and Post-Transitions Team Time Period

For analyses of the post-intervention group only (N=485), differences in each step of the care cascade were compared before and after hospitalization between three groups: 1) no consult N=225, 2) consult alone N=131, and 3) consult + TCN N=128. For engagement in care, patients who received these interventions had a significantly larger increase in post-discharge engagement when compared to those who did not receive any intervention components (consult (23.7%, 95% CI 14.2–33.1 from 61% (80/131) to 84.7% (111/131)) v. no consult (11.1%, 4.0–18.2, from 72.9% (164/225) to 84% (189/225)), p=0.04; TCN+ consult (30.5%, 20.2–40.8, from 52.3% (67/128) to 82.8% (106/128)) v. no consult (11.1%), p <0.01). There was no significant difference between those who received the consult alone (23.7%) vs. consult +TCN (30.5%), p=0.34. Increases in retention in care were not significantly different between the three groups (consult (15.3%,4.4–26.2 from 35.9% (47/131) to 51% (67/131)) v. no consult (7.1%, 1.3–15.5 from 55.6% (125/225) to 62.7% (141/225), p=0.24); consult +TCN (12.5%, 1.7–23.3, from 35.9% (46/128) to 48.4% (62/128) v. no consult (7.1%), p=0.44; and consult (15.3%) v. consult +TCN (12.5%), p=0.72. Increases in rates of virological suppression were significantly greater in consult group (28.3%, 20.0–36.5, from 30.5% (40/131) to 58.8% (77/131)) v. no consult (7.1%, 0.1–14.1, from 64.4% (145/225) to 71.5% (161/225), p<0.01) and in consult +TCN (29.7%, 20.2–39.2, from 26.6% (34/128) to 56.3% (72/128)) v. no consult (7.1%), p<0.01. There was no significant difference in increases in post-discharge virologic suppression between the two intervention groups, consult v. consult +TCN (28.3% v. 29.7%, p=0.82) (Figure 3).

Figure 3. Differences in Engagement in Care, Retention in Care, and Virologic Suppression Before and After Hospitalization During Intervention Period by Treatment Group.

Figure 3.

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Asterix indicates significant difference when compared to no consult group.

Discussion

We describe changes in the HIV care cascade for a large population of hospitalized PLWH who are predominantly male, of minority race/ethnicity, and either uninsured or receiving Medicaid. Despite prior linkage to HIV care, at the time of hospitalization this group had suboptimal retention in care (45%), low virologic suppression rates (45%) and a high proportion had AIDS (38%). As anticipated, we found that inpatient hospitalization was a key opportunity to improve re-engagement in HIV care, retention in care and virologic suppression. These improvements in the HIV care cascade after hospitalization were consistent over multiple years, from 2013–2015. We also found that implementation of a multi-disciplinary inpatient HIV team had a significantly larger impact on care engagement and virologic suppression among patients evaluated by the HIV medical team with or without a TCN visit (N=260 combined) compared to those who did not receive these services (N=225).

When comparing the entire post-intervention hospitalized group to historical controls, the improvements in the care cascade were not significantly different between the two time periods, though nearly half of the HIV-positive inpatients in the post-intervention time frame did not receive any additional services due to the HIV team not being consulted and/or limited TCN availability. In addition, when analyses were limited to those in the intervention time period, retention in care, using the Institute of Medicine definition of 2 visits >90 days apart in a 12 month period (Rebeiro et al., 2014), did not change significantly in the intervention groups compared to the no consult group. These results may be explained by limited sustainability of the intervention many months after hospital discharge, but may also be related to challenges in accurately measuring retention in care (Mugavero, Amico, Horn, & Thompson, 2013; Mugavero, et al., 2012), for which there is no gold standard.

Nearly all patients who meet with the TCN reported at least one barrier to HIV care continuity, especially mental health and substance use, followed by funding, social support, incarceration, transportation and homelessness. Over a third, 39%, reported ≥3 barriers to care, underscoring the social complexity of this inpatient cohort. Traditionally, mental healthcare in the inpatient setting focuses on acute symptom management (e.g. psychosis, suicidality), but does not address subacute problems, such as chronic depression, which may be a key contributor to hospitalization through nonadherence to medications, missed clinic visits, and substance use (Mitchell et al., 2010; Quinlivan et al., 2017; Zuniga, Yoo-Jeong, Dai, Guo, & Waldrop-Valverde, 2016). Similarly, acute medical issues related to substance use (e.g. overdose, withdrawal), may demand immediate medical management, whereas addiction treatment, such as medical assisted therapy or counseling, was until recently deferred to the post-discharge outpatient setting. New models of care which integrate mental health care and addiction services into the inpatient setting and provide a transition of care to continue this treatment after discharge are being implemented with positive results (Marks et al., 2018; Trowbridge et al., 2017; Wakeman, Metlay, Chang, Herman, & Rigotti, 2017), including in patients with HIV.

In our cohort, the primary medical reasons for admission were similar to other studies of PLWH, particularly those which include uninsured or safety net populations (Lazar, et al., 2017). We found that non-AIDS defining infections were most common, followed by respiratory, cardiovascular and gastro-intestinal causes. Our findings align with national trends documenting steady hospitalization rates among PLWH overall, with a decline in AIDS defining illnesses and an increase in other co-morbid conditions (Berry, et al., 2012; Gebo, Fleishman, & Moore, 2005).

Several other studies have examined the impact of interventions initiated in the inpatient setting on the HIV care cascade. A randomized intervention of peer mentoring sessions did not impact a combined outcome of virologic suppression and retention in care at 6 months (28% in each group) (Giordano, et al., 2016). In a multicenter study of hospitalized PLWH and substance use disorder randomized to patient navigation with or without financial incentives compared to treatment as usual, virologic suppression at 12 months (primary outcome), was not significantly different between groups. However, virologic suppression at 6 months (end of intervention) was 50% in those receiving navigation and incentives versus 38% in those receiving treatment as usual (p=0.03) (Metsch, et al., 2016). Both of these studies focused on high-risk subgroups (uncontrolled HIV, substance use disorders) and underscore the challenges with addressing multiple needs (peer support, education, care coordination) and sustainability of resource-intense interventions.

Our study has several limitations. First, it was conducted at a single site, which may limit generalizability. However, our safety-net population is representative of the HIV epidemic in other urban areas especially in the South, a region which leads the US in new HIV diagnoses but has worse clinical outcomes. Second, our intervention was not randomized, rather, it was delivered based on need (primary team requesting consult, readmission risk), and therefore our analyses are focused on a retrospective pre-post comparison using historical controls. However, our before and after populations were similar in terms of baseline characteristics. Lastly, we restricted our analyses to patients who at least one prior HIV clinic visit, thereby excluding new/recent diagnoses, patients who receive care from multiple institutions, and patients who had been lost to care.

At the time of hospital admission, many patients in our study had suboptimal engagement in outpatient HIV care and low rates of virologic suppression. The HIV care cascade improved after hospitalization in the overall study population, though these gains were not significantly greater in the post-intervention period compared to prior to implementation of the multidisciplinary transitions team. However, patients receiving one or more intervention component (HIV specialist consultation +/− TCN) had significantly greater improvements in engagement in care and virologic suppression than those who did not receive any intervention. The most common self-reported barriers to care were mental health and substance use. Hospitalization remains a key time and venue to re-engage out-of-care patients and improve clinical outcomes among PLWH. Future efforts to examine integration of routine mental health care and addiction medicine into inpatient care and coordination of post-hospitalization social services are needed.

Acknowledgments:

NIH K23 AI 112477, NIH R34 DA 045592, AHRQ R24 HS 022418

Footnotes

Conflicts: AN receives research funding from the Gilead FOCUS program.

Contributor Information

AE Nijhawan, Department of Internal Medicine, Division of Infectious Diseases, Department of Clinical Sciences, Division of Outcomes and Health Services Research, University of Texas Southwestern Medical Center, 5323 Harry Hines Blvd, Dallas, Texas 75390-9169; Parkland Health and Hospital Systems, Dallas, Texas.

M Bhattatiry, University of Texas Southwestern Medical Center, Dallas, Texas.

M Chansard, Department of Clinical Sciences, University of Texas Southwestern Medical Center, Dallas, Texas.

S Zhang, Department of Clinical Sciences, University of Texas Southwestern Medical Center, Dallas, Texas.

EA Halm, Department of Internal Medicine, Division of General Internal Medicine, Department of Clinical Sciences, Division of Outcomes and Health Services Research, University of Texas Southwestern Medical Center, Dallas, Texas.

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