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AIDS and Behavior

, Volume 22, Issue 8, pp 2615–2626 | Cite as

Exploring the Correlates of Linkage to HIV Medical Care Among Persons Living with HIV Infection (PLWH) in the Deep South: Results and Lessons Learned from the Louisiana Positive Charge Initiative

  • Russell A. Brewer
  • Sarah Chrestman
  • Snigdha Mukherjee
  • Karen E. Mason
  • Typhanye V. Dyer
  • Peter Gamache
  • Mary Moore
  • DeAnn Gruber
Original Paper

Abstract

We explored the correlates of linkage to HIV medical care and barriers to HIV care among PLWH in Louisiana. Of the 998 participants enrolled, 85.8% were successfully linked to HIV care within 3 months. The majority of participants were male (66.2%), African American (81.6%), and had limited education (74.4%). Approximately 22% of participants were Black gay and bisexual men. The most common reported barrier to care was lack of transportation (27.1%). Multivariable analysis revealed that compared with Black gay and bisexual men, White gay and bisexual men were significantly more likely to be linked to HIV care (adjusted prevalence ratio, aPR 1.08, 95% CI 1.02–1.13). Additionally, participants reporting moderate to high levels of stigma at intake (p < 0.05) were significantly more likely to be linked to HIV care compared with those reporting low or no stigma at enrollment. Study findings highlight the continued importance of client-centered interventions and multi-sector collaborations to link PLWH to HIV medical care.

Keywords

HIV South HIV care Barriers Stigma MSM 

Introduction

The Southern region of the United States (U.S.) is the epicenter of the HIV epidemic [1]. While approximately one-third of the U.S. population lives in the South, this region accounts for more than half of all new HIV diagnoses [2], almost half (44%) of all persons living with HIV (PLWH) [1], and the greatest number of deaths from 2011 to 2015 among persons diagnosed with HIV infection [2].

One Southern state in particular, Louisiana, experiences a high burden of HIV and AIDS [3, 4]. With more than 21,000 PLWH in the state [3, 4] Louisiana ranked 3rd highest in the nation for new HIV case rates and 2nd highest for new AIDS case rates in 2016 [3]. Its two largest cities, New Orleans and Baton Rouge, have one of the highest new HIV and AIDS case rates among cities of similar size [3, 4].

Similar to the national epidemic, African Americans and men who have sex with men (MSM), particularly Black MSM (BMSM) are disproportionately impacted by HIV and AIDS in the state [3, 4]. Representing just 32% of the state’s population, 73% of newly diagnosed HIV cases and 75% of newly diagnosed AIDS cases in 2016 were among African Americans [3]. As of September 2017, MSM accounted for almost half (47.4%) of all PLWH in the state and the majority (55.7%) of newly diagnosed HIV cases with a majority of new cases occurring among BMSM [3].

Survival rates and quality of life for PLWH have improved dramatically since the introduction of highly active antiretroviral therapy (HAART) [5, 6, 7]. Reductions in morbidity and mortality depend on timely linkage and retention in HIV care [5, 6, 7, 8]. Linking and retaining PLWH into medical care is therefore crucial for addressing the HIV epidemic in all regions of the US [9], as is associated with decreased HIV viral loads, shorter time between diagnosis and viral suppression, and a reduction in HIV transmission [10, 11, 12]. It is also critically important to prevent drop-off along the HIV care continuum from initial linkage to retention in care and eventual viral load suppression [12].

Despite advancements in HIV treatment and subsequent health benefits among PLWH [13, 14] and the community as a whole [15], as of 2015, 72% of PLWH in Louisiana were linked to HIV care (i.e., at least one CD4 or viral load test), 55% were retained in care (i.e., two or more CD4 or viral load tests at least 90 days apart), and more than half (57%) were virally suppressed (i.e., most recent viral load that was less than or equal to 200 copies/ml) [4]. A variety of factors operating at the individual, interpersonal, community, and system/structural levels are associated with poor or delayed linkage to HIV medical care [4, 12].

The Southern region, specifically the Deep South, is characterized by its perpetuation of conservative policies, vocal religious base, poorer health infrastructure, longer distances to health facilities, and lower levels of education, income, and insurance coverage than other U.S. regions; all of these factors serve as barriers to every stage of the HIV care continuum [4, 16]. There is an urgent and growing need to identify and address these barriers to HIV care in Southern states including Louisiana and expand services for PLWH in this region as described in the National HIV/AIDS Strategy (NHAS) [17].

In 2010, AIDS United launched a national Positive Charge Access to Care Initiative to improve access to HIV primary medical care; develop and evaluate different access to care models; and address the systemic and/or personal barriers to HIV care experienced by PLWH in the U.S. [12]. Louisiana was one of five sites selected and funded by AIDS United and Bristol-Myers Squibb as part of this initiative to reduce barriers to HIV care experienced by PLWH in the state [12, 18]. From April 2010 to July 2014, the Louisiana Positive Charge (LA PC) initiative was funded to enhance linkage to HIV medical care using a variety of patient-centered approaches. LA PC was led by the Louisiana Public Health Institute (LPHI) in New Orleans in collaboration with 11 multi-sector agencies (e.g., clinical providers, community-based organizations, AIDS Service organizations, correctional facility, and state public health agency) in four Louisiana cities. The goal of the LA PC was to link newly diagnosed individuals, PLWH who were out of care, or those at risk for falling out of care into HIV primary medical care. This manuscript specifically seeks to build on prior research among PLWH by: (1) exploring the recruitment of PLWH in general and MSM in the Deep South; (2) identifying the correlates of linkage to HIV medical care among PLWH in Louisiana with an emphasis on MSM who are disproportionately impacted by HIV and AIDS in the state; and (3) identifying the specific barriers to HIV care among study participants overall and MSM specifically.

Methods

Study Design and Participants

Data used for this analysis were collected from LA PC, a four-year multi-city and multi-arm intervention study conducted to link PLWH to HIV primary medical care in Louisiana. The interventions were conducted in New Orleans, Baton Rouge, Lake Charles, and Shreveport. Lakes Charles is considered an HIV care hub for its surrounding rural communities while the other cities are urban sites. LA PC consisted of a set of brief client-centered interventions to link eligible participants to HIV medical care. Once clients were linked to medical care, the interventionists transitioned clients to long-term case management. The Louisiana Department of Health’s Institutional Review Board (IRB) reviewed and approved the study.

Eligible participants were enrolled into one of six client-centered interventions based on their city of residence or residence intent: (1) linkage case management, (2) peer health navigation, (3) near peer health navigation, (4) health navigation plus treatment adherence, (5) pre/post release case management, and (6) support from a disease intervention specialist. Clients received services regardless of whether or not they enrolled and provided consent to participate in LA PC. The client-centered interventions are summarized in Table 1.
Table 1

Description of client-centered interventions and target populations

Client-centered intervention

Definition

City

FTEs

Target population(s)

Peer health navigation

Assistance with navigating health care system as well as referrals to supportive services provided by peer living with HIV infection

Baton Rouge

1.0

Out of care clinic population, new diagnoses

Near peer health navigation

Assistance with navigating health care system and referrals to supportive services provided by near peer with similar social economic background, history of accessing medical care and supportive services

New Orleans

1.0

Out of care clinic population, new diagnoses

Health navigation + treatment adherence (i.e., enhanced health navigation)

Assistance with navigating health care system to be linked to care and assistance with maintaining treatment regimens

Lake Charles

1.0

1.0

Out of care clinic population

Pre/post-release case management

Identification of PLWH in parish jail and follow-up after release for linkage to care

New Orleans

0.3

Incarcerated individuals living with HIV infection being released from local jail

Linkage case management

Intensive case management for up to 90 days using a strengths-based model

Baton Rouge

1.0

Primarily new diagnoses

Disease intervention specialist

State run public health program to locate and counsel PLWH in order to link them to care

New Orleans & Shreveport

0.66

0.23

Out of care clinic population (i.e., PLWH who have fallen out of care and individuals previously diagnosed who never accessed care) and new diagnoses in parish health units

Peer or Near Peer Navigation

The peer (i.e., person living with HIV infection) or near peer (i.e., person with similar socio-economic background, history of accessing medical care and social services) health navigation models were implemented in New Orleans and Baton Rouge. The peer navigator was housed at two locations (i.e., community-based organization and safety net medical provider) while the near peer navigator was housed at a safety net medical provider. Modeled after evidenced-based health navigation interventions [19], the peer or near peer navigators linked clients living with HIV into primary medical care by helping clients navigate the health care system (e.g., appointment reminders and accompanying clients to appointments), in addition to providing referrals to community services (e.g., housing, substance use treatment). Health navigation has been shown to reduce barriers to HIV care and enhance linkage and engagement in HIV primary care [19].

Health Navigation Plus Treatment Adherence (i.e., Enhanced Health Navigation)

This intervention was provided by two staff members (i.e., a health navigator and treatment adherence specialist) at an AIDS Service Organization in Lake Charles, LA. The health navigator provided similar supportive functions as a peer or near peer navigator described above and the treatment adherence specialist provided education about medications and needed support to enhance HIV treatment adherence.

Pre/Post Release Case Management

The pre/post release case manager worked with jail medical staff to identify PLWH in a local jail and followed up with clients upon release in order to link them into HIV medical care. This intervention was implemented by an AIDS Service Organization in New Orleans.

Linkage Case Management

A linkage case manager housed at a community-based organization worked with newly diagnosed individuals to link them into HIV primary medical care by providing intensive case management services for up to 90 days based on a strengths-based case management model that supports and enhances the inherent strengths and skills of each client. This brief case management intervention was based on the Antiretroviral Treatment Access Study (ARTAS)-II study which demonstrated that brief case management is an effective model to ensure that individuals newly diagnosed with HIV infection are linked to HIV care within a reasonable period of time [20, 21]. This intervention was only implemented in Baton Rouge.

Disease Intervention Specialist (DIS)

In Louisiana DIS fulfill the standard public health functions of conducting field investigations of communicable diseases to locate and counsel persons exposed to, living with, or who are diagnosed with HIV and other sexually transmitted infections. Through LA PC, DIS also connected individuals who were newly diagnosed with HIV at the parish (county) public health clinics and those previously diagnosed with HIV who never accessed or had dropped out of care to HIV medical care. The DIS interventions were implemented in New Orleans and Shreveport.

From July 2010 to March 2014, eligible PLWH in the four cities who agreed to participate were enrolled in the evaluation study upon IRB approval. Participants were recruited via a variety of strategies. All sites recruited from existing or new clients at their agency, as well as referrals from outside agencies. One site specifically recruited from a jail setting. Two sites also recruited from clinic-generated lists of patients who were considered out of care. Potential participants were invited to enroll in the study in person or over the telephone. To be eligible for LA PC, clients needed to: (1) reside or intend to reside in one of the study cities or nearby communities (i.e., New Orleans, Baton Rouge, Lake Charles, and Shreveport); (2) be newly diagnosed with HIV infection or currently living with HIV infection and meet one of the following conditions—(a) considered to be out of care, (b) in sub-optimal care, or (c) in tenuous care. Out of care was defined as failing to have two medical visits at least 2 months apart within the past 12 months [22]. Sub-optimal care was defined as failing to have at least two medical visits at least 2 months apart within the past 6 months. A client was considered in tenuous care if he/she received medical care at the time of enrollment, but was at risk of falling out of medical care as a result of housing instability, incarceration history, unemployment, and previous history of falling out of care. The out of care, sub-optimal, and tenuous care categories were pre-defined by the funder (i.e., AIDS United) and national evaluator (i.e., Johns Hopkins University) for this initiative. The national evaluation strategies have been described elsewhere [23].

At the enrollment visit, eligibility was confirmed and written informed consent was obtained by the interventionist (e.g., peer navigator). Clients completed an initial face-to-face intake questionnaire which assessed demographic and psychosocial characteristics (i.e., quality of life and stigma), needs, most urgent needs, barriers to care, and greatest barriers to care. Each interventionist administered a paper-based questionnaire and recorded (i.e., wrote in or circled) participant responses on the questionnaire. Interviews were conducted in a private room at the intervention sites. A small number of clients completed the questionnaire after providing verbal consent over the telephone; in this situation, interventionists called potential participants from a private room and asked participants to respond to the questions in a private area where they felt comfortable. Clients received a gift card for their time to complete the intake questionnaire. A brief follow-up questionnaire was also administered after participants attended a medical appointment with a provider (i.e., HIV/infectious disease physician) with prescribing privileges. Participants received a second gift card for their time to complete the follow-up questionnaire once they had attended a medical appointment. The completion of the follow-up questionnaire typically occurred between 2 to 6 months after enrollment due to the length of time it took clients to receive HIV medical care.

Upon completion of the initial intake, the interventionists entered participant information into CAREWare, a secure database commonly used by Ryan White providers that was customized by the Louisiana State Department of Health, Office of Public Health STD/HIV Program (OPH SHP) to capture client-level data for the evaluation study. Unique identifiers created in CAREWare were later matched with surveillance data from OPH SHP to confirm linkage to care by the presence of a CD4 or viral load result over a period of 18 months, which were pre-defined by the national evaluators for the Positive Charge Access to Care Initiative.

Study Measures

Outcome Variable

Linkage to HIV Care A participant was considered linked to care if he/she had a medical visit with a provider with prescribing privileges that was verified by the interventionists and later matched with the participant’s HIV laboratory results (CD4 and/or HIV viral load) in the state health department’s HIV surveillance system within 18 months of enrollment. This 18-month parameter was pre-determined by the funder and national evaluator for all funded sites. Given the 2010 National HIV/AIDS Strategy (NHAS) federal guidelines for linkage to HIV care in 3 months [24], linkage to HIV medical care was also determined at 3, 4–6, and 7 to 18 months post-enrollment for purposes of this analysis.

Psychosocial Variables

Quality of Life Quality of life was assessed by asking participants to rate their general health as “excellent,” “very good,” “good,” “fair,” or “poor” [25, 26]. Response options for “refused to answer” and “don’t know” were not read aloud to the client. For analysis purposes, categories were grouped into a 0/1 variable comparing “fair” or “poor” with “excellent,” “very good” or “good.”

Stigma HIV stigma was measured using a perceived stigma distancing scale [27]. Clients were read four statements and asked to rate how often it occurred using the scale “not at all,” “rarely,” “sometimes,” and “often.” A stigma score was calculated using four stigma indicators that measure how often a person felt that people avoid them because they have HIV, feared they would lose friends because of HIV, thought people were uncomfortable being with them because of HIV, and avoided obtaining treatment because someone might find out about their HIV. For all four stigma questions, the responses “sometimes” or “often” were assigned one point and “not at all” or “rarely” were assigned zero points. These responses were summed and divided by 4 for a final mean score used in the analysis.

Barriers and Needs Variables

Needs The assessment of client needs included exploratory questions adapted from research conducted by The Measurement Group, Missouri Department of Health and Senior Services, and the New York State Department of Health AIDS Institute. The interventionists read a list of 8 services to the client (e.g., housing or shelter, food, dental services), and clients were asked to indicate which ones he/she currently needed. A needs score was calculated using the total sum of needs that respondents reported. Those who did not report any needs were categorized as having no needs, those between one and four needs were categorized as having “some needs” and those reporting five to eight needs were categorized as having “many needs.” Participants were subsequently asked about their most urgent need and were instructed to select only one need. This variable was used to create a collapsed “urgent needs” measure. The measure included barriers in the following categories: No urgent needs; drugs and alcohol treatment; food, housing, transportation and other competing needs; and medical services.

Barriers to Care The assessment of barriers to care was also adapted from research conducted by The Measurement Group, the Missouri Department of Health and Senior Services, and the New York State Department of Health AIDS Institute. Clients were asked, “What makes it hard for you to get care?” As clients responded, the interventionist coded each participants’ responses based upon pre-set options on the intake survey. Barriers reported were not mutually exclusive as participants could select more than one. A barriers score was calculated by adding the total number of barriers identified. This was further recoded to 0, or “no barriers” identified; and 1, “one or more” were reported. “Don’t know” and “refused” were set to missing. Common barriers to care were explored by: (a) all study participants, (b) by residence, and (c) by racial/ethnic differences among MSM. Participants were subsequently asked about their greatest barrier and were instructed to select only one barrier. This variable was used to create a collapsed “greatest barriers” measure. The measure included barriers in the following categories: No barriers, financial, competing needs, psychosocial, and structural barriers.

Demographic Variables

The demographic characteristics assessed included race, age at enrollment, gender identity (male, female or transgender), sexual orientation (heterosexual/straight, gay/bisexual, lesbian, or other category), education level, and time since first seropositive test (< 1 year defined as new diagnosis). A combined sexual orientation by race/ethnicity and gender variable was created based on each participant’s self-reported sexual orientation, race/ethnicity, and gender.

Statistical Analyses

For our analyses, we used STATA SE 12.0 software [28] for descriptive statistics and survey commands in STATA for complex analyses. Descriptive statistics, including frequencies, percentages, means, and standard deviations were calculated for the entire sample of enrolled participants. We conducted bivariate analyses using T-tests (for continuous variables) and Chi square (χ2) tests (for categorical variables) to test the association between linkage to care (outcome variable) and the specific independent variables (i.e., demographic, psychosocial, needs, and barriers). Measures significant in the bivariate analyses (p ≤ 0.05) were included in the multivariable analyses. We examined multivariable relationships using a generalized linear model for binomial outcomes, with log link, Poisson distribution without an offset, and a robust variance estimator. We estimated unadjusted and adjusted prevalence ratios (aPR) and 95% confidence intervals for the associations between the combined race/ethnicity, sexual orientation, and gender variable; stigma; and linkage to care. Adjusted models were controlled for age, city of enrollment, new diagnosis, most urgent needs, and greatest barriers at intake. We included enrollment city and not intervention type in the final analyses to adjust for city differences, as the two were dependent upon one another. The referent group for the multivariate analyses was Black gay and bisexual men. As 17% of the sample was missing the combination variable, due mainly to sexual orientation, missing values were imputed as follows: the missing cases were randomly allocated to a group based on the percentage in that race/ethnicity and gender combination from non-missing cases (race/ethnicity was only missing 3% and gender had no missing values). For example, of those who were Black and male, 40% were gay/bisexual and 60% were heterosexual. Thus, 40% of the Black males were randomly assigned to gay/bisexual and 60% to heterosexual. This was repeated for other race and gender groups. Note that for each outcome there are different sample sizes due to missing data. Additional sub-analyses were also conducted to explore MSM participation in the study.

Results

The study successfully enrolled 998 participants as previously cited [18]. Table 2 describes the characteristics of participants at enrollment. The percentage of participants by intervention type ranged from 10.8% in the linkage case management intervention to 21.5% in the enhanced health navigation intervention. More than 75% of enrolled participants met the out of care definition. Close to half (43.9%) of all participants were enrolled in New Orleans. The greatest percentage (42%) of newly diagnosed participants also resided in New Orleans. The majority of participants identified as male (66.2%) and Black (81.6%). The mean age at enrollment was 36 years (σ = 11.4). More than two-thirds of the sample had a high school education or less. Black heterosexual men (BHM) comprised 30.8% of enrolled participants, followed by Black heterosexual females (BHF) (24.0%), Black gay and bisexual men (21.9%), White gay and bisexual men (6.6%), and White heterosexual men (1.3%). Most participants (62.4%) reported a high quality of life (i.e., good, very good or excellent). The majority of participants were diagnosed more than a year prior to participation in the study (58%). The mean number of needs at intake was 3 (σ = 2.0) and mean reported barriers to care at intake was close to 2.0 (σ = 1.6). On a scale of 0 to 4 with 0 being no stigma to 4 being often stigmatized, the mean response for the sample was 1.11 ± 1.29. Overall, 918 (92%) of all participants were linked to HIV care within 18 months. Eight hundred and fifty-six (856) participants were linked to medical care within 3 months of enrollment (85.8%), 33 participants (3.3%) were linked within 4–6 months, and the remaining 29 participants (2.9%) were linked to care within 7–18 months. The linkage to care results were not reported in Table 2.
Table 2

Positive charge study and participant characteristics at baseline (N = 998)

Study characteristics

# (%)

Intervention type

 Peer health navigation

135 (13.5)

 Near peer health navigation

187 (18.7)

 Enhanced health navigation

215 (21.5)

 Pre/post release case management

160 (16.0)

 Linkage case management

108 (10.8)

 Disease intervention specialist

193 (19.3)

Care status at intake

 Out of care

762 (76.4)

 Sub-optimal care

146 (14.6)

 Tenuous care

90 (9)

City of enrollment

 New Orleans

438 (43.9)

 Baton Rouge

248 (24.8)

 Lake Charles

215 (21.5)

 Shreveport

92 (9.2)

 Missing

5 (0.5)

New diagnoses by city

 New Orleans

174 (42)

 Baton Rouge

78 (18.9)

 Lake Charles

78 (18.9)

 Shreveport

78 (18.9)

 Unknown

5 (1.2)

Gender identity

 Male

661 (66.2)

 Female

306 (30.7)

 Transgender

31 (3.1)

Race/ethnicity

 Black

814 (81.6)

 White

122 (12.2)

 Hispanic/Latino

21 (2.1)

 Other

11 (1.1)

 Missing

30 (3.0)

Age

 Mean age at intake (SD)

36.1 (11.4)

Education

 High school or less

743 (74.4)

 More than high school

230 (23.0)

 Missing

25 (2.5)

Race/ethnicity, sexual orientation, and gender (only groups with 50 or more participants included in table)

 Black gay and bisexual men

219 (21.9)

 Black heterosexual men (BHM)

307 (30.8)

 Black heterosexual females (BHF)

240 (24.0)

 White gay and bisexual men

66 (6.6)

 Missing

171 (17.13)

Quality of life

 Fair or poor

257 (25.8)

 Good, very good, good

623 (62.4)

 Missing

118 (11.8)

Time since first seropositive test

 < 1 year

413 (41.6)

 ≥ 1 year

579 (58.4)

 Missing

6 (0.6)

Mean # needs at enrollment (SD)

3.2 (2.0)

Mean # barriers at enrollment (SD)

1.9 (1.6)

Mean stigma score at enrollment (SD)

1.11 ± 1.29 (n = 978, missing 2.0%)

Descriptive analyses described in Table 3 revealed that the most common barriers to care for study participants were lack of transportation (27.1%), financial resources (20.9%), competing priorities (13.9%), fear (14.3%), and incarceration history (9.52%). Barriers by city and the combined race/ethnicity, sexual orientation, and gender variable (i.e., Black and White gay and bisexual men) were also explored and described in Table 3. In New Orleans and Baton Rouge, the top reported barriers to care for study participants at enrollment was lack of transportation. In Lake Charles, the most frequent barrier was financial resources while fear topped the list of barriers in Shreveport. The most frequently reported barrier to care at enrollment for White gay and bisexual men was financial resources and transportation for Black gay and bisexual men.
Table 3

Self-reported barriers of participants enrolled in LA PC

Self-reported barriers

# (%)

Most frequent barriers (all participants)

 Transportation

270 (27.1)

 Money

209 (20.9)

 Competing priorities

139 (13.9)

 Fear

143 (14.3)

 Incarceration

95 (9.52)

Most frequent barriers by city

 New Orleans

 

  Transportation

91 (20.8)

  Competing priorities

85 (19.4)

  Incarceration

75 (17.1)

 Baton Rouge

  Transportation

86 (34.7)

  Money

31 (12.5)

  Competing priorities

45 (18.1)

 Lake Charles

  Transportation

69 (32.1)

  Money

99 (46.0)

  Fear

43 (20.0)

 Shreveport

  Fear

39 (42.4)

  Stigma

34 (37.0)

  Denial

27 (29.3)

Most frequent barriers for white gay and bisexual men

 Transportation

17 (25.8)

 Money

23 (34.8)

 Competing priorities

9 (13.6)

 Fear

12 (18.2)

 Location of care

9 (13.6)

Most frequent barriers for black gay and bisexual men

 Transportation

50 (22.8)

 Money

47 (21.5)

 Competing priorities

28 (12.8)

 Fear

38 (17.4)

 Othera

43 (19.6)

aMany varied reasons listed

Bivariate analyses were used to compare participants who were linked to care vs. those who were not linked to care within an 18-month period of time. We found a significant association for linkage to care by enrollment city (p = 0.000) and intervention type (p = 0.000) (Table 4). Almost all participants were linked to care in Lake Charles (99.1%), followed by Baton Rouge (91.9%), New Orleans (90.0%), and Shreveport (85.9%). Almost all participants in the enhanced health navigation were linked to care (99.1%) followed by those participating in the near peer health navigation (97.9%), peer health navigation (93.3%), linkage case management (91.7%), DIS (86.0%), and finally the pre/post release case management (81.9%). Participants who had been living with HIV for more than a year were more likely to be linked to care compared with those who were newly diagnosed (p = 0.000). All tenuous care participants were linked to HIV care (100%, p = 0.000), followed by those who met the criteria for sub-optimal care (97.3%) and out of care (90%) at enrollment. There was also a significant association between the combined variable (i.e., race/ethnicity, sexual orientation, and gender) and linkage to care (p = 0.006). Almost all White gay and bisexual male participants were linked to HIV care (98.5%) followed by BHF (96.4%), BHM (89.9%), and Black gay and bisexual men (89.4%). Participants who were linked to care tended to be slightly older than those who were not linked to care (36.3 [σ = 11.3] vs. 33.5 [σ = 11.5], p = 0.036). There was a statistically significant association between most urgent needs (p = 0.036) and greatest barriers (p = 0.000) at intake and linkage to HIV care. All participants reporting drug and alcohol treatment as an urgent need were linked to HIV care. Almost all participants (98.4%) reporting a psychosocial factor (i.e., drug use, fear, stigma, denial, distrust) or no identified challenges (97.5%) as greatest barriers at intake were linked to HIV care. Participants who were linked to care also tended to report slightly greater stigma at intake than those who were not linked to care (1.14, ± 1.30 vs. 0.79, ± 1.19, p = 0.016). There was not a statistically significant association between those who were linked to care vs. not linked to care based on gender identity (p = 0.076), race/ethnicity (p = 0.439), education (p = 0.664), quality of life (p = 0.077), reported mean needs at intake (p = 0.361), and reported mean barriers at intake (p = 0.15).
Table 4

Associations between study characteristics and linkage to care at intake

Characteristics

Linked to care (N = 918) # (%)

NOT linked to care (N = 80) # (%)

Test statistic (p value)

City of enrollment

  

χ2 = 21.98 (p = 0.000)

 New Orleans

394 (90.0)

44 (10.0)

 

 Baton Rouge

228 (91.9)

20 (8.1)

 

 Lake Charles

213 (99.1)

2 (0.9)

 

 Shreveport

79 (85.9)

13 (14.1)

 

Intervention

  

χ2 = 55.26 (p = 0.000)

 Peer health navigation

126 (93.3)

9 (6.7)

 

 Near peer health navigation

183 (97.9)

4 (2.1)

 

 Enhanced health navigation

213 (99.1)

2 (0.9)

 

 Pre/post-release case management

131 (81.9)

29 (18.1)

 

 Linkage case management

99 (91.7)

9 (8.3)

 

 Disease intervention specialist

166 (86.0)

27 (14.0)

 

New diagnosis

  

χ2 = 25.43 (p = 0.000)

 Yes

105 (80.8)

25 (19.2)

 

 No

812 (93.7)

55 (6.3)

 

Care status at intake

  

χ2 = 17.32 (p = 0.000)

 Out of care

686 (90.0)

76 (10.0)

 

 Sub-optimal care

142 (97.3)

4 (2.7)

 

 Tenuous care

90 (100.0)

0 (0)

 

Gender Identity

  

χ2 = 5.14 (p = 0.076)

 Male

599 (90.6)

62 (9.4)

 

 Female

289 (94.4)

17 (5.6)

 

 Transgender

30 (96.8)

1 (3.2)

 

Race

  

χ2 = 2.71 (p = 0.439)

 Black

748 (91.9)

66 (8.1)

 

 White

116 (95.1)

6 (4.9)

 

 Hispanic/Latino

20 (95.2)

1 (4.8)

 

 Other

11 (100)

0 (0)

 

 Missing

23 (76.7)

7 (23.3)

 

Race/ethnicity, sexual orientation, and gendera

  

χ2 = 12.47 (p = 0.006)

 Black gay and bisexual men

152 (89.4)

18 (10.6)

 

 BHM

228 (89.8)

26 (10.2)

 

 BHF

186 (96.4)

7 (3.6)

 

 White gay and bisexual men

65 (98.5)

1 (1.5)

 

Ageb

  

t = − 2.97 (p = 0.036)

 Age at intake (mean (SD))

36.3 (11.3)

33.5 (11.5)

 

Education

  

χ2 = 0.19 (p = 0.664)

 High school or less

685 (92.2)

58 (7.8)

 

 Greater than high school

210 (91.3)

20 (8.7)

 

 Missing

23 (92.0)

2 (8.0)

 

Quality of life

  

χ2 = 3.11 (p = 0.077)

 Fair or poor

244 (94.9)

13 (5.1)

 

 Good, very good, excellent

570 (91.5)

53 (8.5)

 

 Missing

104 (88.1)

14 (11.9)

 

Needs at intake

  

t = − 0.91(p = 0.361)

 Mean (SD)

3.2 (2.0)

3.0 (2.1)

 

Most urgent need at intake

  

χ2 = 10.29 (p = 0.036)

 None

51 (91.1)

5 (8.9)

 

 Drug and alcohol treatment

21 (100)

0 (0)

 

 Food, housing, transportation and other competing needs

164 (94.3)

10 (5.7)

 

 Medical services

604 (91.7)

55 (8.3)

 

Barriers at intake

  

t = − 1.43 (p = 0.15)

 Mean (SD)

1.9 (1.7)

1.6 (1.1)

 

Greatest barriers at intake

  

χ2 = 43.87 (p = 0.000)

 No barriers identified

153 (97.5)

4 (2.56)

 

 Financial (i.e., money)

60 (89.6)

7 (10.5)

 

 Competing needs

70 (87.7)

8 (10.3)

 

 Psychosocial (i.e., drug use, fear, stigma, denial, distrust)

122 (98.4)

2 (1.6)

 

 Structural (i.e., transportation, structure of testing, housing, jail)

259 (94.9)

14 (5.1)

 

 New HIV diagnosis

91 (79.8)

23 (20.2)

 

Stigmab

   

 Stigma is sometimes or often (mean + SD)

1.14 + 1.30 (n = 902)

0.79 + 1.19 (n = 76)

t = − 2.47, 0.016

Missing values and ‘Refuse to answer’ were excluded from statistical tests

aNot all groups shown and Hispanic not included in analyses due to small sample size

bValues for all variables were calculated with a Chi square test, except for age and stigma, which were measured using a T-test

The multivariable logistic regression analyses (Table 5) showed that White gay or bisexual men had an 8% greater odds of being linked to care compared to Black gay or bisexual men (aPR 1.08, 95% CI 1.02–1.13). The multivariable logistic regression analyses also showed that participants reporting moderate to high stigma at intake were significantly more likely to be linked to HIV care (p < 0.05) compared with those reporting low or no stigma at enrollment after controlling for age, city, new diagnosis, care status, most urgent needs, and greatest barriers at intake. There were no statistically significant relationships between the combined variable (i.e., race/ethnicity, sexual orientation, and gender) and linkage to HIV care after controlling for age, city, new diagnosis, care status, most urgent needs, and greatest barriers at intake.
Table 5

Unadjusted and adjusted regressions modeling the probability of being linked to care

Race/ethnicity, sexual orientation, and gender

N

%

UPR (95% CI)

APR (95% CI)

Black gay and bisexual men

152

40

Ref.

Ref.

BHM

228

60

1.00 (0.94–1.07)

0.95 (0.87–1.04)

Black gay and bisexual men

152

45

Ref.

Ref.

BHF

186

55

1.07 (1.02–1.14)

1.04 (0.98–1.10)

Black gay and bisexual men

152

70

Ref.

Ref.

White gay and bisexual men

65

30

1.10 (1.04–1.17)

1.08 (1.02–1.13)

Black gay and bisexual men

152

92

Ref.

Ref.

White heterosexual men

13

8

0.97 (0.79–1.19)

0.97 (0.90–1.04)

Black MSM

152

86

Ref.

Ref.

WHF

25

14

1.07 (0.98–1.18)

1.01 (0.94–1.07)

Black gay and bisexual men

152

76.4

Ref.

Ref.

Othera

47

23.6

1.01 (0.91–1.12)

1.02 (0.90–1.16)

# Times stigma reported bad as often or alwaysb

N/A

N/A

0.221

p < 0.05

All adjusted models controlled for age, city, new diagnosis, care status, urgent needs, and greatest barriers at intake

N for a given outcome may not sum to the sample total due to missing values

UPR unadjusted prevalence ratios, APR adjusted prevalence ratios

aIncludes small groups as follows: females–gay/bi, transgender male to female, Hispanic or other race

bStigma is a continuous variable, therefore the estimate is a beta coefficient and corresponding p-value

Additional sub-analyses conducted to explore the participation of MSM in the study (results not included in tables) showed that close to half of all Black gay and bisexual male participants were recruited from New Orleans (42%), followed by Baton Rouge (25.1%), Lake Charles (18.7%), and Shreveport (13.2%). The majority of White gay and bisexual men were enrolled (62.1%) in Lake Charles. Almost one-third (29.2%) of Black gay and bisexual men were enrolled in the DIS intervention, while the majority (62.1%) of White gay and bisexual men were enrolled in the enhanced health navigation intervention.

Discussion

The goal of this study was not to compare and contrast the different client-centered interventions but rather to explore the feasibility of recruiting PLWH in Louisiana. The results of this study reveal a profile of a large sample of PLWH in a southern state with a high incidence and prevalence of HIV and AIDS that can be used to inform the development of state and city HIV care and prevention efforts. The overall societal cost ($341,668) and cost-effectiveness of the LA PC has been described elsewhere [29]. Overall, the common demographic profile of a participant enrolled in this study was an African American male with limited education living with HIV infection who was not in HIV care at the time of enrollment.

The Recruitment of PLWH in General and MSM in the Deep South

The observed results provide support that it was feasible to recruit PLWH to receive one of six client-centered linkage to care interventions in Louisiana. With minimal financial investment in recruitment strategies, the six interventions were able to successfully enroll close to 1000 individuals living with HIV infection over 3 years and 9 months. Most of the interventionists involved in the LA PC were able to use agency generated out-of-care lists to re-engage clients into care. The study also enrolled a fairly large sample of Black gay and bisexual men living with HIV infection (21.9%) in Louisiana, even though specific enrollment targets for MSM were not pre-determined. Given the high enrollment of MSM, the investigators were able to conduct additional sub-analyses among MSM. The observed 17% of missing responses for sexual orientation may indicate that the actual MSM category may be underrepresented. Sexual minority participants may have been reluctant to report their sexual orientation, which points to the impact of stigma associated with sexual orientation in the state.

The Correlates of Linkage to HIV Medical Care Among PLWH and MSM

The six client-centered interventions conducted under LA PC were also able to successfully link 85.8% of participants to HIV medical care within 3 months, which is aligned with the National HIV/AIDS Strategy access to care goal for 2015 [24]. Over an 18-month data collection period, 918 (92%) of participants were linked to HIV medical care. The study’s overall linkage to care result is also higher than the state’s linkage to care estimate of 72% [4]. It was not surprising that the pre/post release case management intervention had the highest percentage of participants (18%) who were not linked to care compared with the other five interventions given that former prisoners living with HIV infection experience additional co-occurring barriers to HIV care (e.g., stigma associated with incarceration history, inability to find a job as a result of incarceration history, substance use relapse, and contact with drug-using social network), which has been shown to affect overall linkage to care rates for this population [30, 31].

White gay or bisexual men reported significantly greater odds of being linked to care compared to Black gay or bisexual men, which is consistent with the current literature on racial/ethnic disparities in the HIV care continuum among MSM. These studies, as well as ours highlight the importance of developing culturally tailored and structural interventions in order to promote linkage to HIV care [32, 33, 34, 35]. Participants in the study reporting moderate to high levels of stigma at intake were also more likely to be linked to care. This is an interesting finding and counter to the current literature that suggests that stigma is a deterrent to accessing HIV care [36, 37]. This finding may indicate the resilience of this group of participants living with HIV infection and/or that the client-centered interventions were responsive to client needs and played an important role in reducing HIV stigma. The impact of client-centered interventions on stigma and discrimination warrants additional investigation given NHAS’ call to eliminate stigma and discrimination, known barriers to HIV care [18].

There is certainly a need for client-centered interventions in the state to move PLWH across the HIV care continuum given the high number of participants who were eligible for and enrolled in the study. The current study provides an example of how multi-sector agencies (e.g., clinical providers, community-based organizations, AIDS Service organizations, correctional facilities, and governmental public health agencies) were engaged in supporting the needs of PLWH and addressing barriers to HIV care. It is not surprising that more than two-thirds (68.7%) of participants were enrolled in New Orleans and Baton Rouge given the greatest percentage of individuals living with HIV infection in Louisiana reside in these two cities [3, 4].

The Specific Barriers to HIV Care Among Study Participants and MSM

The barriers analyses showed that transportation and financial resources served as common barriers to care for all participants. The most frequently reported barrier to care at enrollment for White gay and bisexual men was financial resources and transportation for Black gay and bisexual men. With the 2016 expansion of Medicaid in Louisiana [38], the impact of financial resources on access to care will certainly benefit PLWH including MSM.

Study Limitations

In terms of limitations, the current study did not examine the universe of variables that may be associated with linkage to care (e.g., clinic distance, incarceration history, social support, health provider communication and experiences, etc.). However, incarceration history was listed among the most frequent five barriers among all participants. Our analysis did not examine the correlates of retention in HIV care since the primary goal of the parent project was focused on linkage to HIV care in Louisiana. Future analysis could explore longitudinal changes in barriers to HIV care as a result of the client-centered interventions and their associations with retention in HIV care. Study findings are not generalizable to all PLWH given that a convenience sample of PLWH were enrolled from local HIV service providers. The results should also be interpreted with caution since the majority of participants were linked to HIV care. Missing data also limit the reliability and generalizability of the data. The accumulation of missing data resulted in a final multivariate sample of 707, or 71% of the original 998 participants. The stigma scale was also limited to questions about perceptions of the general population and did not include specific questions related to service providers. In retrospect, it may have been useful to assess whether participants were or were not receiving Ryan White Services (RWS) to compare the relationship between transportation and access to care, since RWS can support transportation in certain instances.

Conclusion

In conclusion the current study represents a large sample of PLWH in Louisiana who were successfully linked to HIV care using a variety of client-centered interventions (e.g., case management, navigators, etc.). Our study contributes to the HIV care continuum literature on the experiences of PLWH in the Deep South and among MSM. It is well-aligned with the NHAS’ goals to reduce new HIV infections, improve access to care, and reduce HIV-disparities and health inequities. Furthermore, it underscores the importance of multi-sector coordination and collaboration in order to achieve successful HIV care outcomes for PLWH in Louisiana.

Notes

Acknowledgements

We would like to thank all study participants; Susan Bergson, MPH; the interventionists; the intervention sites; and our collaborative partners in Louisiana. This project was supported by a grant from AIDS United.

Author Contributions

RAB generated the initial concept, reviewed the analysis results, drafted specific sections of the article, updated subsequent drafts, and completed the final version for publication. SC, SM, PG, and DG also helped design the initial concept, reviewed the analysis results, and drafted specific sections of the article. KEM ran the analyses, reviewed the analysis results, and drafted the results section. TVD and MM re-coded the data, re-ran the analyses, reviewed the analysis results, and contributed to revising all sections of the manuscript. In addition, RAB and DG served as co-investigators of the study.

Funding

This project was funded by AIDS United and Bristol-Myers Squibb. R.A. Brewer’s time was also supported by a Grant from NIMH (R25MH067127) for the Visiting Professor Program at the University of California, San Francisco.

Compliance with Ethical Standards

Ethical Approval

Ethical approval for this analysis was obtained from The Louisiana Department of Health’s Institutional Review Board (IRB) in accordance with the 1964 Helsinki declaration and its later amendments or comparable ethical standards. Informed consent was obtained from all individual participants included in the study. All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards. Institutional Review Board approval was obtained for the study.

Conflict of interest

The authors have no conflicts of interest.

Informed Consent

Informed consent was obtained from all interviewed participants in the study.

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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Department of MedicineUniversity of ChicagoChicagoUSA
  2. 2.Louisiana Public Health InstituteNew OrleansUSA
  3. 3.Foundation for Advancement of International Medical Education and ResearchPhiladelphiaUSA
  4. 4.Department of Epidemiology and BiostatisticsThe University of MarylandCollege ParkUSA
  5. 5.Turnaround Achievement Network, LLCTampaUSA
  6. 6.Dillard UniversityNew OrleansUSA
  7. 7.Louisiana Office of Public Health, STD/HIV ProgramNew OrleansUSA

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