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Case Management Is Associated with Improved Antiretroviral Adherence and CD4+ Cell Counts in Homeless and Marginally Housed Individuals with HIV Infection

  1. M. B. Kushel1,
  2. G. Colfax4,
  3. K. Ragland2,
  4. A. Heineman2,
  5. H. Palacio4, and
  6. D. R. Bangsberg3
  1. 1Division of General Internal Medicine, San Francisco
  2. 2Department of Epidemiology and Biostatistics, San Francisco
  3. 3Epidemiology and Prevention Interventions Center, Division of Infectious Diseases and The Positive Health Program, San Francisco General Hospital Medical Center, University of California, San Francisco
  4. 4Epidemiology and Intervention Research Section, AIDS Office, San Francisco Department of Public Health, San Francisco, California; and 5Harris Public Health and Environmental Services, Houston, Texas
  1. Reprints or correspondence: Dr. David Bangsberg, Epidemiology and Prevention Interventions Center, San Francisco General Hospital, POB 1372 UCSF, San Francisco, CA 94143-1372 (db{at}epi-center.ucsf.edu).
 
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Abstract

Background. Case management (CM) coordinates care for persons with complex health care needs. It is not known whether CM is effective at improving biological outcomes among homeless and marginally housed persons with human immunodeficiency virus (HIV) infection. Our goal was to determine whether CM is associated with reduced acute medical care use and improved biological outcomes in homeless and marginally housed persons with HIV infection.

Methods. We conducted a prospective observational cohort study in a probability-based community sample of HIV-infected homeless and marginally housed adults in San Francisco, California. The primary independent variable was CM, defined as none or rare (any CM in ⩽25% of quarters in the study), moderate (>25% but ⩽75%), or consistent (>75%). The dependent variables were 3 self-reported health service use measures (receipt of primary care, emergency department visits and hospitalizations, and antiretroviral therapy adherence) and 2 biological measures (increase in CD4+ cell count of ⩾50% and geometric mean HIV load of ⩽400 copies/mL).

Results. In multivariate models, CM was not associated with increased primary care, emergency department use, or hospitalization. Moderate CM, compared with no or rare CM, was associated with an adjusted β coefficient of 0.13 (95% confidence interval [CI], 0.02–0.25) for improved antiretroviral adherence. Consistent CM (adjusted odds ratio [AOR], 10.7; 95% CI, 2.3–49.6) and moderate CM (AOR, 6.5; 95% CI, 1.3–33.0) were both associated with ⩾50% improvements in CD4+ cell count. CM was not associated with geometric HIV load <400 copies/mL when antiretroviral therapy adherence was included in the model. Study limitations include a lack of randomization.

Conclusion. CM may be a successful method to improve adherence to antiretroviral therapy and biological outcomes among HIV-infected homeless and marginally housed adults.

Case management (CM) seeks to coordinate medical care for individuals with complex medical problems [1–4]. For HIV-infected patients, CM manages complex medication regimens, coordinates primary medical care, and assists with referrals to housing, mental health, and substance abuse services [1–4]. HIV-infected people living in poverty are disproportionately affected by unstable housing, substance abuse, and mental illness [1–8]. These factors contribute to low rates of receipt of ambulatory health care and uptake of antiretroviral therapy [9, 10] and high rates of emergency department use and hospitalization [6, 11].

Most HIV CM is funded through the Ryan White Comprehensive AIDS Resources Emergency (CARE) Act of 1990. This program provides grants to states and municipalities to promote access to health care for HIV-infected persons living in poverty. In 2002, a total of 332,377 individuals received a total of 3,689,838 CM visits funded by the Ryan White CARE Act [12].

Cross-sectional studies of CM in the general HIV-infected population found that CM was associated with decreased reports of unmet needs and higher use of multidrug antiretroviral therapy (ART) regimens [4, 13]. Those studies did not find an association with use of primary care and did not assess biological outcomes. A randomized, controlled study of a brief CM intervention among persons with newly diagnosed cases of HIV infection found that CM was associated with uptake and with use of HIV primary care services [14].

In this study, we examined CM in a community-based sample of low-income, HIV-infected individuals. We hypothesized that CM is associated with antiretroviral use and adherence, increased access to primary care, decreased emergency department visits and hospitalizations, improved CD4+ cell counts, and decreased HIV load.

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Methods

Overview

We studied participants in a prospective, observational cohort of HIV-infected homeless and marginally housed persons. We assembled our cohort by conducting 2 screenings of homeless and marginally housed persons from April 1996 through December 1997 and from April 1999 through April 2000 in 3 San Francisco neighborhoods. We set out to represent the homeless population by service-use strata using the method of Burnham and Kogel [15]. We constructed a multistage cluster sample that was stratified into shelters, free meal programs, and single-room occupancy hotels. After each screening, in which we tested all screened participants for HIV infection, we invited all who were HIV seropositive (8.8% in 1996–1997 and 14.5% in 1999) to join the cohort. The cohort underwent structured quarterly interviews that focused on their health status, use of and adherence to antiretroviral medications, health service use, housing and health-related behaviors. At quarterly intervals for a 15-month period, between March 2001 and July 2002, participants at the same time underwent a structured interview focused on the use of CM services. At each visit, we drew participants' blood to measure their HIV load and CD4+ cell counts [16]. The study was approved the Institutional Review Board at University of California, San Francisco.

Definition and Measurement of CM

Study staff interviewed all participants about their use of CM. We defined a case manager as a person that (1) worked at an agency, (2) talked with participants about services, and (3) helped participants to get services. We instructed participants that they should not include money managers or doctors but could include nurses and social workers. We asked participants to note which case managers they had seen in the past quarter and at which agency they had seen them. We asked participants whether and how often they had met with each of their case managers since the prior interview. We confirmed participant reports by interviewing the identified case managers. We only considered a participant to have had a case manager when we verified this information.

Independent Variables

We categorized CM use into 3 categories (none or rare, moderate, or consistent) on the basis of the percentage of quarters in the study that the respondent reported having met with their case manager, with ⩽25% of quarters in the study defined as no or rare CM use, >25% but ⩽75% defined as moderate CM use, and >75% defined as consistent CM use. In our multivariate models, we separately compared participants with moderate or consistent CM use with participants with no or rare CM use.

Sociodemographic Variables

At the baseline interview, we ascertained participants' sex, age, and race or ethnicity. We asked participants to complete a residential calendar, describing where they had lived since the prior interview. Participants who reported having spent at least 90% of their nights in a residential hotel or an apartment were considered to be marginally housed. Those who had spent <90% of their nights in a residential hotel and at least 1 night sleeping on the street or in a shelter were considered to be homeless.

Dependent Variables

Use of health services. We asked participants to report whether and how often they had visited their primary care physician for scheduled and acute-care visits each quarter. We considered people to have received primary care if they had a mean of 1 scheduled primary care visit every quarter. We asked whether and how often they have been to the emergency department or been admitted to the hospital. Emergency department visits that resulted in a hospitalization were not counted separately. We dichotomized emergency department use and hospitalization as none or any.

Health status. We assessed health status using the Short Form with 36 Questions (SF-36 ). The SF-36 is a self-administered functional health status instrument that has been validated in a similar population [17]. It includes 2 main dimensions: physical and mental health. The SF-36 is scored from 0 to 100, with higher scores representing better outcomes. The Physical Composite Score (PCS) and Mental Composite Score (MCS) both have means of 50 and SDs of 10 in the US general population [18]. We calculated the PCS and MCS for each participant at baseline and categorized responses as ⩾50, ⩾35 but <50, and <35.

Biological measurements. At each quarterly visit, we obtained blood samples for determination of CD4+ cell count (performed at Unilab; Tarzana, CA) and HIV RNA load (performed at Roche Amplicor; Branchburg, NJ). We determined participants' lifetime CD4+ cell count nadir on the basis of medical record review.

We compared CD4+ cell count values at the baseline visit with those in the follow-up period. We used the CD4+ cell count from the first and last visits to measure the percentage increase in CD4+ cell count, dichotomizing the data at the 50% increase level (i.e., <50% vs. ⩾50%).

We calculated the geometric mean HIV load over the study period and then classified participants with a geometric mean HIV load ⩽400 copies/mL as having undetectable HIV load at follow-up. The remainder of the participants were classified as having a detectable HIV load.

Antiretroviral use and adherence measures. We determined the use of HIV antiretroviral medication on the basis of client self-report during each quarterly interview. We defined appropriate use of ART for baseline and each quarter as concurrent use of ⩾3 antiretroviral medications for a restricted sample of the 219 participants who had a CD4+ cell count nadir of <350 cells/mL (participants with a CD4+ cell count nadir of >350 cells/mL would not meet general criteria for use of ART) [19, 20]. We measured adherence using a standard 3-day structured interview [21]. We estimated adherence by calculating mean adherence over all of the quarters, with 0 assigned to individuals who were eligible for but did not receive therapy.

Participant reimbursement. The participants received $25 for each visit.

Analysis. We analyzed the data using logistic regression, except for adherence, which was measured using linear regression. Variables with P values of <.25 in bivariate analysis were entered into the logistic regression models. For the biological markers, we performed each model with and without adherence entered into the model.

Propensity analysis. Because there was not random assignment of participants into CM or control groups, we conducted a propensity analysis to control for baseline differences in the intervention (CM) group and the nonintervention group. The propensity score is a model-based predicted probability of receiving the intervention of interest [22, 23]. The probability of being in the intervention group is determined for each strata of explanatory variables and is then summarized by combining probabilities weighted by the inverse of the variances to estimate the overall effect. The scores are then entered into a final model as a covariate to account for confounding by indication.

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Results

Baseline Characteristics

Participant demographic characteristics. In the screening portion of the study, 411 persons had test results positive for HIV infection (table 1). of these 411 persons, 330 (80%) agreed to participate in the cohort. Before the start of the study, 35 individuals died, 13 were lost to follow-up, and 2 dropped out, leaving a total of 280 eligible participants. of the 280 participants, the majority (83.2%) were men; their mean age was 43 years. The majority of participants identified as white (41.4%) or African-American (43.2%). Most (71.8%) of the respondents were marginally housed; 28.2% were homeless.

Table 1
Table 1

Characteristics of HIV-infected homeless and marginally housed adults at baseline.

CM use. At the baseline interview, over one-half of the respondents reported currently having a case manager (53.1%). of those who had a case manager, 17.6% had >1 case manager, with a mean (±SD) of 2.3 ± 1.4 case managers.

Baseline substance abuse and mental illness. A total of 40.7% of the participants reported drug use in the past month; almost one-quarter (23.6%) reported having injected drugs in the past 30 days. One-quarter (25.0%) of the participants reported using cocaine (crack and powder cocaine), 18.6% reported use of methamphetamines, and 11.8% reported heroin use. Approximately one-tenth (9.6%) reported daily alcohol intake of >4 drinks per day.

Baseline health status. At baseline, the mean SF-36 PCS of the overall sample was 41.2 (range, 13.3–65.7). The mean MCS was 44.5 (range, 14.6–65.2). The participants' median CD4+ cell count was 374 cells/mL. Nearly one-half (47.9%) of the participants reported using ⩾3 antiretroviral drugs concurrently. Nearly one-third (29.3%) of the participants had an undetectable HIV load (⩽400 copies/mL) at study entry; 49.3% of those receiving ART at baseline had an undetectable viral load at baseline.

Health service use at baseline. At baseline, nearly 70% of respondents reported having had a primary care visit in the previous quarter; one-fifth (20.0%) reported having had an emergency department visit, and 9.6% reported having been hospitalized. At baseline, the mean (±SD) duration of ART was similar for the 3 CM groups: no or rare CM use, 18.0 ± 19.64 months; moderate CM use, 18.0 ± 18.33 months; and consistent CM use, 15.6 ± 15.29 months. The median duration of treatment was 11.0 months, 14.0 months, and 12.0 months for the no or rare CM use group, the moderate CM use group, and the consistent CM use group, respectively.

Outcomes

Follow-up. Twenty-three of 280 subjects were lost to follow-up (defined as >2 consecutive missed interviews).

CM use. Respondents had a mean of 27.7 contacts with a case manager over the 5 quarters of the study period. The number of contacts decreased over the course of the study, from a mean of 9.2 contacts in the first quarter to 3.2 contacts in the final quarter. Among those reporting having a case manager at any point in the study, 148 (52.9%) reported having >1 case manager; 114 (40.7%) reported receiving their services at >1 agency. A total of 41.4% of respondents were classified as having no or rare CM, 23.9% were classified as having moderate CM, and 34.7% were classified as having consistent CM (table 2).

Table 2
Table 2

Case management use, by CD4+ cell count nadir.

Health services use. During the study period, 203 (72.5%) of respondents averaged 1 visit per quarter with their primary care clinician, 112 (41.0%) had at least 1 emergency department visit, and 63 (23.1%) had at least 1 hospitalization.

Antiretroviral treatment and adherence. A total of 115 (41.2%) of the participants reported using ART for at least 1 quarter, whereas 52.8% of participants with a CD4+ cell count nadir of <200 cells/mL and 44.7% of participants with a CD4+ cell count nadir of <350 cells/mL reported using ART. Among those who used ART, 46 (16.4%) reported using it in each quarter of the study.

Biological markers. of the 280 participants, 116 (41.4%) had at least 1 viral load measurement of <400 copies/mL; 46 (16.4%) had ⩽400 copies/mL in all quarters. of the 219 individuals who had CD4+ cell count nadirs of <350 cells/mL, 55 (25.1%) had geometric mean viral loads of ⩽400 copies/mL, and 27 (12.3%) had a ⩾50% increase in CD4+ cell count.

Multivariate Outcomes

CM was not independently associated with primary care use, emergency department use, or hospitalization (table 3).

Table 3
Table 3

Factors associated in logistic regression models with receipt of health care among 280 homeless and marginally housed HIV-infected adults.

Treatment-Indicated Adherence to HIV ART

In a multivariate linear regression model, moderate CM was associated with improved adherence (β = 0.13; 95% CI, 0.02–0.25), compared with no or rare CM. Consistent CM use neared but did not reach a statistically significant association (β = 0.13; 95% CI, -0.01 to 0.26) (table 4).

Table 4
Table 4

Factors associated in a linear regression model with increased treatment-indicated adherence among 219 homeless and marginally housed persons with CD4+ cell count nadir <350 cells/mL.

Biological Markers

Improvement in CD4+ cell count. In a multivariate model examining factors associated with a ⩾50% increase in CD4+ cell count, we found that, compared with no or rare CM, both moderate CM and consistent CM were strongly associated with improvements in CD4+ cell counts (table 5). This relationship was true with and without adherence in the model. Removing adherence from the model slightly increased both adjusted ORs (AORs). Results were similar with a CD4+ cell count increase of >100 cells/mL (data not show).

Table 5
Table 5

Factors associated in logistic regression models with desirable biological outcomes among homeless and marginally housed HIV-infected persons with CD4+ cell count nadir <350 cells/mL (n = 219).

Geometric viral load ⩽400 copies/mL. In a multivariate model examining patients having a geometric mean viral load ⩽400 copies/mL, the model was dominated by adherence (AOR, 16.2; 95% CI, 6.4–41.0). When adherence was in the model, there was no significant reduction in the outcome of having consistent CM (AOR, 1.6; 95% CI, 0.7–3.7) or moderate CM (AOR, 1.1; 95% CI, 0.4–2.8), compared with no or rare CM. When we removed adherence from the model, there was an elevated (but not statistically significant) association between consistent CM and viral load ⩽400 (AOR, 2.0; 95% CI, 0.9–4.4).

Propensity analysis. Adjusting factors using a propensity analysis did not change any of our results (data not shown).

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Discussion

In this study examining a cohort of HIV-infected urban poor, we found that having CM was independently associated with improved adherence to ART and improved CD4+ cell count. Having consistent CM neared but did not reach a statistically significant relationship with improved adherence to ART; it was strongly associated with improvements in CD4+ cell count and neared but did not reach a reduction in geometric viral load. CM was not associated with changes in health services use; it was associated neither with an increased rate of receipt of primary care nor with reductions in emergency department use or hospitalizations.

Although CM is widely used in HIV care and is believed to improve health outcomes, there are few studies looking at health outcomes with HIV CM in disenfranchised populations. Our finding that any CM was associated with improved ART adherence and improved biologic outcomes extends prior research on the effect of CM on patients with HIV infection. The effects of CM on health outcomes have not been previously documented [4]. Our findings suggest that CM may play a role in improving health outcomes among low-income persons with HIV infection.

Without a randomized trial, we cannot state that there was a causal association between CM and improved outcomes. There are several means by which CM could improve biologic outcomes. Improved biologic outcomes could be explained by the increased appropriate use of and adherence to ART [24]. of interest, increased adherence did not fully explain the association between CM and improvements in CD4+ cell count. This may be because CM may have sustained CD4+ cell counts through other means, such as better use of opportunistic infection prophylaxis or other health-related behaviors. One of the primary effects of CM may be in its ability to assist clients in organization, enabling the consistent use of complicated medical regimens, including ART. It is likely that many case managers encourage their clients to adhere to medication, assist in communicating side effects to primary care providers, and check in with clients regularly to make sure medications are prescribed and refilled.

Our findings that CM was not associated with primary care may be a result of high attendance at primary care facilities, allowing little room for improvement from CM. We did not find an association with emergency department use or hospitalizations, suggesting that CM neither reduced visits nor increased them (via increased surveillance).

We found that rates of CM were similar to those reported for participants in Ryan White CARE programs nationally [25]. A relatively large proportion of participants used >1 case manager and >1 agency. This suggests some duplication of services. These may be explained by the different roles played by different case managers, or it may point towards a lack of coordination within the system.

Our study had a number of limitations. We did not determine CM by random enrollment. It is possible that the same qualities that allowed participants to receive CM were the reason for their improved medication adherence or improved biological markers. It is also possible that those who were deemed to have greater need of CM were enrolled more aggressively. Including a propensity analysis in our multivariate model did not change our results.

The CM models studied were heterogeneous: some included brokerage models and other models in which the case managers themselves provided mental health counseling or nursing CM. This heterogeneity would bias our findings towards the null hypothesis. We relied on several self-reported measures. These may be underreported or reported inaccurately. We may not have had sufficient power to note small effects, particularly when we examined the subpopulation that would benefit from the use of ART to measure ART use and adherence. We limited subjects with eligible HAART use to subjects with CD4+ cell counts <350 cells/mL. This is a conservative classification of HAART eligibility, because a common standard was to treat at CD4+ cell counts of <500 cells/mL [19, 20]. The study did not explore whether different models of CM would be more effective nor did it compare CM to other potential interventions, such as improving access to HIV testing or primary care. Finally, our study was conducted in 1 city and therefore may not be generalizable to other locations.

Our study found an association between the use of CM services and improved adherence to ART and improved biological markers of HIV disease among homeless and marginally housed HIV-infected populations. This suggests that CM may be an effective way to improve health outcomes among disenfranchised HIV-infected populations.

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Acknowledgments

Financial support. National Institute of Mental Health (RO-1 54907) and The University-Wide AIDS Research Program. M.B.K. received financial support from the Agency for Health Care Research and Quality (K-08 HS 11415) and the Hellman Family Award for Junior Faculty. D.R.B. received support from The Doris Duke Clinical Scientist Development Program.

Potential conflicts of interest. All authors: no conflicts.

  • Received January 2, 2006.
  • Accepted April 4, 2006.
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  1. Clin Infect Dis. (2006) 43 (2): 234-242. doi: 10.1086/505212
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