Factors Associated With Treatment Initiation for Psychiatric and Substance Use Disorders Among Persons With HIV
Abstract
Objective
Prior studies of individuals with HIV infection have found that accessing psychiatric and substance abuse treatment when needed can improve health and prolong life, yet little is known about factors associated with treatment initiation.
Methods
In a retrospective cohort design including individuals with HIV infection (≥14 years old) in an integrated health care system in Northern California, this study included 822 patients with a major psychiatric diagnosis and 1,624 with a substance use disorder diagnosis. Data were extracted from a regional HIV registry and computerized databases.
Results
Twenty-four percent (N=198) of study patients with psychiatric diagnoses and 15% (N=245) with substance abuse or dependence received one or more specialty care visits within 12 months of diagnosis. Among patients with a psychiatric diagnosis, significant predictors of visiting a psychiatry clinic included not having an AIDS diagnosis at baseline or before the study (p=.049), having a diagnosis of major depression (p=.013), having a diagnosis of bipolar disorder (p<.001), and receiving a psychiatric diagnosis in 1996 versus later years of the study (p<.01). Among patients with a substance use disorder, significant predictors of initiating substance abuse treatment included age <30 (p=.015) and being in the HIV transmission risk group of injection drug use (p<.001).
Conclusions
Clinical, diagnostic, and demographic factors were associated with specialty care treatment initiation in this sample of individuals with HIV infection and substance use or psychiatric disorders. Developing strategies to enhance treatment initiation has the potential to improve outcomes for individuals with HIV infection.
Studies of individuals with HIV have found high prevalence of psychiatric (1–3) and substance use (4,5) disorders. Substance use and psychiatric disorders are associated with numerous general medical comorbidities (6,7) and inadequate antiretroviral (ARV) adherence (8–11), and they place HIV patients at elevated risk for poor health outcomes, including early mortality (12–15). However, among HIV patients with these disorders, those who obtain substance abuse treatment (16) and psychiatric care (17,18) have higher rates of ARV utilization and better viral control (19,20), as well as lower risk of early mortality (5,21). Yet only a minority of HIV-positive patients receives these services (22–24). These studies highlight the urgency of investigations examining how HIV patients initiate behavioral health care, so that a greater number of patients may benefit.
The Andersen model (25) is a useful framework proposed to help understand factors that contribute to treatment initiation. The model has hypothesized that treatment initiation may be determined by predisposing factors, such as demographic characteristics; need factors, such as diagnosis and severity indicators (26); and enabling factors, such as insurance and social variables (27).
Although a number of studies have examined predictors of initiation of substance abuse treatment and psychiatric outpatient service by including components of the Andersen model (28–31), few have been conducted with HIV-positive samples. In a study of HIV patients in the Boston area, who were primarily heterosexual and unemployed (32), self-reported initiation of outpatient substance abuse treatment was associated with need factors of having hepatitis C, being homeless, and having a drug dependence diagnosis and with the enabling factor of not having members of the social support network encourage drug use. In a national probability sample (33), an analysis that controlled for need of psychiatric treatment found that initiating psychotropic medication was associated with predisposing factors of younger age, not being African American, and being disabled; with the need factor of having a greater number of HIV symptoms; and with the enabling factor of having Medicare. Initiating individual or family therapy was associated with higher education and being disabled (predisposing factors), and initiating outpatient substance abuse treatment was associated with being predisposing factors of being African American and having lower education and with the enabling factor of having Medicaid. In a multisite study (34), initiating outpatient psychiatry services was associated with predisposing factors of not being African American and being disabled, with the need factor of current illicit drug use, and with the enabling factor of a greater number of recent primary care visits.
Although informative regarding treatment-seeking patterns, none of this work was conducted in insured samples. Our work builds on these prior studies by examining key demographic and clinical factors associated with outpatient treatment initiation in an insured sample in an integrated health plan, an important model of service delivery in which all patients have access to care.
Linking the Andersen model to the literature on initiation of behavioral health services among HIV patients, we hypothesized that among those with a psychiatric disorder, accessing psychiatric services would be associated with older age and white race as predisposing factors and greater HIV illness severity as a need factor (33). We also hypothesized that among those with a substance use disorder, accessing substance abuse treatment would be associated with the predisposing factor of black race (33) and with the need factors of lower CD4 T-cell counts, not taking ARV medications (32), and using illicit injection drugs (35). Understanding these factors has the potential to enhance efforts to engage HIV-infected individuals with important services.
We examined factors associated with initiation of psychiatric and substance abuse treatment among health plan members with a diagnosis of a psychiatric or substance use disorder noted in their medical records, which established treatment need and awareness of providers. Members were in a private, fully integrated health care plan where access to care and ability to pay for care are not significant barriers to treatment. Conducting the study in this setting allowed us to focus on key clinical and demographic predictors of treatment initiation that health systems can address to improve services.
Methods
Study setting
We conducted a retrospective observational cohort study for years 1996 to 2009 among 12,636 HIV-infected individuals who were members of Kaiser Permanente Northern California (KPNC). KPNC is an integrated health care delivery system with a membership of 3.2 million individuals, representing 34% of the insured population in Northern California. The membership is representative of the population with respect to race-ethnicity, gender, and socioeconomic status, except for some underrepresentation of both extremes of the economic spectrum (36). Members with HIV infection receive services at medical centers throughout the KPNC 17-county catchment region.
Psychiatric and substance abuse treatment services are available to all members. Psychiatric treatment includes assessment, individual and group psychotherapy, and medication management. Outpatient substance abuse treatment services include both day hospital and traditional outpatient programs (37), both of which include eight weeks of individual and group therapy, education, relapse prevention, and family therapy.
Study sample
We assembled two cohorts. In the first, patients had at least one psychiatric diagnosis in their medical record (N=2,704, representing 21% of HIV registry patients); in the second, patients had at least one diagnosed substance use disorder during the study follow-up period (N=2,487, representing 20% of HIV registry patients). The two cohorts were not mutually exclusive. We included only patients with active disorders (that is, not in remission) who had received their diagnoses outside specialty care and before specialty treatment initiation (to enable examination of treatment initiation predictors) and who had at least one month of KPNC health plan membership (to allow enough time for a diagnosis to be assigned).
In the psychiatric cohort of 2,704 potential patients, we excluded 45 individuals whose medical records showed only remission codes and 1,738 patients who had had their first psychiatric clinic visit on or before their first date of psychiatric diagnosis. Finally, 99 patients who did not have at least one month of health plan membership before their first psychiatric diagnosis were excluded. Thus 822 patients were included in the psychiatric cohort analyses.
In the substance use disorder cohort of 2,487 potential patients, we excluded 248 patients whose medical records showed only substance use disorder remission codes and 350 patients who had been seen at a substance use disorder treatment clinic on or before their first date of substance use disorder diagnosis. Finally, the study excluded 265 patients who did not have at least one month of health plan membership before their first diagnosis date of substance use disorder. Thus, 1,624 patients were included in the substance use cohort analyses.
This study was approved by the institutional review boards of KPNC and the University of California, San Francisco.
Data sources
Since 1988, the KPNC Division of Research has maintained a surveillance system of members who are HIV-1 seropositive, ascertained through monitoring electronic inpatient, outpatient, laboratory testing, and pharmacy dispensing databases for sentinel indicators of probable HIV infection and confirmed through review of medical records. Ascertainment of HIV-infected members by this registry has been shown to be at least 95% complete. The HIV registry contains information on demographic characteristics (including sex, birth date, and race-ethnicity), HIV transmission risk group (men who have sex with men, injection drug users, heterosexual sex, other, and unknown), dates of known HIV infection, AIDS diagnoses, CD4 T-cell counts, and HIV-1 RNA levels.
KPNC maintains electronic databases on hospital admission, discharge, and transfer data and emergency department and outpatient visits. To control for the impact of health services utilization as an enabling factor (34,38)—for example, general medical visits may increase the likelihood of initiating specialty behavioral health care (39)—we measured the number of visits between the time of substance use or psychiatric diagnosis through the follow-up period (one year). Measures included inpatient hospitalization (yes or no), emergency department visits (yes or no) and outpatient visits (zero, one, or two or more visits). Inpatient and emergency department visits were dichotomized because these events were relatively infrequent.
ARV medication prescription data were obtained from KPNC pharmacy databases. Approximately 97% of HIV patients fill their prescriptions at KPNC pharmacies. ARV medication data included date of first fill, dosage, days of supply, and refills. Patients were classified as currently receiving or not receiving combination-ARV (or dual nonnucleoside reverse-transcriptase inhibitor–nucleoside reverse-transcriptase inhibitor ARV use for some who received treatment in 1996).
We used psychiatric and substance use diagnoses assigned by providers to identify participants. Diagnoses can be assigned in any clinical setting within the KPNC health plan, such as primary care or an emergency setting, but we excluded participants whose psychiatric diagnosis was initially made in a psychiatric department and participants whose substance use diagnosis was initially made in a substance abuse treatment clinic before they received a diagnosis in another setting. One or more diagnoses can be coded with ICD-9 in the KPNC administrative databases (40,41). We studied the most common and serious psychiatric disorders, including major depressive disorder, bipolar disorder, neurotic disorders (including panic), hysteria, phobic disorders, obsessive-compulsive disorder, anorexia nervosa and bulimia, and schizophrenic disorders (including schizoaffective type disorder). For the substance use disorder cohort, diagnostic categories included all alcoholic psychoses, drug psychoses, alcohol abuse or dependence, drug abuse or dependence (including opioid, barbiturate, sedative-tranquilizer, cocaine, cannabis, amphetamine, and hallucinogen abuse or dependence but excluding tobacco), as well as abuse of multiple or unspecified substances. Remission codes were excluded from the analyses.
Study outcomes
To determine whether patients in the study sample would likely meet a minimum criterion for receiving care (treatment initiation) (42,43), the primary outcomes examined in this study were initiation of psychiatric treatment (having one or more visits at KPNC) by HIV patients who had received a psychiatric diagnosis or initiation of substance abuse treatment (having one or more visits at KPNC) by those who had received a substance use disorder diagnosis, each occurring within one year of diagnosis. Follow-up for treatment initiation (first visit to psychiatry clinic) began at the date of first psychiatric diagnosis (baseline date for psychiatric cohort).
Statistical methods
Initial analyses focused on descriptive characteristics of patients with psychiatric or substance use disorders (Table 1). Cox proportional hazards regression was used to obtain point and interval estimates of risks relative to treatment initiation after diagnosis. These estimates were adjusted for an a priori chosen set of covariates based on the Andersen model, as follows: predisposing factors included age at psychiatric or substance use diagnosis, gender, race-ethnicity, and HIV transmission risk group; need factors included time-dependent covariates of CD4 T-cell counts, HIV-1 RNA levels, and ARV treatment (naïve or experienced) plus AIDS diagnosis before mental health diagnosis; and enabling factors included primary care visits, inpatient hospitalizations, and any emergency visits within the year before follow-up as well as the year of diagnosis of a psychiatric or substance use disorder (32). These variables were selected as key components of the Andersen model (44,45), in which demographic factors represent a biological imperative for service utilization and thus predispose individuals to access care, clinical measures and diagnoses represent professionally evaluated need for medical care, and health services utilization in the prior year represents contact with the health care system that can enable patients to obtain further services, in this case psychiatric and substance abuse treatment.
| Substance use disorder (N=1,624) | Psychiatric disorder (N=822) | |||
|---|---|---|---|---|
| Characteristic | N | % | N | % |
| Age | ||||
| <30 | 109 | 7 | 44 | 5 |
| 30–39 | 556 | 34 | 240 | 29 |
| 40–49 | 621 | 38 | 298 | 36 |
| 50–59 | 268 | 17 | 174 | 21 |
| ≥60 | 70 | 4 | 66 | 8 |
| Gender | ||||
| Female | 133 | 8 | 78 | 9 |
| Male | 1,491 | 92 | 744 | 91 |
| Race-ethnicity | ||||
| White | 1,012 | 62 | 452 | 55 |
| African American | 283 | 17 | 134 | 16 |
| Hispanic | 181 | 11 | 130 | 16 |
| Other | 72 | 4 | 52 | 6 |
| Unknown | 76 | 5 | 54 | 7 |
| HIV risk transmission | ||||
| Heterosexual sex | 181 | 11 | 100 | 12 |
| Injection drug use | ||||
| Not among men who have sex with men | 116 | 71 | 32 | 4 |
| Including men who have sex with men | 123 | 8 | 50 | 6 |
| Men who have sex with men | 1,020 | 63 | 530 | 64 |
| Coagulation disorder or transfusion | 13 | 1 | 6 | 1 |
| Unknown | 171 | 11 | 104 | 13 |
| AIDS diagnosis | ||||
| No | 823 | 51 | 352 | 43 |
| Yes | 801 | 49 | 470 | 57 |
| CD4 cell count (per μl) | ||||
| Missing | 292 | 18 | 169 | 21 |
| <100 | 156 | 10 | 71 | 9 |
| 100–200 | 192 | 12 | 84 | 10 |
| 201–349 | 303 | 19 | 162 | 20 |
| 350–499 | 392 | 24 | 169 | 21 |
| ≥500 | 289 | 18 | 167 | 20 |
| HIV RNA level at baseline | ||||
| Missing | 464 | 29 | 290 | 35 |
| ≥104.7 | 269 | 17 | 111 | 14 |
| 103.3–<104.7 | 392 | 24 | 139 | 17 |
| 102.7–<103.3 | 128 | 8 | 54 | 7 |
| <102.7 | 372 | 23 | 228 | 28 |
| Antiretroviral treatment | ||||
| No | 735 | 45 | 270 | 33 |
| Yes | 889 | 55 | 552 | 67 |
| Any visit to emergency department | ||||
| No | 1,162 | 72 | 598 | 73 |
| Yes | 462 | 28 | 224 | 27 |
| Any inpatient stays | ||||
| No | 1,388 | 85 | 680 | 83 |
| Yes | 236 | 15 | 142 | 17 |
| Any psychiatric disorder | ||||
| No | 1,151 | 71 | ||
| Yes | 473 | 29 | ||
| Specific psychiatric diagnosis | ||||
| Major depression | 526 | 64 | ||
| Anorexia or bulimia | 132 | 16 | ||
| Panic disorder | 99 | 12 | ||
| Bipolar disorder | 41 | 5 | ||
| Other | 25 | 3 | ||
| Any substance use disorder | ||||
| No | 634 | 77 | ||
| Yes | 188 | 23 | ||
| Specific substance use diagnosis | ||||
| Alcohol dependence or abuse | 585 | 36 | ||
| Cannabis abuse or dependence | 195 | 12 | ||
| Dependence or abuse of multiple substances | 195 | 12 | ||
| Amphetamine abuse or dependence | 114 | 7 | ||
| Alcohol or drug psychoses | 65 | 4 | ||
| Cocaine abuse or dependence | 49 | 3 | ||
| Opioid abuse or dependence | 16 | 1 | ||
| Unspecified | 358 | 22 | ||
| Initiated outpatient psychiatric services | ||||
| No | 624 | 76 | ||
| Yes | 198 | 24 | ||
| Initiated outpatient substance abuse treatment | ||||
| No | 1,379 | 85 | ||
| Yes | 245 | 15 | ||
The regression model for the substance use disorder cohort included psychiatric diagnosis as a time-dependent covariate, and the model for the psychiatric diagnosis cohort included substance abuse or dependence diagnosis, major depression diagnosis, and bipolar disorder diagnosis as time-dependent covariates. Gender was included in but dropped from the final model because of lack of significance and because the sample was over 90% male. Data analyses were conducted with SAS software, version 9.1.
Results
Study patients with a psychiatric diagnosis had distributions of demographic and HIV-related clinical and behavioral characteristics similar to patients with a substance use disorder (Table 1). Most patients were white, male, and 30–49 years of age at baseline and belonged to the HIV transmission risk group of men who have sex with men. CD4 T-cell counts measured at or near time of study entry were comparable in both groups. Similar results in the two groups were observed for HIV RNA levels, although rates of ARV therapy were slightly higher in the psychiatric group.
Of the 822 patients with a psychiatric diagnosis, 24% had one or more psychiatry department visits postdiagnosis. The mean±SD time to first psychiatric clinic visit after diagnosis was 76.1±98.5 days. Of the 1,624 patients with a substance use disorder, 15% had one or more substance abuse treatment visits postdiagnosis. Time to first substance abuse treatment visit after diagnosis was 78.8±95.5 days.
The relative hazards (relative risk) for predictors of substance abuse and psychiatric treatment initiation were estimated via Cox proportional hazards regression (Table 2). Among patients with a substance use disorder, significant predictors of having one or more visits to a KPNC substance abuse treatment program included younger age (under 30 versus 60 or older [p=.015] or 50–59 years old [p=.048]) as predisposing factors; being in the HIV transmission group of injection drug users who are not men who have sex with men (p<.001), a need factor; and not having CD4 cell counts measured during study follow-up (p=.015). Not having HIV RNA levels measured during study follow-up (p=.005) also was associated with not seeking care at a KPNC substance abuse treatment program.
| Substance abuse treatment | Psychiatric treatment | |||
|---|---|---|---|---|
| Characteristic | Hazard ratio | 95% CI | Hazard ratio | 95% CI |
| Age (reference: <30) | ||||
| 30–39 | .99 | .61–1.62 | 1.77 | .79–3.96 |
| 40–49 | .67 | .40–1.11 | 2.30* | 1.04–5.09 |
| 50–59 | .55* | .31–1.00 | 1.69 | .73–3.95 |
| ≥60 | .26* | .09–.78 | .70 | .22–2.16 |
| Race-ethnicity (reference: white) | ||||
| African American | .85 | .58–1.25 | 1.45 | .97–2.18 |
| Hispanic | .79 | .51–1.23 | .85 | .54–1.36 |
| Other | 1.03 | .57–1.89 | 1.16 | .62–2.17 |
| Unknown | 1.22 | .68–2.19 | .98 | .50–1.95 |
| HIV transmission risk (reference: heterosexual sex) | ||||
| Injection drug use | ||||
| Not among men who have sex with men | 3.49*** | 1.89–6.45 | 1.15 | .52–2.53 |
| Including men who have sex with men | 1.85 | .95–3.59 | .94 | .45–1.96 |
| Men who have sex with men | 1.57 | .93–2.64 | .91 | .57–1.46 |
| Coagulation disorder or transfusion | .00 | .00–.00 | 1.84 | .39–8.68 |
| Unknown or not measured | 1.42 | .74–2.71 | .73 | .38–1.41 |
| CD4 cell count at baseline (reference: ≥500 cells/μl) | ||||
| 350–499 | 1.07 | .76–1.52 | .98 | .68–1.43 |
| 201–349 | 1.12 | .77–1.64 | .75 | .49–1.14 |
| 100–200 | 1.12 | .68–1.86 | .53 | .27–1.02 |
| <100 | .72 | .38–1.35 | .41* | .19–.87 |
| Unknown or not measured | 2.98* | 1.13–7.87 | 1.54 | .43–5.51 |
| HIV RNA level at baseline (reference: <102.7) | ||||
| 102.7–<103.3 | 1.13 | .68–1.86 | .64 | .29–1.42 |
| 103.3–<104.7 | .89 | .61–1.28 | .83 | .51–1.35 |
| ≥104.7 | 1.27 | .82–1.95 | 1.72* | 1.00–2.97 |
| Unknown | .26** | .10–.67 | .67 | .22–2.09 |
| Antiretroviral therapy during follow-up (reference: no) | 1.19 | .86–1.63 | 1.21 | .81–1.80 |
| AIDS diagnosis at baseline (reference: no) | .90 | .65–1.24 | .71* | .50–1.00 |
| Visit to outpatient clinics (reference: 0) | ||||
| 1 | .74 | .37–1.47 | .79 | .32–1.97 |
| ≥2 | .87 | .52–1.47 | 1.10 | .54–2.24 |
| Visit to emergency department (reference: no) | .99 | .73–1.34 | .82 | .56–1.21 |
| Inpatient stay (reference: no) | .92 | .60–1.40 | 1.39 | .88–2.19 |
| Psychiatric diagnosis (reference: no) | 1.09 | .82–1.45 | ||
| Substance use disorder (reference: no) | .69 | .48–1.01 | ||
| Major depression diagnosis (reference: no) | 1.63* | 1.11–2.39 | ||
| Bipolar diagnosis (reference: no) | 3.41*** | 1.90–6.11 | ||
| Year of psychiatric diagnosis (reference: 1996) | ||||
| 1997 | .48 | .12–1.93 | ||
| 1998 | .21* | .05–.89 | ||
| 1999 | .44 | .09–2.11 | ||
| 2000 | .18* | .05–.69 | ||
| 2001 | .22* | .06–.81 | ||
| 2002 | .22* | .06–.76 | ||
| 2003 | .16** | .05–.53 | ||
| 2004 | .17** | .05–.54 | ||
| 2005 | .26* | .08–.80 | ||
| 2006 | .15** | .05–.50 | ||
| 2007 | .20** | .06–.63 | ||
| 2008 | .15** | .05–.46 | ||
| 2009 | .15** | .05–.49 | ||
| Year of substance use disorder diagnosis (reference: 1996) | ||||
| 1997 | 1.36 | .63–2.91 | ||
| 1998 | 1.75 | .81–3.78 | ||
| 1999 | .95 | .43–2.13 | ||
| 2000 | 1.48 | .70–3.14 | ||
| 2001 | .91 | .41–2.03 | ||
| 2002 | 1.74 | .83–3.66 | ||
| 2003 | 1.06 | .47–2.03 | ||
| 2004 | 1.64 | .76–3.51 | ||
| 2005 | 1.15 | .53–2.52 | ||
| 2006 | 1.35 | .62–2.94 | ||
| 2007 | 1.43 | .66–3.10 | ||
| 2008 | 1.93 | .87–4.26 | ||
| 2009 | .75 | .28–2.00 | ||
a
N=1,624 participants with a substance use disorder and 822 participants with a psychiatric diagnosis
* p<.05, **p<.01, ***p<.001
Among patients with a psychiatric diagnosis, significant predictors of having one or more visits to a KPNC psychiatry clinic included the predisposing factor of older age—specifically, being in the 40- to 49-year-old group versus the under-30 group (p=.041). Having a diagnosis of major depression (p=.013) and having a diagnosis of bipolar disorder (p<.001) were significant need-related predictors of seeking psychiatric treatment, whereas having an AIDS diagnosis at or prior to entry into study was predictive of not seeking treatment (p=.049). Of patients receiving their psychiatric diagnosis between 1997 and 2009, those diagnosed later in the range were significantly less likely to seek psychiatric treatment compared with those diagnosed in 1996 (p<.01) (Table 2).
Discussion
As in prior HIV studies, in this study the results indicated substantial prevalence of both substance use and psychiatric disorders. The overall prevalence rates we observed (21% with a psychiatric disorder and 20% with a substance use disorder) were significantly elevated compared with rates of non–HIV-positive individuals in the general population (1). As in previous general population (29,30) and HIV (23) studies, in this study major depression was the most prevalent diagnosis. Overall rates and prevalence of specific psychiatric and substance use disorders were somewhat lower than those observed in other large HIV samples, perhaps because we used provider-assigned diagnosis in our sample selection rather than structured interviews (3,4,23). Although the prevalence reported thus may be conservative, our approach identified rates of these disorders as recorded by health care providers, which serves as a baseline for examining to what extent these patients received subsequent specialty care services.
Direct comparison of rates of treatment initiation with results of other studies is difficult because of variability in time frame and treatment measurement. However, rates were similar to those found in prior general population studies, in which a minority of patients (approximately 15%–30%) of patients with substance use disorders (46–48) or psychiatric disorders (30,49–51) received specialty care treatment. These rates are also similar to those in prior studies of HIV-positive individuals (24,32,34), highlighting the significant gaps between service need and receipt of specialty care.
To inform ways to improve substance use and psychiatric care among HIV-infected patients, we used the Andersen model to examine demographic and clinical factors associated with initiating specialty services (25). Among indicators of treatment need, we found that two of the most frequent diagnoses (major depression and bipolar disorder) predicted psychiatric service initiation. One prior study found that among HIV-infected individuals with depression, shorter time to psychiatric treatment was associated with greater depression severity (52). Two prior studies found that having a substance use disorder was associated with accessing both substance abuse treatment and psychiatric services (33,34); however, these study samples included HIV-infected participants in general population samples rather than psychiatric samples. Although we did not measure illness severity, more acute and unstable psychiatric problems, such as bipolar disorder and severe depression, generally are managed in specialty psychiatry clinics within the KPNC health plan. Our findings are consistent with this practice.
Including year of diagnosis (enabling factor) as a covariate in the model showed that patients diagnosed as having a psychiatric disorder in later years were less likely to have initiated specialty care. Although the specific reasons for this cannot be determined, the finding is consistent with the trend in the United States for mental health conditions to be increasingly treated in primary care (53). Substance use disorders, which continue to be treated primarily in specialty care, showed no comparable result.
It is difficult to draw conclusions regarding the effect of having missing CD4 and HIV RNA measurements on initiation of substance abuse treatment. Measurements could be missing if a patient neglects routine monitoring, either because viral control is stable or because active substance use problems interfere with regular care. These reasons may explain why lack of HIV RNA measurement was associated with not initiating substance abuse treatment. CD4 tests are sometimes administered less frequently, and it is not clear whether the same possible explanations would apply, given the opposite direction of the effects observed. Not having an AIDS diagnosis was also significantly related to initiating specialty care in psychiatry, and reasons for this are similarly speculative: given the illness severity that an AIDS diagnosis indicates, it may be that illness prevented patients from accessing specialty psychiatric care or that psychiatric treatment was managed in primary care.
Implications for patient care
Improving specialty care service linkages or enhancing primary care–based services could help HIV patients obtain needed substance abuse treatment. For example, one KPNC study found that patients with a substance use disorder and comorbid chronic general medical conditions had better alcohol and drug use outcomes when medical services were integrated (37). In this approach, general medical care was colocated with substance abuse treatment. Alternative forms of implementation of the screening, brief intervention, and referral to treatment (SBIRT) model are being studied, as is training for primary care providers on motivational interviewing to enhance willingness to change and procedures for linking patients with substance abuse treatment (54). Using motivational interviewing as well as secure electronic messaging to implement SBIRT strategies for HIV patients is also being investigated within the health plan (55). Such approaches could help enhance treatment initiation for substance use disorders, including in systems such as KPNC, which are already designed to deliver integrated care but would benefit from more active linkages.
Similarly, enhancing psychiatric specialty care linkages as well as services in primary care also should be explored. Strategies such as those used in the Improving Mood: Promoting Access to Collaborative Treatment trial have explored how to improve depression treatment within primary care settings (56). Depression treatment initiatives implemented in KPNC also have encouraged electronic communication between patients and specialty care providers (57). Given the need for HIV patients to closely track their medications and other aspects of care, these strategies seem especially appropriate in this population.
In addition, analysis of factors associated with treatment initiation helps reveal which patients may be least likely to access care (such as older adults with a substance use disorder). Building on prior studies of utilization of substance use and psychiatric treatment (31,33,58), this study indicates that targeting subgroups of HIV patients in primary care services who underutilize care and addressing issues such as the stigma associated with going to a psychiatry or substance use clinic may help to increase treatment initiation. For patients without significant financial barriers but unwilling to access specialty services within an integrated system, primary care integration strategies are likely to be especially important.
Study strengths and limitations
Strengths of this study include its large sample size and use of administrative data. We used a conservative method in which study patients’ specialty care visits had to occur subsequent to diagnosis to ensure appropriate measurement of predictors of treatment initiation (rather than coincident treatment and diagnosis). Thus we selected patients given a diagnosis in clinics other than chemical dependency or psychiatry, such as within primary care, and focused on treatment initiation rather than on extent of services received.
The study also had limitations. The selection criteria necessitated by our study design resulted in a subsample of the HIV patients treated in KPNC: for example, patients who did not receive a substance use or psychiatric diagnosis before initiating specialty care services were excluded. This could affect the representativeness of the sample. Some patients may have met the criteria for a psychiatric or substance use disorder without receiving a diagnosis, which would also affect representativeness. When participants received diagnoses of psychiatric or substance use disorders, it is not known whether providers discussed these diagnoses with the participants or whether providers specifically referred participants to specialty care. A further limitation of the study is missing data on some measures, such as CD4 cell counts and HIV RNA levels at baseline, reducing our ability to examine the impact of these factors.
The study did not examine services received apart from KPNC specialty care. Additional sources for treatment may have been accessed by HIV-infected members, including discussion of behavioral health problems with a primary care physician (33) and Alcoholics Anonymous or other self-help groups. We note that the characteristics of HIV patients seeking formal substance abuse treatment services and self-help may be similar (33). Because accessing specialty care can reduce mortality (5,21), and referral to specialty care for those with more severe disorders is a widely used approach, exploring potential barriers to treatment initiation is an important area of investigation.
Conclusions
This study examined predictors of substance abuse treatment and psychiatric specialty care treatment initiation among members of an HIV/AIDS registry in an integrated health plan. As in prior studies, a minority of patients with substance use or psychiatric disorders initiated treatment. Demographic and clinical factors were associated with treatment initiation, which varied between the two types of diagnosis. Developing strategies to enhance specialty care treatment initiation has the potential to improve health outcomes for those with HIV infection.
Acknowledgments and disclosures
This study was funded by grants R37 DA10572 and P50 DA09253 from the National Institute on Drug Abuse and by grant U01AA021997 from the National Institute on Alcohol Abuse and Alcoholism. The authors thank Felicia Chi, M.P.H., who developed computer algorithms used to assign ICD-9 codes to patients with psychiatric and substance use disorders, and Agatha Hinman, B.A., for editorial assistance in the preparation of the manuscript.
The authors report no competing interests.
References
1.
Lopes M, Olfson M, Rabkin J, et al.: Gender, HIV status, and psychiatric disorders: results from the National Epidemiologic Survey on Alcohol and Related Conditions. Journal of Clinical Psychiatry 73:384–391, 2012
2.
Nurutdinova D, Chrusciel T, Zeringue A, et al.: Mental health disorders and the risk of AIDS-defining illness and death in HIV-infected veterans. AIDS 26:229–234, 2012
3.
Pence BW, Miller WC, Whetten K, et al.: Prevalence of DSM-IV-defined mood, anxiety, and substance use disorders in an HIV clinic in the Southeastern United States. Journal of Acquired Immune Deficiency Syndromes 42:298–306, 2006
4.
Bing EG, Burnam MA, Longshore D, et al.: Psychiatric disorders and drug use among human immunodeficiency virus-infected adults in the United States. Archives of General Psychiatry 58:721–728, 2001
5.
DeLorenze GN, Weisner C, Tsai AL, et al.: Excess mortality among HIV-infected patients diagnosed with substance use dependence or abuse receiving care in a fully integrated medical care program. Alcoholism, Clinical and Experimental Research 35:203–210, 2011
6.
Altice FL, Kamarulzaman A, Soriano VV, et al.: Treatment of medical, psychiatric, and substance-use comorbidities in people infected with HIV who use drugs. Lancet 376:367–387, 2010
7.
Robinson-Papp J, Gelman BB, Grant I, et al.: Substance abuse increases the risk of neuropathy in an HIV-infected cohort. Muscle and Nerve 45:471–476, 2012
8.
Pence BW: The impact of mental health and traumatic life experiences on antiretroviral treatment outcomes for people living with HIV/AIDS. Journal of Antimicrobial Chemotherapy 63:636–640, 2009
9.
Kacanek D, Jacobson DL, Spiegelman D, et al.: Incident depression symptoms are associated with poorer HAART adherence: a longitudinal analysis from the Nutrition for Healthy Living study. Journal of Acquired Immune Deficiency Syndromes 53:266–272, 2010
10.
Carrico AW, Riley ED, Johnson MO, et al.: Psychiatric risk factors for HIV disease progression: the role of inconsistent patterns of antiretroviral therapy utilization. Journal of Acquired Immune Deficiency Syndromes 56:146–150, 2011
11.
Gonzalez A, Barinas J, O’Cleirigh C: Substance use: impact on adherence and HIV medical treatment. Current HIV/AIDS Reports 8:223–234, 2011
12.
Antelman G, Kaaya S, Wei R, et al.: Depressive symptoms increase risk of HIV disease progression and mortality among women in Tanzania. Journal of Acquired Immune Deficiency Syndromes 44:470–477, 2007
13.
Ickovics JR, Hamburger ME, Vlahov D, et al.: Mortality, CD4 cell count decline, and depressive symptoms among HIV-seropositive women: longitudinal analysis from the HIV Epidemiology Research Study. JAMA 285:1466–1474, 2001
14.
Hessol NA, Kalinowski A, Benning L, et al.: Mortality among participants in the Multicenter AIDS Cohort Study and the Women’s Interagency HIV Study. Clinical Infectious Diseases 44:287–294, 2007
15.
French AL, Gawel SH, Hershow R, et al.: Trends in mortality and causes of death among women with HIV in the United States: a 10-year study. Journal of Acquired Immune Deficiency Syndromes 51:399–406, 2009
16.
Palepu A, Horton NJ, Tibbetts N, et al.: Uptake and adherence to highly active antiretroviral therapy among HIV-infected people with alcohol and other substance use problems: the impact of substance abuse treatment. Addiction 99:361–368, 2004
17.
Carrico AW, Bangsberg DR, Weiser SD, et al.: Psychiatric correlates of HAART utilization and viral load among HIV-positive impoverished persons. AIDS 25:1113–1118, 2011
18.
Yun LW, Maravi M, Kobayashi JS, et al.: Antidepressant treatment improves adherence to antiretroviral therapy among depressed HIV-infected patients. Journal of Acquired Immune Deficiency Syndromes 38:432–438, 2005
19.
Coleman SM, Blashill AJ, Gandhi RT, et al.: Impact of integrated and measurement-based depression care: clinical experience in an HIV clinic. Psychosomatics 53:51–57, 2012
20.
Hoang T, Goetz MB, Yano EM, et al.: The impact of integrated HIV care on patient health outcomes. Medical Care 47:560–567, 2009
21.
DeLorenze GN, Satre DD, Quesenberry CP, et al.: Mortality after diagnosis of psychiatric disorders and co-occurring substance use disorders among HIV-infected patients. AIDS Patient Care and STDs 24:705–712, 2010
22.
Soller M, Kharrazi N, Prentiss D, et al.: Utilization of psychiatric services among low-income HIV-infected patients with psychiatric comorbidity. AIDS Care 23:1351–1359, 2011
23.
Taylor SL, Burnam MA, Sherbourne C, et al.: The relationship between type of mental health provider and met and unmet mental health needs in a nationally representative sample of HIV-positive patients. Journal of Behavioral Health Services and Research 31:149–163, 2004
24.
Weaver MR, Conover CJ, Proescholdbell RJ, et al.: Utilization of mental health and substance abuse care for people living with HIV/AIDS, chronic mental illness, and substance abuse disorders. Journal of Acquired Immune Deficiency Syndromes 47:449–458, 2008
25.
Andersen R, Newman JF: Societal and individual determinants of medical care utilization in the United States. Milbank Memorial Fund Quarterly: Health and Society 51:95–124, 1973
26.
Satre DD, Knight BG, Dickson-Fuhrmann E, et al.: Predictors of alcohol-treatment seeking in a sample of older veterans in the GET SMART program. Journal of the American Geriatrics Society 51:380–386, 2003
27.
Dhingra SS, Zack M, Strine T, et al.: Determining prevalence and correlates of psychiatric treatment with Andersen’s behavioral model of health services use. Psychiatric Services 61:524–528, 2010
28.
Bruwer B, Sorsdahl K, Harrison J, et al.: Barriers to mental health care and predictors of treatment dropout in the South African Stress and Health Study. Psychiatric Services 62:774–781, 2011
29.
Carragher N, Adamson G, Bunting B, et al.: Treatment-seeking behaviours for depression in the general population: results from the National Epidemiologic Survey on Alcohol and Related Conditions. Journal of Affective Disorders 121:59–67, 2010
30.
Wang PS, Lane M, Olfson M, et al.: Twelve-month use of mental health services in the United States: results from the National Comorbidity Survey Replication. Archives of General Psychiatry 62:629–640, 2005
31.
Weisner C, Matzger H, Tam T, et al.: Who goes to alcohol and drug treatment? Understanding utilization within the context of insurance. Journal of Studies on Alcohol 63:673–682, 2002
32.
Orwat J, Saitz R, Tompkins CP, et al.: Substance abuse treatment utilization among adults living with HIV/AIDS and alcohol or drug problems. Journal of Substance Abuse Treatment 41:233–242, 2011
33.
Burnam MA, Bing EG, Morton SC, et al.: Use of mental health and substance abuse treatment services among adults with HIV in the United States. Archives of General Psychiatry 58:729–736, 2001
34.
Himelhoch S, Josephs JS, Chander G, et al.; HIV Research Network: use of outpatient mental health services and psychotropic medications among HIV-infected patients in a multisite, multistate study. General Hospital Psychiatry 31:538–545, 2009
35.
Pisu M, Cloud G, Austin S, et al.: Substance abuse treatment in an urban HIV clinic: who enrolls and what are the benefits? AIDS Care 22:348–354, 2010
36.
Krieger N: Overcoming the absence of socioeconomic data in medical records: validation and application of a census-based methodology. American Journal of Public Health 82:703–710, 1992
37.
Weisner C, Mertens J, Parthasarathy S, et al.: Integrating primary medical care with addiction treatment: a randomized controlled trial. JAMA 286:1715–1723, 2001
38.
Brown C, Barner J, Bohman T, et al.: A multivariate test of an expanded Andersen Health Care utilization model for complementary and alternative medicine (CAM) use in African Americans. Journal of Alternative and Complementary Medicine 15:911–919, 2009
39.
Yoon J, Bernell SL: The role of adverse physical health events on the utilization of mental health services. Health Services Research 48:175–194, 2013
40.
Chi FW, Satre DD, Weisner C: Chemical dependency patients with cooccurring psychiatric diagnoses: service patterns and 1-year outcomes. Alcoholism, Clinical and Experimental Research 30:851–859, 2006
41.
Mertens JR, Lu YW, Parthasarathy S, et al.: Medical and psychiatric conditions of alcohol and drug treatment patients in an HMO: comparison with matched controls. Archives of Internal Medicine 163:2511–2517, 2003
42.
Garnick DW, Lee MT, Chalk M, et al.: Establishing the feasibility of performance measures for alcohol and other drugs. Journal of Substance Abuse Treatment 23:375–385, 2002
43.
Summary table of measures, product lines and changes: HEDIS 2013 measures. Washington, DC, National Committee for Quality Assurance, 2012. Available at www.ncqa.org/Portals/0/HEDISQM/HEDIS%202011/SUMMARY_TABLE_OF_MEASURES_for_HEDIS_2012.pdf.
44.
Andersen RM: Revisiting the behavioral model and access to medical care: does it matter? Journal of Health and Social Behavior 36:1–10, 1995
45.
Hulka BS, Wheat JR: Patterns of utilization: the patient perspective. Medical Care 23:438–460, 1985
46.
Mojtabai R, Crum RM: Perceived unmet need for alcohol and drug use treatments and future use of services: results from a longitudinal study. Drug and Alcohol Dependence 127:59–64, 2012
47.
McCabe SE, West BT, Hughes TL, et al.: Sexual orientation and substance abuse treatment utilization in the United States: results from a national survey. Journal of Substance Abuse Treatment 44:4–12, 2012
48.
Green-Hennessy S: Factors associated with receipt of behavioral health services among persons with substance dependence. Psychiatric Services 53:1592–1598, 2002
49.
Hennessy KD, Green-Hennessy S, Marshall CC: Reported mental health specialty care in the 2010 HealthStyles Survey. Psychiatric Services 63:306, 2012
50.
Kessler RC, Demler O, Frank RG, et al.: Prevalence and treatment of mental disorders, 1990 to 2003. New England Journal of Medicine 352:2515–2523, 2005
51.
Mojtabai R: Unmet need for treatment of major depression in the United States. Psychiatric Services 60:297–305, 2009
52.
Hooshyar D, Goulet J, Chwastiak L, et al.: Time to depression treatment in primary care among HIV-infected and uninfected veterans. Journal of General Internal Medicine 25:656–662, 2010
53.
Wang PS, Demler O, Olfson M, et al.: Changing profiles of service sectors used for mental health care in the United States. American Journal of Psychiatry 163:1187–1198, 2006
54.
Mertens JR, Chi FW, Sterling S, et al. Alcohol SBIRT implementation in adult primary care: preliminary results from an integrated health care delivery system. Presented at INEBRIA, Boston, Sept 21–23, 2011
55.
Satre D, DeLorenze GN, Quesenberry CP Jr, et al: Integrating substance use and psychiatric disorder treatment for patients with HIV. Presented at annual Research Society on Alcoholism Scientific Meeting, San Francisco, June 23–27, 2012
56.
Unützer J, Katon W, Callahan CM, et al.: Collaborative care management of late-life depression in the primary care setting: a randomized controlled trial. JAMA 288:2836–2845, 2002
57.
Hunkeler EM, Hargreaves WA, Fireman B, et al.: A Web-delivered care management and patient self-management program for recurrent depression: a randomized trial. Psychiatric Services 63:1063–1071, 2012
58.
Satre DD, Campbell CI, Gordon NS, et al.: Ethnic disparities in accessing treatment for depression and substance use disorders in an integrated health plan. International Journal of Psychiatry in Medicine 40:57–76, 2010
Information & Authors
Information
Published In
Cover: Summer Afternoon, by William Dean Fausett, 1943. Oil and tempera on masonite, 30 × 38 inches. Collection of the San Antonio Art League and Museum, San Antonio, Texas.
History
Published in print: August 2013
Published online: 15 October 2014
Authors
Metrics & Citations
Metrics
Citations
Export Citations
If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download.
For more information or tips please see 'Downloading to a citation manager' in the Help menu.
View Options
View options
PDF/EPUB
View PDF/EPUBGet Access
Login options
Already a subscriber? Access your subscription through your login credentials or your institution for full access to this article.
Personal login Institutional Login Open Athens loginNot a subscriber?
PsychiatryOnline subscription options offer access to the DSM-5-TR® library, books, journals, CME, and patient resources. This all-in-one virtual library provides psychiatrists and mental health professionals with key resources for diagnosis, treatment, research, and professional development.
Need more help? PsychiatryOnline Customer Service may be reached by emailing [email protected] or by calling 800-368-5777 (in the U.S.) or 703-907-7322 (outside the U.S.).