Racial and Ethnic Disparities in SSRI Availability in Substance Abuse Treatment

Data were drawn from the National Treatment Center Study (NTCS), which focuses on the long-term adaptation of substance abuse treatment organizations to the environmental contexts in which they operate. The NTCS has several components, including nationally representative samples of specialty addiction treatment programs in the public and private sectors. The face-to-face interviews conducted with program administrators between mid-2002 and early 2004 represent the initial NTCS activity with the public-sector sample and the fourth such wave of data collection from the private-sector sample. The human subjects committee of the institutional review board at the University of Georgia approved the research design.

The NTCS uses a two-stage random sample of treatment programs. Separate samples were drawn for the public and private treatment center components. In both samples eligible facilities are community-based organizations that offer treatment for alcohol and drug problems and provide a level of care at least equivalent to structured outpatient programming as defined by the American Society of Addiction Medicine's patient placement criteria ( 35 ). Excluded from the study were counselors in private practice, halfway houses, required driving-under-the-influence programs or other driver education programs, correctional institutions, treatment facilities operated by the federal government, and units exclusively offering methadone maintenance services.

A sample of 450 private-sector programs was drawn in 1994 ( 36, 37 ). Over time, random sampling was used to select replacements for units that closed, became ineligible, or refused to participate, such that geographic stratification and a target sample of 400 were maintained. Private-sector programs were defined as those receiving less than 50% of their annual operating revenues from government block grants and contracts; the average private center received less than 9% of its revenues from such sources. The private sector included both for-profit and nonprofit programs. This study used data from those 403 private programs. The response rate for this wave of interviews was 88% of those that were sampled and eligible.

Using similar stratification and identification procedures, we selected a separate sample of public-sector treatment programs in early 2002. Eligibility rules were the same as for the private sample, except that public-sector programs were defined as receiving at least 51% of their annual operating revenues from federal, state, or local government grants or contracts; the average public center received nearly 80% of their revenues from these sources. The public-sector sample included a mixture of state and local government-owned facilities and nonprofits under private ownership. A total of 363 publicly funded treatment programs (80% response rate) were interviewed between mid-2002 and early 2004.

For both samples data were collected in face-to-face interviews with administrators and clinical directors who oversaw the substance abuse treatment services delivered by the organization. These interviews were conducted by trained members of the project staff. The average on-site interview lasted approximately 90 minutes.

The NTCS utilizes a longitudinal design that includes telephone follow-up interviews at six, 12, and 18 months after baseline face-to-face interviews. Our research drew from data collected during the first telephone follow-up interview. Of the 363 public centers, 326 (90%) participated in the follow-up; the rate of follow-up was 84% (N=339) among the private-sector sample.

In summary, these analyses relied on 665 centers that participated in both a baseline interview and a six-month follow-up interview. Pooled, unweighted data from these samples of private and public centers formed the basis for the analyses.

The dependent variable was availability of SSRI medications at the center. This measure was dichotomous (1, yes; 0, no) and was constructed on the basis of a series of items. First, administrators were asked if any client had ever been treated with SSRIs at the center. Administrators who answered yes were then asked additional questions; specifically, they were asked whether the center currently uses SSRIs to treat clients at the center. If administrators responded no, they were asked whether the center had discontinued use of SSRIs at the center. This follow-up question was used to ensure that centers were not erroneously coded as nonusers of SSRIs simply because no clients were receiving SSRI medications on the day of the interview.

The primary independent variables of interest were the percentages of clients at the center that represent racial or ethnic minority groups. Specifically, administrators reported the percentage of the center's African-American clients and the percentage of its Hispanic clients. These data were collected during a telephone follow-up interview six months after the face-to-face interview; the baseline interview included only an aggregate measure of racial-ethnic group representation in the center's caseload. (Specifically, administrators were asked in the baseline interview, "Typically, what proportion of your total caseload are racial and/or ethnic minorities?") Comparison of the data from the baseline interview and the six-month follow-up interview suggests that the racial-ethnic composition of the center's caseload was reasonably stable during this six-month period. When the percentages of African-American and Hispanic clients (from the six-month follow-up) were summed and this additive measure was compared with the baseline aggregate measure of racial-ethnic composition, the correlation was .80.

Center type was measured in four categories that integrated ownership, predominant sources of funding, and profit status. From the private center sample, facilities were coded as for profit or as privately funded nonprofit. Public centers were differentiated by ownership, such that centers were characterized as government owned or as publicly funded nonprofit. In these analyses, privately funded nonprofit treatment centers represent the reference category.

The measure of organizational affiliation categorized centers on the basis of whether they were affiliated with a hospital or mental health center or were freestanding (the reference category). This measure integrated information collected during the on-site interviews (such as ownership by or affiliation with a hospital) and data derived from the Substance Abuse and Mental Health Services Administration (SAMHSA) Mental Health Services Locator (www.mentalhealth.samhsa.gov/databases). The locator database was used to categorize sampled centers; about 25% of the sample identified themselves to SAMHSA as a mental health service provider. The database further categorized these centers as general hospitals, psychiatric hospitals, substance abuse organizations, multisite mental health organizations, and outpatient clinics. Facilities listed in the database as hospitals or as substance abuse organizations retained their hospital or freestanding code in our data set. However, facilities identifying themselves as multisite or outpatient mental health facilities were coded as mental health centers for these analyses.

Two geographical measures were included in the model of SSRI availability. First, the state in which the center was located was coded into four geographic regions: Northeast, Midwest, South (reference), and West. Second, a dichotomous measure of location in a rural county was constructed on the basis of whether the county was within a metropolitan statistical area. Both measures use current U.S. Census area definitions.

Other organizational characteristics included center age, center size, accreditation status, physician availability, presence of a dual diagnosis program offering integrated care, and adherence to a 12-step treatment model. Center age was measured in years, and center size was measured by the number of full-time-equivalent employees; both measures were natural log-transformed to correct for substantial skew. Accreditation by the Joint Commission on Accreditation of Healthcare Organizations or the Commission on Rehabilitation Facilities (1, yes; 0, no) was included as a proxy measure of center quality ( 38 ). A set of dummy variables categorized the type of physician availability at the center: at least one physician on staff, at least one physician on contract, and no physicians (reference). Center administrators were asked whether they offered a dual diagnosis program that addressed both the mental health and substance abuse needs of clients (1, integrated care program; 0, no integrated care program). Finally, a dichotomous measure was included to identify whether the center was based on a 12-step model of recovery (1, yes; 0, no).

Logistic regression was used to estimate three models of SSRI availability in specialty substance abuse treatment centers because of the dichotomous nature of the dependent variable ( 39 ). The bivariate association between the percentage of racial-ethnic minority clients and the likelihood of SSRI availability was presented in model 1. In model 2, center type and basic organizational characteristics were added to the regression equation. In model 3, measures related to treatment inputs, including physician availability, availability of integrated care, and the 12-step orientation of the center, were added to the analysis. Unstandardized coefficients and standard errors are reported as well as several measures of model fit, including likelihood ratio chi square tests, McKelvey and Zavoina's R ², and the Bayesian information criterion (BIC). McKelvey and Zavoina's R ² attempts to model the proportion of variation explained by the independent variables and has properties that are preferable to other pseudo-R ² measures ( 40, 41 ). More negative BIC values also indicate improvement in model fit ( 42 ).

All three models used the subsample of 578 centers that provided complete information on all measures. Additional analyses (not shown) were undertaken to examine possible sources of bias because of missing data. First, centers with complete data were compared with those that were excluded in the models of SSRI availability because of missing data. Chi square and t tests were used to compare included and excluded centers on all variables. The only significant difference was in the natural log-transformed measure of full-time employees. Centers providing complete data were smaller (mean±SD=2.80±1.12) than centers that were excluded because of missing data (3.06±1.34; t=2.50, df=751, p<.01).

An additional source of missing data was related to the six-month follow-up interview, which included the measures related to racial-ethnic caseload composition; some centers did not complete this interview, whereas others were unable to provide specific information on the racial-ethnic composition of the center's caseload. A logistic regression analysis was performed where the dependent variable was coded 1, indicating missing data on the race-ethnicity variables, or 0, indicating that the center provided these data. Neither the measure of SSRI availability nor the other organization-level measures were associated with the likelihood of missing race-ethnicity data.