The effects of health sector market factors and vulnerable group membership on access to alcohol, drug, and mental health care

Health Services Research, June, 2007 by Susan E. Stockdale, Lingqi Tang, Lily Zhang, Thomas R. Belin, Kenneth B. Wells

Access to care for alcohol, drug, and mental health (ADM) conditions is the outcome of a complex dynamic involving demand and supply factors at both the system and individual levels. While some research posits that access for everyone in the community may be compromised as poverty and population racial/ethnic distribution lead to reductions in community-wide service availability, other research suggests that certain vulnerable subgroups (nonwhites, the elderly, the poor, and the uninsured) will be disproportionately, and negatively, affected (IOM 2003). Although a number of studies have examined individual pieces of this dynamic, few if any have explored at a national level the combined effects of community-level socioeconomic disadvantage (i.e., poverty and racial/ethnic distribution), safety net development, service availability, and individual risk factors on access to ADM care. Using a large national sample, this study tests a conceptual model of access based on the expansion of Andersen's Behavioral Model for vulnerable populations (Gelberg, Andersen, and Leake 2000) and explores whether certain health sector market conditions compound disparities for vulnerable subgroups.

CONCEPTUAL MODEL

Andersen's original behavioral model, developed in the 1960s, posited that health services use is a function of predisposing, enabling, and need factors (Andersen 1995). A more recent expansion of the model to explain utilization and outcomes for vulnerable populations distinguishes between traditional and vulnerable domains within predisposing, enabling, and need factors (Gelberg, Andersen, and Leake 2000). Based on the literature about problems affecting utilization of care by the homeless, Andersen and colleagues add new "vulnerability" predictors. More recent iterations of the behavioral model also point to the importance of including enabling and predisposing factors, as well as a vulnerability domain, at the community level; such a model has not been developed for ADM services use. In addition, the possibility of cross-level interactions between community and individual levels has not been well conceptualized within Andersen's model. By including cross-level interactions between community-level vulnerability factors and individual-level characteristics, we can determine if some vulnerable subgroups are more negatively impacted by unfavorable health sector market conditions.

To develop a framework to explain ADM treatment utilization with a particular focus on the poor, uninsured, elderly, and nonwhites, we follow Gelberg, Andersen, and Leake's (2000) approach and turn to literature on ADM service utilization to identify important vulnerability factors at the community level. The IOM and others argue that community socioeconomic disadvantage, particularly poverty (Chow, Jaffee, and Snowden 2003) and percent nonwhite population (Chandra and Skinner 2003), creates unfavorable health sector market conditions that lead to reduced access to services. Our model incorporates these community-level social structure and demographic variables as predisposing vulnerability factors, along with traditional predisposing factors such as individual-level race/ethnicity, education, employment, and marital status.

Andersen (1995) has suggested that broadening the scope of community enabling factors beyond traditional service availability measures (physicians per capita and number of facilities) to include more information about the health services sector would improve the ability of the behavioral model to explain service use. While greater service availability at the community level (i.e., psychiatrists per capita, MDs per capita, inpatient psychiatric units) has been associated with increased access and use of mental health services (Hendryx, Urdaneta, and Borders 1995), two additional health sector market factors identified in the literature may be particularly important for explaining ADM service use by vulnerable subgroups: community uninsurance/safety net development and HMO presence. As suggested by the literature discussed below, in addition to traditional service availability measures, our conceptual model expands the community-level enabling domain to include the percent of the population uninsured and HMO market penetration as additional vulnerability factors.

Studies of access to mental health care and treatment of mental disorders show that people living in communities with a better developed safety net for the uninsured (more public health collaborations with state and local community agencies, higher levels of public insurance coverage) have greater access to mental health care (Hendryx and Ahem 2001). Conversely, high community uninsurance rates may overburden existing services with uncompensated care, forcing providers, hospitals, and clinics to limit access to services (IOM 2003). This shortage of charity care is particularly likely to decrease access to care for low-income uninsured persons (Cunningham 1999).

Evidence of the effects of HMO market penetration on access to care is less clear. Although several studies demonstrate better initial access to health and mental health services under managed care, including behavioral health "carve-outs" (Sturm 1997; Goldman, McCulloch, and Sturm 1998; Grazier and Eselius 1998; Grazier et al. 1999; Gresenz, Stockdale, and Wells 2000; Hendryx et al. 2002), some of these also indicate that intensity or volume of services decreases. One study found that although the introduction of managed care did not affect access to mental health specialty care, patients in more managed plans were less likely to receive a referral to specialty mental health care (Grembowski et al. 2002), and another study conducted in Ohio found worse access to health care in areas with higher HMO market penetration (Litaker and Cebul 2003). In addition, a few studies have raised concerns about strategies used by managed care to reduce costs, such as restricting number of outpatient visits and specialty care visits, arguing that lower costs per plan member may indicate restricted access to services (Weissman et al. 2000; Wilk et al. 2005).