Abstract: PREDICTORS OF MENTAL HEALTH NEED AND TREATMENT IN SAFETY NET PRIMARY CARE By: Kristen O’Loughlin, M.A. A thesis submitted in partial fulfillment of the requirements for the degree of Master of Science at Virginia Commonwealth University. Virginia Commonwealth University, 2020 Director: Bruce Rybarczyk, Ph.D. Professor, Department of Psychology Many mental health (MH) needs go unidentified in primary care, and certain patients appear to be at higher risk of needs going unidentified and subsequently untreated. Little is known about patterns of detection and treatment in clinics with integrated mental health services. The purpose of this study was to characterize the prevalence of MH needs and evaluate patient characteristics as predictors of both the presence of a MH need and type of MH services received. Subjects were patients receiving care at two safety net primary care clinics with integrated mental health services (N=816; 52.7% Latinx, 15.9% African American), and were classified as either having received integrated MH services in the previous year or as not. Sociodemographic and medical information was extracted from all medical records, and patients who had not received integrated MH services completed a MH needs assessment. The prevalences for depression, suicidal ideation, anxiety and PTSD were within expected ranges. Surprisingly, patient characteristics did not predict the presence of a MH need, though several characteristics predicted the type of MH treatment received. Patients were less likely to receive integrated MH services if they were older (χ2(1) = 7.36, p= .007), Hispanic/Latinx (χ2(1) = 7.97, p= .005), and/or partnered (χ2(1) = 20.65, p= .000). This study suggests that biases in detection of MH needs in integrated primary care Running head: PREDICTORS OF NEED AND TREATMENT 6 may be less pronounced than in non-integrated primary care. However, longstanding disparities in MH treatment may persevere in this newer model of primary care. Running head: PREDICTORS OF NEED AND TREATMENT 7 Predictors of Mental Health Need and Treatment in Safety Net Primary Care Background Untreated mental illness is a major economic and medical burden to the United States. Poor health outcomes have been directly linked to depression (Kinder et al., 2008), anxiety (ElGabalawy et al., 2014), and post-traumatic stress (Andersen et al., 2010; Felitti et al., 1998). Not surprisingly, these mental health needs are often present in patients that interact with the healthcare system at higher frequencies (Greene et al., 2016). Epidemiological research shows that psychiatric disorders are more prevalent in primary care settings than the general population. This puts primary care physicians in a unique position to identify mental health needs early on and connect their patients to appropriate treatment. Unfortunately, mental health services are often challenging for patients to attain even once a need has been identified. The majority of primary care physicians report difficulty in finding and arranging outpatient mental health services (Trude & Stoddard, 2003). Further, only a small percentage of patients follow-up on referrals. Additional barriers to connecting patients to the services they need are cost, stigma, (Mental Health: A Report of the Surgeon General, 1999) transportation, and other logistical barriers (Sadock et al., 2017). To combat these barriers, various forms of collaborative care models have been implemented coordinating care between primary care physicians (PCP) and mental health specialists. The integrated behavioral healthcare (IBHC) model is characterized by having psychologists housed within the primary care clinic, sharing space, medical files, and working collaboratively with physicians (American Psychiatric Association, 2016). This model is particularly efficient in providing populationfocused care for the community in that it is provides emergent, brief interventions on an asneeded basis (Bryan et al., 2009, 2012). Running head: PREDICTORS OF NEED AND TREATMENT 8 IBHC has recently gained significant support, propelling its expansion throughout healthcare systems. Expansion to safety net clinics is particularly important due to the great need for behavioral health services within the populations they serve. Safety net clinics are characterized as serving free or reduced cost services to patients regardless of health insurance status (Sadock et al., 2014). High-utilizer patients of these clinics tend to be low-income, insured by Medicaid or Medicare, and are faced with a high burden of mental health, social, and chronic medical conditions (Bell et al., 2017). Safety net clinics therefore serve a critical role in providing healthcare services to individuals who would otherwise experiences barriers to access. Behavioral health interventions delivered to patients within primary care clinics have shown to improve psychiatric symptoms and distress (Bryan et al., 2009, 2012; Corso et al., 2012; Landis et al., 2013; Mcfeature & Pierce, 2012; Sadock et al., 2017), improve health outcomes (Woltmann et al., 2012), and reduce overall healthcare costs (Jacob et al., 2012; Stephenson et al., 2019). It is clear that psychiatric distress can be effectively managed at a reasonable cost using brief evidence-based interventions within an IBHC model. However, to successfully manage these needs, physicians must first be able to identify patients with need and refer them to the behavioral health clinicians. Currently, research suggests that patients are not being identified in an equitable manner. In the following sections, I will summarize what is known about the prevalence of common psychiatric disorders in primary care, particularly safety net clinics, how well they are identified by physicians, and which patients are at increased risk of non-detection. Our knowledge of biases in physician detection and referral to behavioral health services must be incorporated into improving current integrated safety net clinics. IBHC will not be able to reach Running head: PREDICTORS OF NEED AND TREATMENT 9 its full potential until patients’ mental health needs are more frequently identified and subsequently more patients are connected to treatment.