PROJECT SUMMARY Individuals with serious mental illness (SMI) are three times more likely to die prematurely than the general population. Sixty percent of this premature death is attributable to inadequate care of chronic, co-morbid medical conditions. A growing proportion of patients with SMI receive care in accountable care organizations (ACOs) – health care delivery and finance systems, in which global payments and quality benchmarks are used to incentivize quality care and lower spending. An increasing number of states are implementing ACO models in their Medicaid programs, the primary source of health insurance for low-income Americans with SMI. Medicaid ACOs exist in 12 states, caring for over 6% of the Medicaid population. Medicaid ACOs have the potential to both improve and worsen access to, and quality of, care for low-income adults with SMI. While financial structures that incentivize care coordination and programs that address health-related social needs likely benefit those with SMI, inadequate global payments that fail to account fully for social adversities such as homelessness could result in lower quality care. Certain features of Medicaid ACOs, e.g. leadership structure or ACO size, may amplify the benefits or drawbacks of the ACO model for patients with SMI. Evidence from Medicare ACOs has shown that smaller, provider-led ACOs and those serving a lower proportion of socially- vulnerable patients perform better in terms of quality. However, no evidence exists on how Medicaid ACO characteristics affect quality of care or the care experience of SMI adults. Since Medicaid ACOs are rapidly proliferating, filling this evidence gap is critical and can inform the evolution of the ACO model to better achieve the goal of mental health parity. In this K23 research plan, we propose to identify features of Medicaid ACOs (e.g. provider-led vs. hospital-led ACOs) that produce the highest quality ACO care for adults with SMI. We will undertake this research objective in three critical domains. First, we will study whether certain ACO types tend to drop patients with SMI, a practice known as favorable risk selection (or “cherry-picking”). This phenomenon can cause instability of ACO enrollment for patients, itself a marker of lower quality care. Second, we will compare care access and quality among adults receiving care in different ACO types. Lastly, we will use mixed methods to examine the care experiences of adults with SMI receiving care in different ACO types, through in-depth interviews and subsequent integration of qualitative and quantitative findings. For the first two aims, we will use Massachusetts All-Payer Claims Data and leverage the state’s unique auto- assignment mechanism as a natural experiment to study favorable risk selection, access, and quality. Auto- assignment refers to Medicaid randomly assigning individuals to ACOs, allowing us to compare outcomes across ACO types without selection bias caused by patients self-selecting their ACO affiliation. The goal of my K23 research is to guide policymakers and hospital administrators in shaping the Medicaid ACO model to produce more stable, higher-quality ACO care for patients with SMI.

PROJECT NARRATIVE An increasing number of patients with serious mental illness receive care in Medicaid Accountable Care Organizations (ACOs), an alternative payment model in which global payments and quality benchmarks are used to incentivize quality and lower spending, but little evidence exists on quality of ACO care for this patient population. We propose to identify features of Medicaid ACOs (e.g. provider-led vs. hospital-led ACOs) that produce the highest quality ACO care for adults with serious mental illness. We will compare stability of enrollment, care quality, and patient experience between differing ACO types using mixed methods, including quantitative analysis of claims data and qualitative interviews with patients and case managers.