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Background: Cancer is the second leading cause of death for people with serious mental illness (SMI), such as schizophrenia and bipolar disorder. People with SMI receive cancer screenings at lower rates than the general population., Aims: We sought to identify factors associated with cancer screening in a publicly insured population with SMI and stratified by race, a factor itself linked with differential rates of cancer screening., Materials and Methods: We used Maryland Medicaid administrative claims data (2010-2018) to examine screening rates for cervical cancer (N = 40,622), breast cancer (N = 9818), colorectal cancer (N = 19,306), and prostate cancer (N = 4887) among eligible Black and white enrollees with SMI. We examined individual-level socio-demographic and clinical factors, including co-occurring substance use disorder, medical comorbidities, psychiatric diagnosis, obstetric-gynecologic and primary care utilization, as well as county-level characteristics, including metropolitan status, mean household income, and primary care workforce capacity. Generalized estimating equations with a logit link were used to examine the characteristics associated with cancer screening., Results: Compared with white enrollees, Black enrollees were more likely to receive screening for cervical cancer (AOR: 1.18; 95% CI: 1.15-1.22), breast cancer (AOR: 1.27; 95% CI: 1.19-1.36), and colorectal cancer (AOR: 1.07; 95% CI: 1.02-1.13), while similar rates were observed for prostate cancer screening (AOR: 1.06; 95% CI: 0.96-1.18). Primary care utilization and longer Medicaid enrollment were positively associated with cancer screening while co-occurring substance use disorder was negatively associated with cancer screening., Conclusion: Improving cancer screening rates among populations with SMI should focus on facilitating continuous insurance coverage and access to primary care., (© 2021 John Wiley & Sons Ltd.)

Objective: To evaluate the impact of Maryland's behavioral health homes (BHHs) on receipt of follow-up care and readmissions following hospitalization among Medicaid enrollees with serious mental illness (SMI)., Data Sources: Maryland Medicaid administrative claims for 12 232 individuals., Study Design: Weighted marginal structural models were estimated to account for time-varying exposure to BHH enrollment and time-varying confounders. These models compared changes over time in outcomes among BHH and comparison participants. Outcome measures included readmissions and follow-up care within 7 and 30 days following hospitalization., Data Collection/extraction Methods: Eligibility criteria included continuous enrollment in Medicaid for the first two years of the study period; 21-64 years; and use of psychiatric rehabilitation services., Principal Findings: Over three years, BHH enrollment was associated with 3.8 percentage point (95% CI: 1.5, 6.1) increased probability of having a mental health follow-up service within 7 days of discharge from a mental illness-related hospitalization and 1.9 percentage point (95% CI: 0.0, 3.9) increased probability of having a general medical follow-up within 7 days of discharge from a somatic hospitalization. BHHs had no effect on probability of readmission., Conclusions: BHHs may improve follow-up care for Medicaid enrollees with SMI, but effects do not translate into reduced risk of readmission., (© Health Research and Educational Trust.)

Background: Nineteen US states and D.C. have used the Affordable Care Act Medicaid health home waiver to create behavioral health home (BHH) programs for Medicaid beneficiaries with serious mental illness (SMI). BHH programs integrate physical healthcare management and coordination into specialty mental health programs. No studies have evaluated the effects of a BHH program created through the Affordable Care Act waiver on cardiovascular care quality among people with SMI., Objective: To study the effects of Maryland's Medicaid health home waiver BHH program, implemented October 1, 2013, on quality of cardiovascular care among individuals with SMI., Design: Retrospective cohort analysis using Maryland Medicaid administrative claims data from July 1, 2010, to September 30, 2016. We used marginal structural modeling with inverse probability of treatment weighting to account for censoring and potential time-dependent confounding., Participants: Maryland Medicaid beneficiaries with diabetes or cardiovascular disease (CVD) participating in psychiatric rehabilitation programs, the setting in which BHHs were implemented. To qualify for psychiatric rehabilitation programs, individuals must have SMI. The analytic sample included BHH and non-BHH participants, N = 2605 with diabetes and N = 1899 with CVD., Main Measures: Healthcare Effectiveness Data and Information Set (HEDIS) measures of cardiovascular care quality including annual receipt of diabetic eye and foot exams; HbA1c, diabetic nephropathy, and cholesterol testing; and statin therapy receipt and adherence among individuals with diabetes, as well as HEDIS measures of annual receipt of cholesterol testing and statin therapy and adherence among individuals with CVD., Key Results: Relative to non-enrollment, enrollment in Maryland's BHH program was associated with increased likelihood of eye exam receipt among individuals with SMI and co-morbid diabetes, but no changes in other care quality measures., Conclusions: Additional financing, infrastructure, and implementation supports may be needed to realize the full potential of Maryland's BHH to improve cardiovascular care for people with SMI.

Objective: This study evaluated the association of the Maryland Medicaid behavioral health home (BHH) integrated care program with cancer screening., Methods: Using administrative claims data from October 2012 to September 2016, the authors measured cancer screening among 12,176 adults in Maryland's psychiatric rehabilitation program who were eligible for cervical (N=6,811), breast (N=1,658), and colorectal (N=3,430) cancer screening. Marginal structural modeling was used to examine the association between receipt of annual cancer screening and whether participants had ever enrolled in a BHH (enrolled: N=3,298, 27%; not enrolled: N=8,878, 73%)., Results: Relative to nonenrollment, BHH enrollment was associated with increased screening for cervical and breast cancer but not for colorectal cancer. Predicted annual rates remained low, even in BHHs., Conclusions: Despite estimates of improvements in cervical and breast cancer screening after BHH implementation, cancer screening rates remained suboptimal. Broader cancer screening interventions are needed to improve cancer screening for people with mental illness.

Behavioral health homes, shown to improve receipt of evidence-based medical services among people with serious mental illness in randomized clinical trials, have had limited results in real-world settings; nonetheless, these programs are spreading rapidly. To date, no studies have considered what set of policies is needed to support effective implementation of these programs. As a first step toward identifying an optimal set of policies to support behavioral health home implementation, we use the policy ecology framework to map the policies surrounding Maryland's Medicaid behavioral health home program. Results suggest that existing policies fail to address important implementation barriers.

Objectives: Behavioral health home (BHH) models have been developed to integrate physical and mental health care and address medical comorbidities for individuals with serious mental illnesses. Previous studies identified population health management capacity and coordination with primary care providers as key barriers to BHH implementation. This study examines the BHH leaders' perceptions of and organizational capacity to conduct these functions within the community mental health programs implementing BHHs in Maryland., Methods: Interviews and surveys were conducted with 72 implementation leaders and 627 front-line staff from 46 of 48 Maryland BHH programs. In-depth coding of the population health management and primary care coordination themes identified subthemes related to these topics., Results: BHH staff described cultures supportive of evidence-based practices, but limited ability to effectively perform population health management or primary care coordination. Tension between population health management and direct, clinical care, lack of experience, and state regulations for service delivery were identified as key challenges for population health management. Engaging primary care providers was the primary barrier to care coordination. Health information technology and staffing were barriers to both functions., Conclusions: BHHs face a number of barriers to effective implementation of core program elements. To improve programs' ability to conduct effective population health management and care coordination and meaningfully impact health outcomes for individuals with serious mental illness, multiple strategies are needed, including formalized protocols, training for staff, changes to financing mechanisms, and health information technology improvements.