Measuring Variation Across Dimensions of Integrated Care: The Maryland Medicaid Health Home Model

Scaling Interventions to Manage Chronic Disease: Innovative Methods at the Intersection of Health Policy Research and Implementation Science

Policy implementation is a key component of scaling effective chronic disease prevention and management interventions. Policy can support scale-up by mandating or incentivizing intervention adoption, but enacting a policy is only the first step. Fully implementing a policy designed to facilitate implementation of health interventions often requires a range of accompanying implementation structures, like health IT systems, and implementation strategies, like training. Decision makers need to know what policies can support intervention adoption and how to implement those policies, but to date research on policy implementation is limited and innovative methodological approaches are needed. In December 2021, the Johns Hopkins ALACRITY Center for Health and Longevity in Mental Illness and the Johns Hopkins Center for Mental Health and Addiction Policy convened a forum of research experts to discuss approaches for studying policy implementation. In this report, we summarize the ideas that came out of the forum. First, we describe a motivating example focused on an Affordable Care Act Medicaid health home waiver policy used by some US states to support scale-up of an evidence-based integrated care model shown in clinical trials to improve cardiovascular care for people with serious mental illness. Second, we define key policy implementation components including structures, strategies, and outcomes. Third, we provide an overview of descriptive, predictive and associational, and causal approaches that can be used to study policy implementation. We conclude with discussion of priorities for methodological innovations in policy implementation research, with three key areas identified by forum experts: effect modification methods for making causal inferences about how policies' effects on outcomes vary based on implementation structures/strategies; causal mediation approaches for studying policy implementation mechanisms; and characterizing uncertainty in systems science models. We conclude with discussion of overarching methods considerations for studying policy implementation, including measurement of policy implementation, strategies for studying the role of context in policy implementation, and the importance of considering when establishing causality is the goal of policy implementation research.

Systematic Review of Care Coordination Interventions Linking Health and Social Services for High-Utilizing Patient Populations

Recognizing that social factors influence patient health outcomes and utilization, health systems have developed interventions to address patients' social needs. Care coordination across the health care and social service sectors is a distinct and important strategy to address social determinants of health, but limited information exists about how care coordination operates in this context. To address this gap, the authors conducted a systematic review of peer-reviewed publications that document the coordination of health care and social services in the United States. After a structured elimination process, 25 publications of 19 programs were synthesized to identify patterns in care coordination implementation. Results indicate that patient needs assessment, in-person patient contact, and standardized care coordination protocols are common across programs that bridge health care and social services. Publications discussing these programs often provide limited detail on other key elements of care coordination, especially the nature of referrals and care coordinator caseload. Additional research is needed to document critical elements of program implementation and to evaluate program impacts.

Behavioral health home impact on transitional care and readmissions among adults with serious mental illness

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.

Association Between the Maryland Medicaid Behavioral Health Home Program and Cancer Screening in People With Serious Mental Illness

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.