Literature Collection

OBJECTIVES: Understanding the epidemiology of treatment for patients with co-occurring depression and obesity can inform care quality. The objective of the study was to identify how patients with obesity and newly diagnosed depression are treated and whether treatment is associated with body mass index change. METHODS: This cohort study included adults with obesity and newly diagnosed depression who had ≥2 primary care visits between 2015 and 2020 at a large integrated health system. Treatment within 45 days of a depression diagnosis was identified, including antiobesity medication and group or individual weight management visits (eg, bariatric medicine); antidepressant prescriptions; or visits with a psychologist, social worker, or psychiatrist. Patients were grouped into treatment groups: none, depression only, weight management only, or both. Generalized structural equation models were used to identify the association between treatment group and body mass index change at 6 and 12 months, accounting for demographic and health characteristics as fixed variables and clinician identifier as a random variable. RESULTS: Of the 13,729 adults, 43% received depression treatment, 3% received weight management treatment, and 4% received both. Individuals who received weight management treatment only lost more weight at 6 months (β = -1.0 kg/m(2)) and 12 months (β = -1.07 kg/m(2)) than individuals with no treatment. Individuals who had both treatments lost more weight than individuals with depression treatment alone (6 months: β = -1.07 kg/m(2); 12 months: β = -1.21 kg/m(2)) and underwent a similar average change than those who received weight management treatment alone (P > 0.05). CONCLUSIONS: There is an opportunity to increase treatment for obesity among patients with newly diagnosed depression.

PURPOSE: This article shows how financial health serves as an integral component of behavioral health beyond only a social determinant. It presents a framework conceptualizing financial health through three dimensions - financial precarity, efficacy, and well-being - and demonstrates how these interact with established behavioral health domains. MATERIALS AND METHODS: The paper integrates several theoretical perspectives with empirical evidence from social work, psychology, and financial therapy literature. It synthesizes research on financial assessment tools and evidence-based interventions that can be integrated into care settings. RESULTS: Evidence demonstrates multidirectional relationships between financial and other behavioral health domains. Whereas financial precarity correlates with worse behavioral health conditions, financial efficacy serves as a protective factor. Intervention research shows that addressing financial concerns directly significantly improves both financial well-being outcomes and other behavioral health indicators, including healthcare engagement and medication adherence. DISCUSSION: Conceptualizing financial health as a behavioral health domain enhances assessment and intervention practices in integrated care settings. This approach enables practitioners to identify and address specific financial behaviors that interact with other health domains, creates opportunities for interprofessional collaboration, and provides strategies for addressing health disparities. CONCLUSION: By positioning financial health as a type of behavioral health, practitioners can more effectively address complex interrelationships between financial circumstances and health outcomes. This perspective aligns with social work's person-in-environment approach while providing actionable strategies for improving overall well-being through simultaneous attention to financial and other behavioral health concerns.

BACKGROUND: Office-Based Opioid Treatment (OBOT) is a delivery model which seeks to make medications for opioid use disorder (MOUD), particularly buprenorphine, widely available in general medical clinics and offices. Despite evidence supporting its effectiveness and cost-effectiveness, uptake of the OBOT model has been relatively slow. One important barrier to faster diffusion of OBOT may be the financial challenges facing clinics that could adopt it. METHODS: We review key features and variants of the OBOT model, then discuss different approaches that have been used to fund it, and the findings from previous economic analyses of OBOT's impact on organizational finances. We conclude by discussing the implications of these analyses for the financial sustainability of the OBOT delivery model. RESULTS: Like other novel services, OBOT poses challenges for providers due to its reliance on services which are 'non-billable' in a fee-for-service environment. A variety of approaches exist for covering the non-billable costs, but which approaches are feasible depends on local payer policies. The scale of the challenges varies with clinic size, organizational affiliations and the policies of the state where the clinic operates. Small clinics in a purely fee-for-service environment may be particularly challenged in pursuing OBOT, given the need to fund a dedicated staff and extra administrative work. The current pandemic may pose both opportunities and challenges for the sustainability of OBOT, with expanded access to telemedicine, but also uncertainty about the durability of the expansion. CONCLUSION: The reimbursement environment for OBOT delivery varies widely around the US, and is evolving as Medicare (and possibly other payers) introduce alternative payment approaches. Clinics considering adoption of OBOT are well advised to thoroughly investigate these issues as they make their decision. In addition, payers will need to rethink how they pay for OBOT to make it sustainable.