RESUMO
BACKGROUND: To bring evidence-based interventions (EBIs) to individuals with behavioral health needs, psychosocial interventions must be delivered at scale. Despite an increasing effort to implement effective treatments in communities, most individuals with mental health and behavioral problems do not receive EBIs. We posit that organizations that commercialize EBIs play an important role in disseminating EBIs, particularly in the USA. The behavioral health and implementation industry is growing, bringing the implementation field to an important inflection point: how to scale interventions to improve access while maintaining EBI effectiveness and minimizing inequities in access to psychosocial intervention. MAIN BODY: We offer a first-hand examination of five illustrative organizations specializing in EBI implementation: Beck Institute for Cognitive Behavioral Therapy; Incredible Years, Inc.; the PAXIS Institute; PracticeWise, LLC; and Triple P International. We use the Five Stages of Small Business Growth framework to organize themes. We discuss practical structures (e.g., corporate structures, intellectual property agreements, and business models) and considerations that arise when trying to scale EBIs including balancing fidelity and reach of the intervention. Business models consider who will pay for EBI implementation and allow organizations to scale EBIs. CONCLUSION: We propose research questions to guide scaling: understanding the level of fidelity needed to maintain efficacy, optimizing training outcomes, and researching business models to enable organizations to scale EBIs.
Assuntos
Medicina Baseada em Evidências , Intervenção Psicossocial , Humanos , Serviços de Saúde , Organizações , Saúde MentalRESUMO
The New York Delivery System Reform Incentive Payment (DSRIP) waiver was viewed as a prototype for Medicaid and safety net redesign waivers in the Affordable Care Act (ACA) era. After the insurance expansions of the ACA were implemented, it was apparent that accountability, value, and quality improvement would be priorities in future waivers in many states. Despite New York's distinct provider relationships, previous coverage expansions, and local and state politics, it is important to understand the key characteristics of the waiver so that other states can learn how to better incorporate value-based arrangements into future waivers or attempts to limit spending under proposed Medicaid per-capita caps or block grants. In this article, we examine the New York DSRIP waiver by drawing on its design, early experiences, and evolution to inform recommendations for the future renewal, implementation, and expansion of redesigned or transformational Medicaid waivers.
Assuntos
Reembolso de Incentivo/economia , Reembolso de Incentivo/organização & administração , Reembolso de Incentivo/tendências , Planos Governamentais de Saúde/economia , Planos Governamentais de Saúde/organização & administração , Reforma dos Serviços de Saúde/economia , Gastos em Saúde , Programas de Assistência Gerenciada/economia , Programas de Assistência Gerenciada/legislação & jurisprudência , Programas de Assistência Gerenciada/tendências , Medicaid/economia , Medicaid/legislação & jurisprudência , Medicaid/tendências , New York , Patient Protection and Affordable Care Act , Qualidade da Assistência à Saúde , Provedores de Redes de Segurança , Estados Unidos , Seguro de Saúde Baseado em Valor/economia , Seguro de Saúde Baseado em Valor/organização & administraçãoRESUMO
OBJECTIVES: Cohen's kappa coefficient is presently a standard tool for the analysis of agreement on a binary outcome between two tests. In view of the ubiquity of the use of sensitivity, specificity, raw agreement and kappa in clinical studies, clearly it is advantageous to have a useful analytic relation connecting these measures of agreement. METHODS: We elaborate on previous work, comment on other results appearing in the literature and discuss analytic formulas relevant to various problems connecting specificity, sensitivity and kappa. RESULTS: For selected values of kappa that range from good to excellent, a graph of the curves representing minimal pairs of sensitivity and specificity is provided. CONCLUSIONS: The analytic formulas and graph could be potentially useful to clinicians and biostatisticians in better interpreting the outcomes of an alternative diagnostic test whenever the measures sensitivity, specificity and kappa are employed together.