Literature Collection
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Opioids & SU
The Literature Collection contains over 11,000 references for published and grey literature on the integration of behavioral health and primary care. Learn More
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Opioid use disorder (OUD) is highly prevalent among persons who are incarcerated. Medication treatment for opioid use disorder (MOUD), methadone, buprenorphine, and naltrexone, is widely used to treat OUD in the community. Despite MOUD's well-documented effectiveness in improving health and social outcomes, its use in American jails and prisons is limited.Several factors are used to justify limited access to MOUD in jails and prisons including: "uncertainty" of MOUD's effectiveness during incarceration, security concerns, risk of overdose from MOUD, lack of resources and institutional infrastructure, and the inability of people with OUD to provide informed consent. Stigma regarding MOUD also likely plays a role. While these factors are relevant to the creation and implementation of addiction treatment policies in incarcerated settings, their ethicality remains underexplored.Using ethical principles of beneficence/non-maleficence, justice, and autonomy, in addition to public health ethics, we evaluate the ethicality of the above list of factors. There is a two-fold ethical imperative to provide MOUD in jails and prisons. Firstly, persons who are incarcerated have the right to evidence-based medical care for OUD. Secondly, because jails and prisons are government institutions, they have an obligation to provide that evidence-based treatment. Additionally, jails and prisons must address the systematic barriers that prevent them from fulfilling that responsibility. According to widely accepted ethical principles, strong evidence supporting the health benefits of MOUD cannot be subordinated to stigma or inaccurate assessments of security, cost, and feasibility. We conclude that making MOUD inaccessible in jails and prisons is ethically impermissible.
OBJECTIVE: To evaluate the Mental Health and Primary Care Partnership (MaP) pilot program which operated in a metropolitan Melbourne setting in 2020. METHOD: Data collection included: surveys, interviews, file audits, and an evaluation of routinely collected data, with MaP consumers, their carers, GPs, Practice Managers and Nurses located in Boroondara, and MaP and Aged Person's Mental Health Service staff. RESULTS: Thirty-five consumers aged between 66 and 101 years old (of whom 63% were female) received support from the MaP program throughout its 12-month operation. Statistically significant improvements in outcome measures assessing for psychological distress and symptoms of mental illness were observed. Strengths of the program included the single referral pathway and the provision of services for those not meeting criteria to access tertiary mental health support. Consumers and clinicians made recommendations for service improvement including provision of a longer duration of care to consumers and greater integration of community and primary care. CONCLUSIONS: It is hoped that the learnings from the MaP pilot program can be used to guide future program development.
BACKGROUND: Integrated care is a promising strategy to advance system transformation, care coordination, equity, and better health outcomes. Health services and policy research can drive evidence-informed health system improvements but is often underutilized. To optimize the relevance and impact of integrated care research as a transformative lever for better health and system outcomes, the Canadian Institutes of Health Research's Institute of Health Services and Policy Research (CIHR-IHSPR) designed a large-scale, evidence-informed, community-engaged research funding initiative. This paper outlines the approach and methods used by CIHR-IHSPR and describes how they informed the design and development of Transforming Health with Integrated Care (THINC), a large-scale, impact-oriented research funding initiative that promotes the adoption and proliferation of integrated care in Canada. METHODS: A multi-method qualitative, community-engaged approach was used to inform the design of a research funding strategy. Key features of the approach included multiple evidence inputs (retrospective and prospective information from primary [key informant interviews, focus groups, and a workshop] and secondary [CIHR funding data and literature review] sources), pan-Canadian reach of community engagement, involvement of diverse interest-holders, iterative data collection and analysis, and a commitment to identifying shared priorities through a community-engaged process. FINDINGS: There was consensus across the evidence inputs that implementing, adapting, and scaling evidence-informed integrated care interventions is crucial for real-world impact. Strategies found important for improved research relevance and impact include implementation science, rapid response, embedded research, and knowledge mobilization, along with key initiative design elements such as co-leadership, cross-jurisdictional and interdisciplinary teams, and a focus on the Quintuple Aim. Priority populations were also identified for maximizing the potential benefit and impact of the research. These findings informed the design of THINC, resulting in a multi-program initiative aligned to a shared goal of evidence-informed integrated care transformation. A collaborative design approach fostered shared objectives, commitment from multiple partner organizations, and resources to increase the initiative's size and scope. CONCLUSIONS: The study demonstrates the feasibility of using an evidence-informed, community-engaged approach and the influence and benefits of the approach in designing a large-scale research funding initiative that aims to be transformational and impactful.
This grey literature reference is included in the Academy's Literature Collection in keeping with our mission to gather all sources of information on integration. Grey literature is comprised of materials that are not made available through traditional publishing avenues. Often, the information from unpublished resources can be limited and the risk of bias cannot be determined.
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