Literature Collection

BACKGROUND: Contingency management (CM), a behavioral intervention that provides incentives for achieving treatment goals, is an evidence-based adjunct to medication to treat opioid use disorder. Unfortunately, many front-line treatment providers do not utilize CM, likely due to contextual barriers that limit effective training and ongoing support for evidence-based practices. This study applied user-informed approaches to adapt a multi-level implementation strategy called the Science to Service Laboratory (SSL) to support CM implementation. METHODS: Leaders and treatment providers working in community-based opioid treatment programs (OTPs; N = 43) completed qualitative interviews inquiring about their preferences for training and support implementation strategies (didactic training, performance feedback, and external facilitation). Our team coded interviews using a reflexive team approach to identify common a priori and emergent themes. RESULTS: Leaders and providers expressed a preference for brief training that included case examples and research data, along with experiential learning strategies. They reported a desire for performance feedback from internal supervisors, patients, and clinical experts. Providers and leaders had mixed feelings about audio-recording sessions but were open to the use of rating sheets to evaluate CM performance. Finally, participants desired both on-call and regularly scheduled external facilitation to support their continued use of CM. CONCLUSIONS: This study provides an exemplar of a user-informed approach to adapt the SSL implementation support strategies for CM scale-up in community OTPs. Study findings highlight the need for user-informed approaches to training, performance feedback, and facilitation to support sustained CM use in this setting.

Opioid agonist medication, including methadone, is considered the first-line treatment for opioid use disorder. Methadone, when taken daily, reduces the risk of fatal overdose; however, overdose risk increases following medication cessation. Amid an overdose epidemic accelerated by the proliferation of fentanyl, ensuring continuity of methadone treatment during the COVID-19 pandemic is a vital public health priority. (Am J Public Health. 2021;111(12):2115-2117. https://doi.org/10.2105/AJPH.2021.306523).

Chronic kidney disease (CKD) is a common condition and important cardiovascular risk factor. However, CKD remains underdiagnosed and evidence-based medicines underutilized. In most healthcare systems, most CKD is managed in primary care. Optimal management in this setting can only be achieved with integration of care including early identification, prioritization, and use of the tools and skill mix available. This narrative review focuses on the importance of screening and identification in primary care, looking at innovative solutions and methods from other long-term conditions, particularly cardio-renal-metabolic conditions. Integrated care virtual multidisciplinary reviews, have demonstrated clinical and economic benefits, improved medication optimization, and reduced unnecessary referrals. However, implementation remains inconsistent, and prescribing of both established and novel therapies remains sub-optimal. Optimizing CKD care requires a system-wide approach that reinforces primary-secondary care collaboration, prioritizes early detection, and facilitates timely, evidence-based interventions. The inclusion of urine albumin: creatinine ratio testing, integrated digital tools, and shared accountability frameworks must be urgently adopted to realize improved outcomes and reduce the burden of CKD on individuals and healthcare systems alike.

BACKGROUND: Pharmacists remain an underutilized resource in the treatment of opioid use disorder (OUD). Although studies have engaged pharmacists in dispensing medications for OUD (MOUD), few studies have evaluated collaborative care models in which pharmacists are an active, integrated part of a primary care team offering OUD care. METHODS: This study seeks to implement a pharmacist integrated MOUD clinical model (called PrIMO) and evaluate its feasibility, acceptability, and impact across four diverse primary care sites. The Consolidated Framework for Implementation Research is used as an organizing framework for study development and interpretation of findings. Implementation Facilitation is used to support PrIMO adoption. We assess the primary outcome, the feasibility of implementing PrIMO, using the Stages of Implementation Completion (SIC). We evaluate the acceptability and impact of the PrIMO model at the sites using mixed-methods and combine survey and interview data from providers, pharmacists, pharmacy technicians, administrators, and patients receiving MOUD at the primary care sites with patient electronic health record data. We hypothesize that it is feasible to launch delivery of the PrIMO model (reach SIC Stage 6), and that it is acceptable, will positively impact patient outcomes 1 year post model launch (e.g., increased MOUD treatment retention, medication regimen adherence, service utilization for co-morbid conditions, and decreased substance use), and will increase each site's capacity to care for patients with MOUD (e.g., increased number of patients, number of prescribers, and rate of patients per prescriber). DISCUSSION: This study will provide data on a pharmacist-integrated collaborative model of care for the treatment of OUD that may be feasible, acceptable to both site staff and patients and may favorably impact patients' access to MOUD and treatment outcomes. TRIAL REGISTRATION: The study was registered on Clinicaltrials.gov (NCT05310786) on April 5, 2022, https://www.clinicaltrials.gov/study/NCT05310786?id=NCT05310786&rank=1 

BACKGROUND: Despite the high prevalence of alcohol use disorders (AUDs), in 2016, only 7.8% of individuals meeting diagnostic criteria received any type of AUD treatment. Developing options for treatment within primary care settings is imperative to increase treatment access. As part of a trial to implement AUD pharmacotherapy in primary care settings, this qualitative study analyzed pre-implementation provider interviews using the Consolidated Framework for Implementation Research (CFIR) to identify implementation barriers. METHODS: Three large Veterans Health Administration facilities participated in the implementation intervention. Local providers were trained to serve as implementation/clinical champions and received external facilitation from the project team. Primary care providers received a dashboard of patients with AUD for case identification, educational materials, and access to consultation from clinical champions. Veterans with AUD diagnoses received educational information in the mail. Prior to the start of implementation activities, 24 primary care providers (5-10 per site) participated in semi-structured interviews. Transcripts were analyzed using common coding techniques for qualitative data using the CFIR codebook Innovation/Intervention Characteristics, Outer Setting, Inner Setting, and Characteristics of Individuals domains. Number and type of barriers identified were compared to quantitative changes in AUD pharmacotherapy prescribing rates. RESULTS: Four major barriers emerged across all three sites: complexity of providing AUD pharmacotherapy in primary care, the limited compatibility of AUD treatment with existing primary care processes, providers' limited knowledge and negative beliefs about AUD pharmacotherapy and providers' negative attitudes toward patients with AUD. Site specific barriers included lack of relative advantage of providing AUD pharmacotherapy in primary care over current practice, complaints about the design quality and packaging of implementation intervention materials, limited priority of addressing AUD in primary care and limited available resources to implement AUD pharmacotherapy in primary care. CONCLUSIONS: CFIR constructs were useful for identifying pre-implementation barriers that informed refinements to the implementation intervention. The number and type of pre-implementation barriers identified did not demonstrate a clear relationship to the degree to which sites were able to improve AUD pharmacotherapy prescribing rate. Site-level implementation process factors such as leadership support and provider turn-over likely also interacted with pre-implementation barriers to drive implementation outcomes.