Literature Collection

BACKGROUND: Evidence of patterns of medical utilization and distribution of comorbidities among individuals using methamphetamine remains limited. OBJECTIVE: This study aims to investigate changes in medical utilization and comorbidities before and after a diagnosis of methamphetamine use disorder. METHODS: A total of 3321 cases (79% were male) of methamphetamine use disorder between January 1, 1996, and December 31, 2012, were identified from Psychiatric Inpatient Medical Claims database in Taiwan. Information was collected on demographics, diagnoses, and medical utilizations. The date of newly diagnosed with methamphetamine use disorder was defined as the baseline. Mirror-image study design was used to compare changes in medical utilization and comorbidities between the pre-baseline period (within 1 year before diagnosis) and the post-baseline period (within 1 year after diagnosis). Conditional logistic regression was used to estimate changes in medical utilization and comorbidities. RESULTS: Most cases (77%) were first identified in a psychiatric department. There is a significant increase (P < .001) in psychiatric admission (odds ratio[OR] = 2.19), psychiatric emergency visits (OR = 1.31), and psychiatric outpatient visits (OR = 1.15) after diagnosis. Multivariable analysis revealed significantly increased risks (P < .001) of non-methamphetamine drug induced mental disorders (adjusted OR[aOR] = 29.47), schizophrenia (aOR = 2.62), bipolar disorder (aOR = 2.14), organic mental disorder (aOR = 1.82), and upper respiratory tract infection (aOR = 2.03) after diagnosis. CONCLUSIONS: We found significant increases of medical utilization and psychiatric comorbidities after diagnosed with methamphetamine use disorder. These findings may reflect the problem of delayed diagnosis and treatment. Enhancement of early identification of methamphetamine use disorder in general practice is required for early intervention and decreased subsequent morbidities.

OBJECTIVES: Evidence-based therapies for opioid use disorder (OUD) and chronic pain, such as medications for OUD (MOUD) and complementary and integrative health (CIH; e.g., acupuncture and meditation) therapies, exist. However, their adoption has been slow, particularly in primary care, due to numerous implementation challenges. We sought to expand the use of MOUD and CIH within primary care by using an evidence-based quality improvement (EBQI) implementation strategy. METHODS: We used EBQI to engage two facilities in the Veterans Health Administration (VHA) from June 2018 to September 2019. EBQI included multilevel stakeholder engagement, with external facilitators providing technical support, practice facilitation, and routine data feedback. We established a quality improvement (QI) team at each facility with diverse stakeholders (e.g., primary care, addiction, pain, nursing, pharmacy). We met monthly with regional stakeholders to address implementation barriers. We also convened an advisory board to ensure alignment with national priorities. RESULTS: Pre-implementation interviews indicated facility-level and provider-level barriers to prescribing buprenorphine, including strong primary care provider resistance. Both facilities developed action plans. They both conducted educational meetings (e.g., Grand Rounds, MOUD waiver trainings). Facility A also offered clinical preceptorships for newly trained primary care prescribers. Facility B used mass media and mailings to educate patients about MOUD and CIH options and dashboards to identify potential candidates for MOUD. After 15 months, both facilities increased their OUD treatment rates to the ≥ 90th percentile of VHA medical centers nationally. Exit interviews indicated an attitudinal shift in MOUD delivery in primary care. Stakeholders valued the EBQI process, particularly cross-site collaboration. IMPLICATIONS: Despite initial implementation barriers, we effectively engaged stakeholders using EBQI strategies. Local QI teams used an assortment of QI interventions and developed tools to catapult their facilities to among the highest performers in VHA OUD treatment. IMPACTS: EBQI is an effective strategy to partner with stakeholders to implement MOUD and CIH therapies.

Background: Having prescribers use clinical video teleconferencing (telemedicine) to prescribe buprenorphine to people with opioid use disorder (OUD) has shown promise but its implementation is challenging. We describe barriers, facilitators and lessons learned while implementing a system to remotely prescribe buprenorphine to Veterans in rural settings. Methods: We conducted a quality improvement project aimed at increasing the availability of medications for OUD (MOUD) to Veterans. This project focused on tele-prescribing buprenorphine to rural sites via a hub (centralized prescribers) and spoke (rural clinics) model. After soliciting a wide-range of inputs from site visits, qualitative interviews of key stakeholders at rural sites, and review of preliminary cases, a "how-to" toolkit was developed and iteratively refined to guide tele-prescribing of buprenorphine. After internal and external facilitation strategies were employed, Veterans with OUD at three clinics were transitioned to buprenorphine treatment via telemedicine. Results: Factors impacting adoption of the tele-prescribing intervention were mapped to the Consolidated Framework for Implementation Research (CFIR) constructs. Barriers to adoption included concerns about legality of tele-prescribing a controlled substance, conflicting interests between different stakeholders, and coordination with an existing buprenorphine program requiring more attendance and abstinence from Veterans than the tele-prescribing program required. Factors facilitating adoption included a sense of mission around combating the opioid epidemic, preexisting use of and comfort with tele-prescribing, and rural sites' control over Veterans referred to tele-prescribers. A total of 12 patients from rural areas were successfully transitioned onto buprenorphine, of whom 9 remained on buprenorphine 6 months after initiation of treatment. Conclusions: Implementing tele-prescribing was negotiated with stakeholders at the target clinics and operationalized in a toolkit to guide future efforts. Implementation issues can be addressed by activities that foster collaboration between hubs (centralized prescribers) and spokes (rural clinics) and by a toolkit that operationalizes tele-prescribing procedures.