Effects of medication assisted treatment (MAT) for opioid use disorder on functional outcomes: A systematic review.

This systematic review synthesizes evidence on the effects of Medication-Assisted Treatment (MAT) for opioid use disorder (OUD) on functional outcomes, including cognitive (e.g., memory), physical (e.g., fatigue), occupational (e.g., return to work), social/behavioral (e.g., criminal activity), and neurological (e.g., balance) function. Five databases were searched from inception to July 2017 to identify English-language controlled trials, case control studies, and cohort comparisons of one or more groups; cross-sectional studies were excluded. Two independent reviewers screened identified literature, abstracted study-level information, and assessed the quality of included studies. Meta-analyses used the Hartung-Knapp method for random-effects models. The quality of evidence was assessed using the GRADE approach. A comprehensive search followed by 1411 full text publication screenings yielded 30 randomized controlled trials (RCTs) and 10 observational studies meeting inclusion criteria. The studies reported highly diverse functional outcome measures. Only one RCT was rated as high quality, but several methodologically sound observational studies were identified. The statistical power to detect differences in functional outcomes was unclear in most studies. When compared with matched "healthy" controls with no history of substance use disorder (SUD), in two studies MAT patients had significantly poorer working memory and cognitive speed. One study found MAT patients scored worse in aggressive responding than did "healthy" controls. A large observational study found that MAT users had twice the odds of involvement in an injurious traffic accident as non-users. When compared with persons with OUD not on MAT, one cohort study found lower fatigue rates among buprenorphine-treated OUD patients. No differences were reported for occupational outcomes and results for criminal activity and other social/behavioral areas were mixed. There were few differences among MAT drug types. A pooled analysis of three RCTs found a significantly lower prevalence of fatigue with buprenorphine compared to methadone, while a meta-analysis of the same RCTs found no statistical difference in insomnia prevalence. Three RCTs that focused on cognitive function compared the effects of buprenorphine to methadone; no statistically significant differences in memory, cognitive speed and flexibility, attention, or vision were reported. The quality of evidence for most functional outcomes was rated low or very low. In sum, weaknesses in the body of evidence prevent strong conclusions about the effects of MAT for opioid use disorder on functional outcomes. Rigorous studies of functional effects would strengthen the body of literature.

Feasibility of a computer-assisted social network motivational interviewing intervention for substance use and HIV risk behaviors for housing first residents.

BACKGROUND: Social networks play positive and negative roles in the lives of homeless people influencing their alcohol and/or other drug (AOD) and HIV risk behaviors. METHODS: We developed a four-session computer-assisted social network motivational interviewing intervention for homeless adults transitioning into housing. We examined the acceptability of the intervention among staff and residents at an organization that provides permanent supportive housing through iterative rounds of beta testing. Staff were 3 men and 3 women who were residential support staff (i.e., case managers and administrators). Residents were 8 men (7 African American, 1 Hispanic) and 3 women (2 African American, 1 Hispanic) who had histories of AOD and HIV risk behaviors. We conducted a focus group with staff who gave input on how to improve the delivery of the intervention to enhance understanding and receptivity among new residents. We conducted semi-structured qualitative interviews and collected self-report satisfaction data from residents. RESULTS: Three themes emerged over the course of the resident interviews. Residents reported that the intervention was helpful in discussing their social network, that seeing the visualizations was more impactful than just talking about their network, and that the intervention prompted thoughts about changing their AOD use and HIV risk networks. CONCLUSIONS: This study is the first of its kind that has developed, with input from Housing First staff and residents, a motivational interviewing intervention that targets both the structure and composition of one's social network. These results suggest that providing visual network feedback with a guided motivational interviewing discussion is a promising approach to supporting network change. ClinicalTrials.gov Identifier NCT02140359.

A computer-assisted motivational social network intervention to reduce alcohol, drug and HIV risk behaviors among Housing First residents.

BACKGROUND: Individuals transitioning from homelessness to housing face challenges to reducing alcohol, drug and HIV risk behaviors. To aid in this transition, this study developed and will test a computer-assisted intervention that delivers personalized social network feedback by an intervention facilitator trained in motivational interviewing (MI). The intervention goal is to enhance motivation to reduce high risk alcohol and other drug (AOD) use and reduce HIV risk behaviors. METHODS/DESIGN: In this Stage 1b pilot trial, 60 individuals that are transitioning from homelessness to housing will be randomly assigned to the intervention or control condition. The intervention condition consists of four biweekly social network sessions conducted using MI. AOD use and HIV risk behaviors will be monitored prior to and immediately following the intervention and compared to control participants' behaviors to explore whether the intervention was associated with any systematic changes in AOD use or HIV risk behaviors. DISCUSSION: Social network health interventions are an innovative approach for reducing future AOD use and HIV risk problems, but little is known about their feasibility, acceptability, and efficacy. The current study develops and pilot-tests a computer-assisted intervention that incorporates social network visualizations and MI techniques to reduce high risk AOD use and HIV behaviors among the formerly homeless. CLINICALTRIALS. GOV IDENTIFIER: NCT02140359.

Resources and Capabilities of the Department of Veterans Affairs to Provide Timely and Accessible Care to Veterans.

The Veterans Access, Choice, and Accountability Act of 2014 addressed the need for access to timely, high-quality health care for veterans. Section 201 of the legislation called for an independent assessment of various aspects of veterans' health care. The RAND Corporation was tasked with an assessment of the Department of Veterans Affairs (VA) current and projected health care capabilities and resources. An examination of data from a variety of sources, along with a survey of VA medical facility leaders, revealed the breadth and depth of VA resources and capabilities: fiscal resources, workforce and human resources, physical infrastructure, interorganizational relationships, and information resources. The assessment identified barriers to the effective use of these resources and capabilities. Analysis of data on access to VA care and the quality of that care showed that almost all veterans live within 40 miles of a VA health facility, but fewer have access to VA specialty care. Veterans usually receive care within 14 days of their desired appointment date, but wait times vary considerably across VA facilities. VA has long played a national leadership role in measuring the quality of health care. The assessment showed that VA health care quality was as good or better on most measures compared with other health systems, but quality performance lagged at some VA facilities. VA will require more resources and capabilities to meet a projected increase in veterans' demand for VA care over the next five years. Options for increasing capacity include accelerated hiring, full nurse practice authority, and expanded use of telehealth.

In the weeds: a baseline view of cannabis use among legalizing states and their neighbours.

AIMS: To describe patterns of cannabis use, the degree of overlap between medicinal and recreational users, and their differential use patterns, modes of consumption and sources of cannabis. DESIGN: An ongoing probability-based internet panel maintained by the market research firm GfK Group. SETTING: Households in Colorado, Washington, Oregon and New Mexico, USA. PARTICIPANTS: A total of 2009 individuals from Washington (n = 787), Oregon (n = 506), Colorado (n = 503) and New Mexico (n = 213). Post stratification sampling weights were provided so that estimates could be made representative of the household population in each of these states. Respondents were aged between 18 and 91 years, with a mean age of 53 years. METHODS: We compare patterns of cannabis consumption for medicinal and recreational users as well as simultaneous use of alcohol and cannabis. We also examine the extent to which patterns of use differ across states that chose to legalize (Washington and Colorado) and those that did not (New Mexico and Oregon). FINDINGS: Rates of life-time medical cannabis use are similar in Colorado and Washington (8.8% and 8.2%) but lower in Oregon and New Mexico (6.5% and 1%). Recreational use is considerably higher than medical use across all states (41%), but highest in Oregon and Washington. Approximately 86% of people who report ever using cannabis for medicinal purposes also use it recreationally. Medical users are more likely to vaporize and consume edibles and report a higher amount (in grams) consumed, and spend more money per month than recreational users. Individuals who use cannabis do not commonly use it with alcohol, irrespective of whether they are consuming cannabis recreationally or medically. Fewer than one in five recreational users report simultaneous use of alcohol and cannabis most or all of the time and fewer than 3% of medicinal users report frequent simultaneous use of alcohol and cannabis. CONCLUSIONS: In the United States, the degree of overlap between medicinal and recreational cannabis users is 86%. Medicinal and recreational cannabis users favor different modes and amounts of consumption. Only a small proportion (12%) of cannabis users usually consume cannabis and alcohol simultaneously, while concurrent use is common among recreational users.