Literature Collection

OBJECTIVE: We conducted this systematic review to support the U.S. Preventive Services Task Force in updating its 2008 recommendation on screening adolescents and adults, including pregnant women, for illicit drug use. Our review addressed 5 key questions (KQ): 1a. Does primary care screening for drug use in adolescents and adults, including pregnant women, reduce drug use or improve other risky behaviors? 1b. Does primary care screening for drug use in adolescents and adults, including pregnant women, reduce morbidity or mortality or improve other health, social, or legal outcomes? 2. What is the accuracy of drug use screening instruments? 3. What are the harms of primary care screening for drug use in adolescents and adults, including pregnant women? 4a. Do counseling interventions to reduce drug use, with or without referral, reduce drug use or improve other risky behaviors in screen-detected persons? 4b. Do counseling interventions to reduce drug use, with or without referral, reduce morbidity or mortality or improve other health, social, or legal outcomes in screen-detected persons? 5. What are the harms of interventions to reduce drug use in screen-detected persons? DATA SOURCES: We performed a search of MEDLINE, PubMed Publisher-Supplied, PsycINFO, and the Cochrane Central Register of Controlled Trials for studies published through June 7, 2018. Studies included in three related USPSTF reviews were re-evaluated for potential inclusion. We supplemented searches by examining reference lists from related articles and expert recommendations and searched federal and international trial registries for ongoing trials. STUDY SELECTION: Two researchers reviewed 17,919 titles and abstracts and 271 full-text articles against prespecified inclusion criteria. For all KQs, we included studies among adolescents and adults aged 12 years and older, including pregnant women. Studies targeting illicit psychoactive drug use or nonmedical pharmaceutical drug use were included; those targeting nonpsychoactive drugs (e.g., laxatives, anabolic steroids) were excluded. For KQs 1 and 3, we included studies that compared individuals who received screening with those who received no screening or who received usual care, including randomized trials or nonrandomized controlled trials. For KQ 2, we included studies that reported the accuracy (sensitivity and specificity) of standardized screening instruments compared with structured clinical interviews or biologic verification and that took place in a setting that was applicable to primary care. Studies evaluating the accuracy of laboratory testing to detect drug use were not included. For KQ 4 and 5 about counseling interventions, only randomized and nonrandomized trials among screen-detected persons were included. Trials among persons who sought drug treatment or were referred or mandated to receive drug treatment were excluded. Interventions could include any brief counseling approach designed to reduce drug use, with or without referral. Studies of medication-assisted therapy (i.e., the use of methadone, buprenorphine, or naltrexone plus counseling) to treat opioid use disorders were excluded given that use of this therapy limited to adults with a diagnosed opioid use disorder (typically severe and non-screen detected). We conducted dual, independent critical appraisal of all provisionally included studies and abstracted all important study details and results from all studies rated fair or good quality. Data were abstracted by one reviewer and confirmed by another. DATA ANALYSIS: We synthesized data separately for each KQ and subpopulation (i.e., adolescents, young adults and adults, and pregnant and postpartum women). The data for KQ 2 did not allow for quantitative pooling due to the limited number of contributing studies for each screening instrument and condition, so we synthesized the data qualitatively through tables and narrative synthesis. For drug use outcomes, we ran random effects meta-analyses using the DerSimonian and Laird method to calculate the pooled differences in mean changes in drug use days; data was too sparse to pool for binary data on drug abstinence. We examined statistical heterogeneity among the pooled studies using standard χ(2) tests and estimated the proportion of total variability in point estimates using the I(2) statistic. We graded the strength of the overall body of evidence based on the consistency and precision of the results, reporting bias, and study quality. RESULTS: We found no evidence that addressed the benefits and harms of screening for drug use. Twenty-eight studies (n=65,720) addressed the accuracy of 30 drug use screening instruments; each specific screening instrument has not been studied more than once or twice. Studies among adolescents mainly focused on detecting cannabis use. They found that sensitivity for detecting any cannabis use or unhealthy cannabis use of frequency-based and risk assessment screen tools (all validated against structured clinical interview alone) ranged from 0.68 to 0.98 (95% CI range, 0.64 to 0.99) and specificity ranging from 0.82 to 1.00 (95% CI range, 0.80 to 1.00). Among adults, frequency-based and risk assessment drug screening tools (all but two validated against structured clinical interview alone) showed sensitivity for detecting unhealthy use of any drug ranging from 0.71 to 0.94 (95% CI range, 0.62 to 0.97) and specificity ranging from 0.87 to 0.97 (95% CI range, 0.83 to 0.98). For identifying drug use disorders among adults, sensitivity ranged from 0.85 to 1.00 (95% CI range, 0.67 to 1.00) and specificity ranged from 0.67 to 0.93 (95% CI, 0.58 to 0.95) when using the same cutoffs. Sensitivity for detecting any prenatal drug use using frequency-based and risk assessment (all validated against hair or urine analyses) was lower than the estimates for any drug use in non-pregnant adults (only rarely based on validation against biologic samples) and ranged from 0.37 to 0.76 (95% CI range, 0.24 to 0.86). Specificity was comparable and ranged from 0.68 to 0.83 (95% CI range, 0.55 to 0.91). We included 27 trials that addressed the effectiveness of a counseling intervention on changes in drug use or improved health, social, or legal outcomes among a screen-detected population. Across all 27 trials (n analyzed=8705), in general, there was no consistent effect of the interventions on rates of self-reported or biologically confirmed drug use at 3- to 12-month followup. Likewise, across 13 trials reporting the effects of the interventions on health, social, or legal outcomes (n-analyzed=4304), none of the trials found a statistically significant difference between intervention and control groups on any of these measures at 3- to 12-month followup. Of four trials providing information regarding potential harms, none found any evidence of harm. LIMITATIONS: This review was not intended to be a comprehensive review of the evidence for treating drug use or drug use disorders and therefore, only trials of interventions among screen-detected populations that were applicable to primary care were included. CONCLUSIONS: Several screening instruments with acceptable sensitivity and specificity have been developed to screen for drug use and drug use disorders in primary care, although in general, the accuracy of each tool has not been evaluated in more than one study and there is no evidence on the benefits or harms of screening versus no screening for drug use. Brief interventions for reducing the use of illicit drugs or the nonmedical use of prescription drugs in screen-detected primary care patients are unlikely to be effective for decreasing drug use or drug use consequences. Given the burden of drug use, more research is needed on approaches to identify and effectively intervene with patients exhibiting risky patterns of drug use in primary care.

Substance use remains a leading cause of preventable death globally. A model of intervention known as screening, brief intervention, and referral to treatment (SBIRT) was developed decades ago to facilitate time- and resource-sensitive interventions in acute care and outpatient settings. SBIRT, which includes a psychosocial intervention incorporating the principles of motivational interviewing, has been shown to be effective in reducing alcohol consumption and consequences in unhealthy drinkers both in primary care and emergency department settings. Subsequently, SBIRT for unhealthy alcohol use has been endorsed by governmental agencies and professional societies in multiple countries. Although most trials support the efficacy of SBIRT for unhealthy alcohol use (McQueen et al. in Cochrane Database Syst Rev 8, 2011; Kaner et al. in Cochrane Database Syst Rev 2, 2007; O'Donnell et al. in Alcohol Alcohol 49(1):66-78, 2014), results are heterogenous; negative studies exist. A newer approach to screening and intervention for substance use can incorporate initiation of medication management at the index visit, for individuals willing to do so, and for providers and healthcare systems that are appropriately trained and resourced. Our group has conducted two successful trials of an approach we call screening, treatment initiation, and referral (STIR). In one trial, initiation of nicotine pharmacotherapy coupled with screening and brief counseling in adult smokers resulted in sustained biochemically confirmed abstinence. In a second trial, initiation of buprenorphine for opioid dependent individuals resulted in greater engagement in treatment at 30 days and greater self-reported abstinence. STIR may offer a new, clinically effective approach to the treatment of substance use in clinical care settings.

INTRODUCTION: Opioid overdose deaths are increasing rapidly in the United States. Medications for opioid use disorder (MOUD) are effective and can be delivered in primary care, but uptake has been limited in rural communities. Referral to and coordination with an external telemedicine (TM) vendor by rural primary care clinics for MOUD (TM-MOUD) may increase MOUD access for rural patients, but we know little about perspectives on this model among key stakeholders. As part of a TM-MOUD feasibility study, we explored TM-MOUD acceptability and feasibility among personnel and patients from seven rural primary care clinics and a TM-MOUD vendor. METHODS: We conducted virtual interviews or focus groups with clinic administrators (n = 7 interviews), clinic primary care and behavioral health providers (8 groups, n = 30), other clinic staff (9 groups, n = 37), patients receiving MOUD (n = 16 interviews), TM-MOUD vendor staff (n = 4 interviews), and vendor-affiliated behavioral health and prescribing providers (n = 17 interviews). We asked about experiences with and acceptability of MOUD (primarily buprenorphine) and telemedicine (TM) and a TM-MOUD referral and coordination model. We conducted content analysis to identify themes and participants quantitatively rated acceptability of TM-MOUD elements on a 4-item scale. RESULTS: Perceived benefits of vendor-based TM-MOUD included reduced logistical barriers, more privacy and less stigma, and access to services not available locally (e.g., counseling, pain management). Barriers included lack of internet or poor connectivity in patients' homes, limited communication and trust between TM-MOUD and clinic providers, and questions about the value to the clinic of TM-MOUD referral to external vendor. Acceptability ratings for TM-MOUD were generally high; they were lowest among frontline staff. CONCLUSIONS: Rural primary care clinic personnel, TM-MOUD vendor personnel, and patients generally perceived referral from primary care to a TM-MOUD vendor to hold potential for increasing access to MOUD in rural communities. Increasing TM-MOUD uptake requires buy-in and understanding among staff of the TM-MOUD workflow, TM services offered, requirements for patients, advantages over clinic-based or TM services from clinic providers, and identification of appropriate patients. Poverty, along with patient hesitation to initiate treatment, creates substantial barriers to MOUD treatment generally; insufficient internet availability creates a substantial barrier to TM-MOUD.

Nurse practitioner (NP) and physician assistant (PA) prescribing can increase access to buprenorphine treatment for opioid use disorder. In this cross-sectional study, we used deidentified claims from approximately 90% of U.S. retail pharmacies (2017-2018) to examine the association of state policies with the odds of receiving buprenorphine treatment from an NP/PA versus a physician, overall and stratified by urban/rural status. From 2017 to 2018, the percentage of buprenorphine treatment episodes prescribed by NPs/PAs varied widely across states, from 0.4% in Alabama to 57.2% in Montana. Policies associated with greater odds of buprenorphine treatment from an NP/PA included full scope of practice (SOP) for NPs, full SOP for PAs, Medicaid pay parity for NPs (reimbursement at 100% of the fee-for-service physician rate), and Medicaid expansion. Although most findings with respect to policies were similar in urban and rural settings, the association of Medicaid expansion with NP/PA buprenorphine treatment was driven by rural counties.

Provider networks in Medicaid Managed Care (MMC) play a crucial role in ensuring access to buprenorphine, a highly effective treatment for opioid use disorder. Using a difference-in-differences approach that compares network breadth across provider specialties and market segments within the same state, we investigated the association between three Medicaid policies and the breadth of MMC networks for buprenorphine prescribers: Medicaid expansion, substance use disorder (SUD) network adequacy criteria, and SUD carveouts. We found that both Medicaid expansion and SUD network adequacy criteria were associated with substantially increased breadth in buprenorphine-prescriber networks in MMC. In both cases, we found that the associations were largely driven by increases in the network breadth of primary care physician prescribers. Our findings suggest that Medicaid expansion and SUD network adequacy criteria may be effective strategies at states' disposal to improve access to buprenorphine.

OBJECTIVE: As the United States grapples with an opioid epidemic, expanding access to effective treatment for opioid use disorder is a major public health priority. Identifying effective policy tools that can be used to expand access to care is critically important. This article examines the relationship between state-targeted funding and technical assistance and adoption of three medications for treating opioid use disorder: oral naltrexone, injectable naltrexone, and buprenorphine. METHODS: This study draws from the 2013-2014 wave of the National Drug Abuse Treatment System Survey, a nationally representative, longitudinal study of substance use disorder treatment programs. The sample includes data from 695 treatment programs (85.5% response rate) and representatives from single-state agencies in 49 states and Washington, D.C. (98% response rate). Logistic regression was used to examine the relationships of single-state agency targeted funding and technical assistance to availability of opioid use disorder medications among treatment programs. RESULTS: State-targeted funding was associated with increased program-level adoption of oral naltrexone (adjusted odds ratio [AOR]=3.14, 95% confidence interval [CI]=1.49-6.60, p=.004) and buprenorphine (AOR=2.47, 95% CI=1.31-4.67, p=.006). Buprenorphine adoption was also correlated with state technical assistance to support medication provision (AOR=1.18, 95% CI=1.00-1.39, p=.049). CONCLUSIONS: State-targeted funding for medications may be a viable policy lever for increasing access to opioid use disorder medications. Given the historically low rates of opioid use disorder medication adoption in treatment programs, single-state agency targeted funding is a potentially important tool to reduce mortality and morbidity associated with opioid disorders and misuse.