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.

The goal of this report is to provide an overview of shared decision making as a healthcare practice and related policy options for the state of New Hampshire. Through evaluation of current research and salient case studies, this report seeks to highlight the opportunities and challenges of implementing shared decision making in a variety of settings. There are a number of policy options for New Hampshire to consider should the legislature wish to pursue the support and development of shared decision making in the state. They include endorsing shared decision making practices, developing partnerships with other stakeholders, creating new incentives for physicians and mandating the use of shared decision making.