In type 2 diabetes, the BT-001 smartphone app reduced HbA1c more than a control app at 90 d.

SOURCE CITATION: Hsia J, Guthrie NL, Lupinacci P, et al. Randomized, controlled trial of a digital behavioral therapeutic application to improve glycemic control in adults with type 2 diabetes. Diabetes Care. 2022;45:2976-81. 36181554.

Development and validation of an electronic health records-based opioid use disorder algorithm by expert clinical adjudication among patients with prescribed opioids.

BACKGROUND: In the US, over 200 lives are lost from opioid overdoses each day. Accurate and prompt diagnosis of opioid use disorders (OUD) may help prevent overdose deaths. However, international classification of disease (ICD) codes for OUD are known to underestimate prevalence, and their specificity and sensitivity are unknown. We developed and validated algorithms to identify OUD in electronic health records (EHR) and examined the validity of OUD ICD codes. METHODS: Through four iterations, we developed EHR-based OUD identification algorithms among patients who were prescribed opioids from 2014 to 2017. The algorithms and OUD ICD codes were validated against 169 independent "gold standard" EHR chart reviews conducted by an expert adjudication panel across four healthcare systems. After using 2014-2020 EHR for validating iteration 1, the experts were advised to use 2014-2017 EHR thereafter. RESULTS: Of the 169 EHR charts, 81 (48%) were reviewed by more than one expert and exhibited 85% expert agreement. The experts identified 54 OUD cases. The experts endorsed all 11 OUD criteria from the Diagnostic and Statistical Manual of Mental Disorders-5, including craving (72%), tolerance (65%), withdrawal (56%), and recurrent use in physically hazardous conditions (50%). The OUD ICD codes had 10% sensitivity and 99% specificity, underscoring large underestimation. In comparison our algorithm identified OUD with 23% sensitivity and 98% specificity. CONCLUSIONS AND RELEVANCE: This is the first study to estimate the validity of OUD ICD codes and develop validated EHR-based OUD identification algorithms. This work will inform future research on early intervention and prevention of OUD.

Recent and active problematic substance use among primary care patients: Results from the alcohol, smoking, and substance involvement screening test in a multisite study.

Background: Primary care settings provide salient opportunities for identifying patients with problematic substance use and addressing unmet treatment need. The aim of this study was to examine the extent and correlates of problematic substance use by substance-specific risk categories among primary care patients to inform screening/intervention efforts. Methods: Data were analyzed from 2000 adult primary care patients aged ≥18 years (56% female) across 5 clinics in the eastern U.S. Participants completed the Alcohol, Smoking and Substance Involvement Screening Test (ASSIST). Prevalence and ASSIST-defined risk-level of tobacco use, alcohol use, and nonmedical/illicit drug use was examined. Multinomial logistic regression models analyzed the demographic correlates of substance use risk-levels. Results: Among the total sample, the prevalence of any past 3-month use was 53.9% for alcohol, 42.0% for tobacco, 24.2% for any illicit/Rx drug, and 5.3% for opioids; the prevalence of ASSIST-defined moderate/high-risk use was 45.1% for tobacco, 29.0% for any illicit/Rx drug, 14.2% for alcohol, and 9.1% for opioids. Differences in the extent and risk-levels of substance use by sex, race/ethnicity, and age group were observed. Adjusted logistic regression showed that male sex, white race, not being married, and having less education were associated with increased odds of moderate/high-risk use scores for each substance category; older ages (versus ages 18-25 years) were associated with increased odds of moderate/high-risk opioid use. Conclusions: Intervention need for problematic substance use was prevalent in this sample. Providers should maintain awareness and screen for problematic substance use more consistently in identified high risk populations.

E-Cigarette Use Among Adult Primary Care Patients: Results from a Multisite Study.

BACKGROUND: Primary care settings provide opportunities to identify electronic-cigarette (e-cigarette) use and to implement strategies for changing tobacco use behavior. However, a better understanding of the extent and associated characteristics of e-cigarette use among primary care patients are needed to inform such efforts. OBJECTIVE: To describe patient demographic and substance use characteristics by e-cigarette use status among a large sample of primary care patients. To examine the prevalence and correlates of e-cigarette use among tobacco users in the sample. DESIGN: Cross-sectional analysis from a multisite validation study of a substance use screening instrument. PARTICIPANTS: Adult primary care patients aged 18 and older (n = 2000) recruited across 5 primary care clinics in the Eastern USA from 2014 to 2015. MAIN MEASURES: Patients reported past 3-month e-cigarette use, sociodemographics, tobacco use, and other substance use. Current nicotine dependence and DSM-5 criteria for past-year substance use disorders were also assessed. KEY RESULTS: Among the total sample, 7.7% (n = 154) adults reported past 3-month e-cigarette use. Adults who reported e-cigarette use (vs. no use) were more likely to be younger, white, or have frequent tobacco use, nicotine dependence, or past-year illicit drug use/disorders. Among past 3-month tobacco users, 16.3% reported e-cigarette use. Adjusted logistic regression indicated that odds of e-cigarette use were greater among tobacco users who had some college education or more (vs. < high school) or were daily/almost daily tobacco users (vs. not); odds were lower among Blacks/African-Americans (vs. whites). E-cigarette use among tobacco users was associated with increased odds of current nicotine dependence or tobacco use disorder as well as more severe dependence/disorder. CONCLUSIONS: Enhanced surveillance of e-cigarette use among adult tobacco users in primary care, particularly among those who use tobacco frequently, may have implications for helping patients with tobacco cessation using established approaches including behavioral support, pharmacotherapy, or referral to specialized care.

Identifying core curricular components for behavioral health training in internal medicine residency: Qualitative interviews with residents, faculty, and behavioral health clinicians.

OBJECTIVE: Behavioral health services frequently delivered by primary care providers include care for mental health and substance abuse disorders and assistance with behavioral risk factor reduction. Internal medicine residencies in the United States lack formal expectations regarding training in behavioral health for residents. This qualitative study aimed to determine learners' and teachers' perceptions about appropriate behavioral health curricular components for internal medicine residents. METHOD: Focus groups and interviews were conducted with the following individuals from the Duke Outpatient Clinic: residents with continuity practice (n = 27), advanced practice providers (n = 2), internal medicine attending physicians (n = 4), internal medicine/psychiatry attending physicians (n = 2), and behavioral health clinicians (n = 4). A focus group leader asked regarding residents' successes and challenges in managing behavioral health issues and about specific learning components considered necessary to understand and manage these behavioral health conditions. Transcripts were coded using an editing analysis style to identify central themes and concordance/discordance between groups. RESULTS: Regarding mental health management (Theme 1), residents emphasized a need for better care coordination with specialty mental health, while attendings and behavioral health clinicians gave priority to residents' skills in primary management of mental health. Residents, attendings, and behavioral health clinicians all emphasized advanced interviewing skills (Theme 2) with subthemes: eliciting the patient's perspective, managing time in encounters, improving patients' understanding, and patient counseling. CONCLUSIONS: Internal medicine residents, attendings, and behavioral health clinicians may differ significantly in their perceptions of primary care's role in mental health care. Future internal medicine behavioral health curricula should specifically address these attitudinal differences. Curricula should also emphasize interview skills training as an essential component of behavioral health learning.

Buprenorphine physician-pharmacist collaboration in the management of patients with opioid use disorder: results from a multisite study of the National Drug Abuse Treatment Clinical Trials Network.

BACKGROUND AND AIMS: Physician and pharmacist collaboration may help address the shortage of buprenorphine-waivered physicians and improve care for patients with opioid use disorder (OUD). This study investigated the feasibility and acceptability of a new collaborative care model involving buprenorphine-waivered physicians and community pharmacists. DESIGN: Nonrandomized, single-arm, open-label feasibility trial. SETTING: Three office-based buprenorphine treatment (OBBT) clinics and three community pharmacies in the United States. PARTICIPANTS: Six physicians, six pharmacists, and 71 patients aged ≥18 years with Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5) OUD on buprenorphine maintenance. INTERVENTION: After screening, eligible patients' buprenorphine care was transferred from their OBBT physician to a community pharmacist for 6 months. MEASUREMENTS: Primary outcomes included recruitment, treatment retention and adherence, and opioid use. Secondary outcomes were intervention fidelity, pharmacists' use of prescription drug monitoring program (PDMP), participant safety, and satisfaction with treatment delivery. FINDINGS: A high proportion (93.4%, 71/76) of eligible participants enrolled into the study. There were high rates of treatment retention (88.7%) and adherence (95.3%) at the end of the study. The proportion of opioid-positive urine drug screens (UDSs) among complete cases (i.e. those with all six UDSs collected during 6 months) at month 6 was (4.9%, 3/61). Intervention fidelity was excellent. Pharmacists used PDMP at 96.8% of visits. There were no opioid-related safety events. Over 90% of patients endorsed that they were "very satisfied with their experience and the quality of treatment offered," that "treatment transfer from physician's office to the pharmacy was not difficult at all," and that "holding buprenorphine visits at the same place the medication is dispensed was very or extremely useful/convenient." Similarly, positive ratings of satisfaction were found among physicians/pharmacists. CONCLUSIONS: A collaborative care model for people with opioid use disorder that involves buprenorphine-waivered physicians and community pharmacists appears to be feasible to operate in the United States and have high acceptability to patients.

Characteristics of New Opioid Use Among Medicare Beneficiaries: Identifying High-Risk Patterns.

BACKGROUND: Opioid prescription patterns, including long-term use, multiple prescribers, and high opioid doses, increase the risk for adverse outcomes; however, previous research in older adult populations has primarily described opioid dose patterns using average daily dose measures or using very high thresholds (i.e., > 100 morphine milligram equivalents [MME] per day). OBJECTIVE: To describe prescription patterns by peak dose among older adults who have newly initiated opioid use in 2014 and describe long-term opioid use and the use of multiple pharmacies and prescribers among those with peak opioid doses over 50 and over 90 MME per day. METHODS: This was a retrospective cohort study of Medicare Part D prescription claims data (5% sample) for beneficiaries aged 65 years and older who were prescribed ≥ 1 opioid prescription in 2014 and did not have an opioid prescription in the preceding 180 days. Within a 1-year period of follow-up, we used prescription claims to characterize individuals' opioid exposure, measuring long-term opioid use (≥ 90 days of continuous opioid supply), unique opioid prescribers, and unique opioid-dispensing pharmacies. Peak MME was defined as the maximum daily MME received across all overlapping opioid prescriptions in the observation period. RESULTS: 144,127 beneficiaries without an opioid prescription in the previous 6 months filled ≥ 1 opioid prescription in 2014. During the 1-year follow-up period, 6.5% of beneficiaries transitioned to long-term opioid use; 39.5% received opioid prescriptions from > 1 prescriber; 18.1% filled opioid prescriptions from > 1 pharmacy; and 21.8% had a peak MME of 50-89. Among the 28.1% of beneficiaries exposed to a peak MME > 50, 8.6% developed long-term opioid use; 7.0% had 3 or more opioid dispensing pharmacies; and 28.0% had 3 or more opioid prescribers. Among the 6.2% of beneficiaries exposed to a peak MME ≥ 90, 18.5% developed long-term opioid use; 13.0% had 3 or more opioid dispensing pharmacies; and 39.6% had 3 or more opioid prescribers. CONCLUSIONS: High doses of opioids were prescribed for about one quarter (28%) of Medicare beneficiaries with new opioid use in 2014. Having multiple opioid prescribers or multiple opioid dispensing pharmacies was common, especially among those prescribed higher doses. These prescription patterns can be particularly helpful to identify older adults with increased opioid-related risk. DISCLOSURES: No funding supported this study. Raman reports research grants from GlaxoSmithKline not related to this study. Roberts was supported by a CTSA grant from NCATS awarded to the University of Kansas Medical Center for Frontiers: The Heartland Institute for Clinical and Translational Research (#KL2TR000119). The other authors have no potential conflicts to report.