Prevalence and Medication Treatment of Opioid Use Disorder Among Primary Care Patients with Hepatitis C and HIV.

BACKGROUND: Hepatitis C and HIV are associated with opioid use disorders (OUD) and injection drug use. Medications for OUD can prevent the spread of HCV and HIV. OBJECTIVE: To describe the prevalence of documented OUD, as well as receipt of office-based medication treatment, among primary care patients with HCV or HIV. DESIGN: Retrospective observational cohort study using electronic health record and insurance data. PARTICIPANTS: Adults ≥ 18 years with ≥ 2 visits to primary care during the study (2014-2016) at 6 healthcare systems across five states (CO, CA, OR, WA, and MN). MAIN MEASURES: The primary outcome was the diagnosis of OUD; the secondary outcome was OUD treatment with buprenorphine or oral/injectable naltrexone. Prevalence of OUD and OUD treatment was calculated across four groups: HCV only; HIV only; HCV and HIV; and neither HCV nor HIV. In addition, adjusted odds ratios (AOR) of OUD treatment associated with HCV and HIV (separately) were estimated, adjusting for age, gender, race/ethnicity, and site. KEY RESULTS: The sample included 1,368,604 persons, of whom 10,042 had HCV, 5821 HIV, and 422 both. The prevalence of diagnosed OUD varied across groups: 11.9% (95% CI: 11.3%, 12.5%) for those with HCV; 1.6% (1.3%, 2.0%) for those with HIV; 8.8% (6.2%, 11.9%) for those with both; and 0.92% (0.91%, 0.94%) among those with neither. Among those with diagnosed OUD, the prevalence of OUD medication treatment was 20.9%, 16.0%, 10.8%, and 22.3%, for those with HCV, HIV, both, and neither, respectively. HCV was not associated with OUD treatment (AOR = 1.03; 0.88, 1.21), whereas patients with HIV had a lower probability of OUD treatment (AOR = 0.43; 0.26, 0.72). CONCLUSIONS: Among patients receiving primary care, those diagnosed with HCV and HIV were more likely to have documented OUD than those without. Patients with HIV were less likely to have documented medication treatment for OUD.

Approaches for Implementing App-Based Digital Treatments for Drug Use Disorders Into Primary Care: A Qualitative, User-Centered Design Study of Patient Perspectives.

BACKGROUND: Digital interventions, such as websites and smartphone apps, can be effective in treating drug use disorders (DUDs). However, their implementation in primary care is hindered, in part, by a lack of knowledge on how patients might like these treatments delivered to them. OBJECTIVE: This study aims to increase the understanding of how patients with DUDs prefer to receive app-based treatments to inform the implementation of these treatments in primary care. METHODS: The methods of user-centered design were combined with qualitative research methods to inform the design of workflows for offering app-based treatments in primary care. Adult patients (n=14) with past-year cannabis, stimulant, or opioid use disorder from 5 primary care clinics of Kaiser Permanente Washington in the Seattle area participated in this study. Semistructured interviews were recorded, transcribed, and analyzed using qualitative template analysis. The coding scheme included deductive codes based on interview topics, which primarily focused on workflow design. Inductive codes emerged from the data. RESULTS: Participants wanted to learn about apps during visits where drug use was discussed and felt that app-related conversations should be incorporated into the existing care whenever possible, as opposed to creating new health care visits to facilitate the use of the app. Nearly all participants preferred receiving clinician support for using apps over using them without support. They desired a trusting, supportive relationship with a clinician who could guide them as they used the app. Participants wanted follow-up support via phone calls or secure messaging because these modes of communication were perceived as a convenient and low burden (eg, no copays or appointment travel). CONCLUSIONS: A user-centered implementation of treatment apps for DUDs in primary care will require health systems to design workflows that account for patients' needs for structure, support in and outside of visits, and desire for convenience.

Measuring the Implementation of Behavioral Intervention Technologies: Recharacterization of Established Outcomes.

Behavioral intervention technologies (BITs) are websites, software, mobile apps, and sensors designed to help users address or change behaviors, cognitions, and emotional states. BITs have the potential to transform health care delivery, and early research has produced promising findings of efficacy. BITs also favor new models of health care delivery and provide novel data sources for measurement. However, there are few examples of successful BIT implementation and a lack of consensus on as well as inadequate descriptions of BIT implementation measurement. The aim of this viewpoint paper is to provide an overview and characterization of implementation outcomes for the study of BIT use in routine practice settings. Eight outcomes for the evaluation of implementation have been previously described: acceptability, adoption, appropriateness, feasibility, fidelity, implementation cost, penetration, and sustainability. In a proposed recharacterization of these outcomes with respect to BIT implementation, definitions are clarified, expansions to the level of analysis are identified, and unique measurement characteristics are discussed. Differences between BIT development and implementation, an increased focus on consumer-level outcomes, the expansion of providers who support BIT use, and the blending of BITs with traditional health care services are specifically discussed. BITs have the potential to transform health care delivery. Realizing this potential, however, will hinge on high-quality research that consistently and accurately measures how well such technologies have been integrated into health services. This overview and characterization of implementation outcomes support BIT research by identifying and proposing solutions for key theoretical and practical measurement challenges.

Do trauma type, stressful life events, and social support explain women veterans' high prevalence of PTSD?

OBJECTIVES: To examine factors that account for women veterans' higher prevalence of past-year DSM-5 posttraumatic stress disorder (PTSD) compared to women civilians and men veterans. METHODS: Cross-sectional analyses of the 2012-2013 National Epidemiologic Survey on Alcohol and Related Conditions-III (NESARC-III). Face-to-face interviews with 379 women veterans, 20,007 women civilians, and 2740 men veterans were conducted. Trauma type (child abuse, interpersonal violence, combat or war zone, and other), number of trauma types, past-year stressful life events, current social support, and DSM-5 PTSD were assessed using the Alcohol Use Disorder and Associated Disabilities Interview Schedule-5. Generalized linear models were used that accounted for the complex survey design. RESULTS: Women veterans had a higher unadjusted prevalence of past-year PTSD (11.40%) compared to their civilian (5.96%) and male (5.19%) counterparts. Individual predictor models indicated that the difference between women veterans' and civilians' prevalence of PTSD was attenuated when adjusting for number of trauma types, whereas the difference between men and women veterans was attenuated when adjusting for child abuse, interpersonal violence, and stressful life events. Nonetheless, while full adjustment in a multiple predictor model accounted for the difference in PTSD between women veterans and civilians, gender differences between men and women veterans remained. CONCLUSIONS: Number of trauma types, type of trauma, and social factors may together help explain women veterans' higher PTSD prevalence compared to women civilians, but do not fully account for differences between men and women veterans. Results highlight a need to explore additional explanatory factors and evaluate associations with longitudinal data.

Intersections of poverty, race/ethnicity, and sex: alcohol consumption and adverse outcomes in the United States.

We examine whether intersectionality theory-which formalizes the notion that adverse health outcomes owing to having a marginalized social status, identity, or characteristic, may be magnified for individuals with an additional marginalized social status, identity, or characteristic-can be applied using quantitative methods to describe the differential effects of poverty on alcohol consumption across sex and race/ethnicity. Using the National Epidemiologic Survey on Alcohol and Related Conditions, we analyze longitudinal data from Black, Hispanic, and White drinkers (n = 21,140) to assess multiplicative interactions between poverty, as defined by the US Census Bureau, sex, and race/ethnicity, on adverse alcohol outcomes. Findings indicated that the effect of poverty on the past-year incidence of heavy episodic drinking was stronger among Black men and Black women in comparison to men and women of other racial/ethnic groups. Poverty reduction programs that are culturally informed may help reduce racial/ethnic disparities in the adverse outcomes of alcohol consumption.

Psychosocial stressors and alcohol use, severity, and treatment receipt across human immunodeficiency virus (HIV) status in a nationally representative sample of US residents.

BACKGROUND: Human immunodeficiency virus (HIV) is stigmatized and disproportionately impacts vulnerable populations. Thus, people living with HIV (PLWH) may have greater exposure to psychosocial stressors than those without HIV. Exposure to psychosocial stressors may increase alcohol use and serve as barriers to alcohol treatment receipt. The authors evaluate whether psychosocial stressors and alcohol use, symptom severity, and treatment receipt vary across HIV status in a general population sample of US residents and assess whether psychosocial stressors mediate identified associations. METHODS: Data from Wave 2 of the National Epidemiologic Survey on Alcohol and Related Conditions (NESARC) were used to assess associations between HIV status and psychosocial stressors (perceived stress, alcohol-related stigma, and perceived discrimination based on race/ethnicity, sexual orientation, or sex) and alcohol-related outcomes (any use, heavy drinking, symptom severity, and treatment receipt). For each outcome, regression models were fit and iteratively adjusted for sociodemographic characteristics and comorbidities. Indirect effects of HIV on alcohol-related outcomes through stressors were estimated to assess mediation when main effects were significant. RESULTS: Among 34,653 NESARC Wave 2 respondents, 161 were PLWH. PLWH were more likely than those without HIV to experience discrimination and had higher levels of perceived stress than those without HIV (P values <.05), but the 2 groups did not differ regarding alcohol-related stigma. PLWH were less likely to use alcohol and had similar rates of heavy drinking relative to participants without HIV, but alcohol symptom severity and treatment receipt were greater among PLWH. Perceived stress but not discrimination mediated associations. CONCLUSIONS: Findings from this first study of variation in psychosocial stressors and alcohol use, severity, and treatment receipt across HIV status further highlight PLWH as a population that is particularly vulnerable to experiences of psychosocial stress and certain adverse alcohol-related outcomes. Future longitudinal research is needed in a larger sample of PLWH to identify intervention targets.

Alcohol Screening and Intervention Among United States Adults who Attend Ambulatory Healthcare.

BACKGROUND: There is limited data on the extent to which indicated alcohol interventions are delivered in U.S. ambulatory care settings. OBJECTIVE: To assess the receipt of alcohol-related services, including assessment of use, advice to reduce drinking, and information about alcohol treatment, during ambulatory care visits. DESIGN: Secondary data analysis of the 2013 National Survey on Drug Use and Health, a cross-sectional, nationally representative survey of civilians in the non-institutionalized U.S. general population (response rate 71.7 %). PARTICIPANTS: Adult ambulatory care users in the public use data file who did not obtain emergency or inpatient services (n = 17,266). MAIN MEASURES: Measurements included respondents' alcohol consumption, heavy episodic drinking, alcohol use disorder, healthcare use, and receipt of alcohol-related interventions. KEY RESULTS: Approximately 71.1 % of ambulatory care users received an alcohol assessment. Among past-month heavy episodic drinkers without an alcohol use disorder who reported receiving an alcohol assessment, 4.4 % were advised to cut back. Among individuals with alcohol abuse and alcohol dependence who reported receiving an alcohol assessment, 2.9 % and 7.0 %, respectively, were offered information about treatment. CONCLUSIONS: Rates of alcohol screening and assessment were relatively high among adults who attended healthcare visits, but rates of intervention were low, even when individuals were assessed for use. Efforts are needed to expand delivery of interventions when patients are identified as positive for risky drinking, hazardous alcohol use, and alcohol use disorders during ambulatory care visits.

Implementing an mHealth system for substance use disorders in primary care: a mixed methods study of clinicians' initial expectations and first year experiences.

BACKGROUND: Millions of Americans need but don't receive treatment for substance use, and evidence suggests that addiction-focused interventions on smart phones could support their recovery. There is little research on implementation of addiction-related interventions in primary care, particularly in Federally Qualified Health Centers (FQHCs) that provide primary care to underserved populations. We used mixed methods to examine three FQHCs' implementation of Seva, a smart-phone app that offers patients online support/discussion, health-tracking, and tools for coping with cravings, and offers clinicians information about patients' health tracking and relapses. We examined (a) clinicians' initial perspectives about implementing Seva, and (b) the first year of implementation at Site 1. METHODS: Prior to staggered implementation at three FQHCs (Midwest city in WI vs. rural town in MT vs. metropolitan NY), interviews, meetings, and focus groups were conducted with 53 clinicians to identify core themes of initial expectations about implementation. One year into implementation at Site 1, clinicians there were re-interviewed. Their reports were supplemented by quantitative data on clinician and patient use of Seva. RESULTS: Clinicians anticipated that Seva could help patients and make behavioral health appointments more efficient, but they were skeptical that physicians would engage with Seva (given high caseloads), and they were uncertain whether patients would use Seva. They were concerned about legal obligations for monitoring patients' interactions online, including possible "cries for help" or inappropriate interactions. One year later at Site 1, behavioral health care providers, rather than physicians, had incorporated Seva into patient care, primarily by discussing it during appointments. Given workflow/load concerns, only a few key clinicians monitored health tracking/relapses and prompted outreach when needed; two researchers monitored the discussion board and alerted the clinic as needed. Clinician turnover/leave complicated this approach. Contrary to clinicians' initial concerns, patients showed sustained, mutually supportive use of Seva, with few instances of misuse. CONCLUSIONS: Results suggest the value of (a) focusing implementation on behavioral health care providers rather than physicians, (b) assigning a few individuals (not necessarily clinicians) to monitor health tracking, relapses, and the discussion board, (c) anticipating turnover/leave and having designated replacements. Patients showed sustained, positive use of Seva. TRIAL REGISTRATION: ClinicalTrials.gov ( NCT01963234 ).

Psychiatric comorbidity and perceived alcohol stigma in a nationally representative sample of individuals with DSM-5 alcohol use disorder.

BACKGROUND: Alcohol use disorder (AUD) is among the most stigmatized health conditions and is frequently comorbid with mood, anxiety, and drug use disorders. Theoretical frameworks have conceptualized stigma-related stress as a predictor of psychiatric disorders. We described profiles of psychiatric comorbidity among people with AUD and compared levels of perceived alcohol stigma across profiles. METHODS: Cross-sectional data were analyzed from a general population sample of U.S. adults with past-year DSM-5 AUD (n = 3,368) from the National Epidemiologic Survey on Alcohol and Related Conditions, which was collected from 2001 to 2005. Empirically derived psychiatric comorbidity profiles were established with latent class analysis, and mean levels of perceived alcohol stigma were compared across the latent classes while adjusting for sociodemographic characteristics and AUD severity. RESULTS: Four classes of psychiatric comorbidity emerged within this AUD sample, including those with: (i) high comorbidity, reflecting internalizing (i.e., mood and anxiety disorders) and externalizing (i.e., antisocial personality and drug use disorders) disorders; (ii) externalizing comorbidity; (iii) internalizing comorbidity; and (iv) no comorbidity. Perceived alcohol stigma was significantly higher in those with internalizing comorbidity (but not those with high comorbidity) as compared to those with no comorbidity or externalizing comorbidity. CONCLUSIONS: Perceived stigma, as manifested by anticipations of social rejection and discrimination, may increase risk of internalizing psychiatric comorbidity. Alternatively, internalizing psychiatric comorbidity could sensitize affected individuals to perceive more negative attitudes toward them. Future research is needed to understand causal and bidirectional associations between alcohol stigma and psychiatric comorbidity.

A Systematic Review of Strategies for Implementing Empirically Supported Mental Health Interventions.

OBJECTIVE: This systematic review examines experimental studies that test the effectiveness of strategies intended to integrate empirically supported mental health interventions into routine care settings. Our goal was to characterize the state of the literature and to provide direction for future implementation studies. METHODS: A literature search was conducted using electronic databases and a manual search. RESULTS: Eleven studies were identified that tested implementation strategies with a randomized (n = 10) or controlled clinical trial design (n = 1). The wide range of clinical interventions, implementation strategies, and outcomes evaluated precluded meta-analysis. However, the majority of studies (n = 7; 64%) found a statistically significant effect in the hypothesized direction for at least one implementation or clinical outcome. CONCLUSIONS: There is a clear need for more rigorous research on the effectiveness of implementation strategies, and we provide several suggestions that could improve this research area.

Offering nurse care management for opioid use disorder in primary care: Impact on emergency and hospital utilization in a cluster-randomized implementation trial.

BACKGROUND: Patients with opioid use disorder (OUD) have increased emergency and hospital utilization. The PROUD trial showed that implementation of office-based addiction treatment (OBAT) increased OUD medication treatment compared to usual care, but did not decrease acute care utilization in patients with OUD documented pre-randomization (clinicaltrials.gov/study/NCT03407638). This paper reports secondary emergency and hospital utilization outcomes in patients with documented OUD in the PROUD trial. METHODS: This cluster-randomized implementation trial was conducted in 12 clinics from 6 diverse health systems (March 2015-February 2020). Patients who visited trial clinics and had an OUD diagnosis within 3 years pre-randomization were included in primary analyses; secondary analyses added patients with OUD who were new to the clinic or with newly-documented OUD post-randomization. Outcomes included days of emergency care and hospital utilization over 2 years post-randomization. Explanatory outcomes included measures of OUD treatment. Patient-level analyses used mixed-effect regression with clinic-specific random intercepts. RESULTS: Among 1988 patients with documented OUD seen pre-randomization (mean age 49, 53 % female), days of emergency care or hospitalization did not differ between intervention and usual care; OUD treatment also did not differ. In secondary analyses among 1347 patients with OUD post-randomization, there remained no difference in emergency or hospital utilization despite intervention patients receiving 32.2 (95 % CI 4.7, 59.7) more days of OUD treatment relative to usual care. CONCLUSIONS: Implementation of OBAT did not reduce emergency or hospital utilization among patients with OUD, even in the sample with OUD first documented post-randomization in whom the intervention increased treatment.

Perceived alcohol stigma: factor structure and construct validation.

INTRODUCTION: There has been an increasing interest in studying the stigma of alcohol use disorders (AUDs) yet scant research has evaluated the conceptualization and measurement of alcohol stigma. This study examined the measurement properties (i.e., factor structure) and validity of the alcohol-adapted Perceived Devaluation-Discrimination scale (PDD), which assesses the construct of perceived alcohol stigma (PAS). METHODS: Our sample included 34,386 respondents from the Wave 2 assessment in the National Epidemiologic Survey on Alcohol and Related Conditions, a population-representative survey of noninstitutionalized U.S. adults. Analytic procedures included confirmatory factor analysis and structural equation modeling. RESULTS: One-factor (perceived devaluation-discrimination) and 2-factor (perceived devaluation, perceived discrimination) confirmatory factor analytic models fit the data well (Comparative Fit Index = 0.958, Tucker-Lewis Index = 0.942, Root Mean Square Error of Approximation = 0.056; Comparative Fit Index = 0.962, Tucker-Lewis Index = 0.946, Root Mean Square Error of Approximation = 0.054; respectively) when adjusting for item wording effects with a latent method factor. Despite having a better fit to the data, χ(2) (1) = 542, p < 0.0001, the 2 factors were highly correlated (r = 0.90), which led us to favor a 1-factor model. Structural equation models found that the inverse relationship between PAS and perceived interpersonal social support was strongest for persons with a stigmatized labeling status. The same was not true in analyses predicting social network involvement. CONCLUSIONS: A 1-factor solution of PAS had superior parsimony. The alcohol-adapted PDD appears to be a psychometrically sound measure and exhibits relationships that are consistent with modified labeling theory.

Considering the Role of Information and Context in Promoting Health-Related Behavioral Change.

This poster considers the role that information and context may play in health management. We employ a well-known taxonomy of techniques for promoting behavioral change to consider how social media authors describe their recovery from substance use. We harvest discussion posts from subreddits, or discussion forums, about alcohol, cannabis, and opioids, and perform content analysis to identify behavioral change techniques (BCTs) described in the content. We then consider the role that the context of information use plays in these BCTs, as well as how interventions and technologies might be leveraged to better support the recovery process.

Associations Between Distinct Co-occurring Substance Use Disorders and Receipt of Medications for Opioid Use Disorder in the Veterans Health Administration.

OBJECTIVES: Among people with opioid use disorder (OUD), having a co-occurring substance use disorder (SUD) is associated with lower likelihood of receiving OUD treatment medications (MOUD). However, it is unclear how distinct co-occurring SUDs are associated with MOUD receipt. This study examined associations of distinct co-occurring SUDs with initiation and continuation of MOUD among patients with OUD in the national Veterans Health Administration (VA). METHODS: Electronic health record data were extracted for outpatients with OUD who received care August 1, 2016, to July 31, 2017. Analyses were conducted separately among patients without and with prior-year MOUD receipt to examine initiation and continuation, respectively. SUDs were measured using diagnostic codes; MOUD receipt was measured using prescription fills/clinic visits. Adjusted regression models estimated likelihood of following-year MOUD receipt for patients with each co-occurring SUD relative to those without. RESULTS: Among 23,990 patients without prior-year MOUD receipt, 12% initiated in the following year. Alcohol use disorder (adjusted incidence rate ratio [aIRR], 0.80; 95% confidence interval [CI], 0.72-0.90) and cannabis use disorder (aIRR, 0.78; 95% CI, 0.70-0.87) were negatively associated with initiation. Among 11,854 patients with prior-year MOUD receipt, 83% continued in the following year. Alcohol use disorder (aIRR, 0.94; 95% CI, 0.91-0.97), amphetamine/other stimulant use disorder (aIRR, 0.94; 95% CI, 0.90-0.99), and cannabis use disorder (aIRR, 0.95; 95% CI, 0.93-0.98) were negatively associated with continuation. CONCLUSIONS: In this study of national VA outpatients with OUD, those with certain co-occurring SUDs were less likely to initiate or continue MOUD. Further research is needed to identify barriers related to specific co-occurring SUDs.

Addictions treatment mechanisms of change science and implementation science: A critical review.

This manuscript aims to contribute to the next phase of mechanisms of behavior change (MOBC) science on alcohol or other drug use. Specifically, we encourage the transition from a basic science orientation (i.e., knowledge generation) to a translational science orientation (i.e., knowledge application or Translational MOBC Science). To inform that transition, we examine MOBC science and implementation science and consider how these two research areas can intersect to capitalize on the goals, strengths, and key methodologies of each. First, we define MOBC science and implementation science and offer a brief historical rationale for these two areas of clinical research. Second, we summarize similarities in rationale and discuss two scenarios where one draws from the other-MOBC science on implementation strategy outcomes and implementation science on MOBC. We then focus on the latter scenario, and briefly review the MOBC knowledge base to consider its readiness for knowledge translation. Finally, we provide a series of research recommendations to facilitate the translation of MOBC science. These recommendations include: (1) identifying and targeting MOBC that are well suited for implementation, (2) use of MOBC research results to inform broader health behavior change theory, and (3) triangulation of a more diverse set of research methodologies to build a translational MOBC knowledge base. Ultimately, it is important for gains borne from MOBC science to affect direct patient care, while basic MOBC research continues to be developed and refined over time. Potential implications of these developments include greater clinical significance for MOBC science, an efficient feedback loop between clinical research methodologies, a multi-level approach to understanding behavioral change, and reduced or eliminated siloes between MOBC science and implementation science.

Treating opioid use disorder in veterans with co-occurring substance use: a qualitative study with buprenorphine providers in primary care, mental health, and pain settings.

BACKGROUND: Most people with opioid use disorder (OUD) have co-occurring substance use, which is associated with lower receipt of OUD medications (MOUD). Expanding MOUD provision and care linkage outside of substance use disorder (SUD) specialty settings is a key strategy to increase access. Therefore, it is important to understand how MOUD providers in these settings approach care for patients with co-occurring substance use. This qualitative study of Veterans Health Administration (VA) clinicians providing buprenorphine care in primary care, mental health, and pain settings aimed to understand (1) their approach to addressing OUD in patients with co-occurring substance use, (2) perspectives on barriers/facilitators to MOUD receipt for this population, and (3) support needed to increase MOUD receipt for this population. METHODS: We interviewed a purposive sample of 27 clinicians (12 primary care, 7 mental health, 4 pain, 4 pharmacists) in the VA northwest network. The interview guide assessed domains of the Tailored Implementation for Chronic Diseases Checklist. Interviews were transcribed and qualitatively analyzed using inductive content analysis. RESULTS: Participants reported varied approaches to identifying co-occurring substance use and addressing OUD in this patient population. Although they reported that this topic was not clearly addressed in clinical guidelines or training, participants generally felt that patients with co-occurring substance use should receive MOUD. Some viewed their primary role as providing this care, others as facilitating linkage to OUD care in SUD specialty settings. Participants reported multiple barriers and facilitators to providing buprenorphine care to patients with co-occurring substance use and linking them to SUD specialty care, including provider, patient, organizational, and external factors. CONCLUSIONS: Efforts are needed to support clinicians outside of SUD specialty settings in providing buprenorphine care to patients with co-occurring substance use. These could include clearer guidelines and policies, more specific training, and increased care integration or cross-disciplinary collaboration. Simultaneously, efforts are needed to improve linkage to specialty SUD care for patients who would benefit from and are willing to receive this care, which could include increased service availability and improved referral/hand-off processes. These efforts may increase MOUD receipt and improve OUD care quality for patients with co-occurring substance use.

Implementation and workflow strategies for integrating digital therapeutics for alcohol use disorders into primary care: a qualitative study.

BACKGROUND: Alcohol use disorders (AUD) are prevalent and often go untreated. Patients are commonly screened for AUD in primary care, but existing treatment programs are failing to meet demand. Digital therapeutics include novel mobile app-based treatment approaches which may be cost-effective treatment options to help fill treatment gaps. The goal of this study was to identify implementation needs and workflow design considerations for integrating digital therapeutics for AUD into primary care. METHODS: We conducted qualitative interviews with clinicians, care delivery leaders, and implementation staff (n = 16) in an integrated healthcare delivery system in the United States. All participants had experience implementing digital therapeutics for depression or substance use disorders in primary care. Interviews were designed to gain insights into adaptations needed to optimize existing clinical processes, workflows, and implementation strategies for use with alcohol-focused digital therapeutics. Interviews were recorded and transcribed and then analyzed using a rapid analysis process and affinity diagramming. RESULTS: Qualitative themes were well represented across health system staff roles. Participants were enthusiastic about digital therapeutics for AUD, anticipated high patient demand for such a resource, and made suggestions for successful implementation. Key insights regarding the implementation of digital therapeutics for AUD and unhealthy alcohol use from our data include: (1) implementation strategy selection must be driven by digital therapeutic design and target population characteristics, (2) implementation strategies should seek to minimize burden on clinicians given the large numbers of patients with AUD who are likely to be interested in and eligible for digital therapeutics, and (3) digital therapeutics should be offered alongside many other treatment options to accommodate individual patients' AUD severity and treatment goals. Participants also expressed confidence that previous implementation strategies used with other digital therapeutics such as clinician training, electronic health record supports, health coaching, and practice facilitation would be effective for the implementation of digital therapeutics for AUD. CONCLUSIONS: The implementation of digital therapeutics for AUD would benefit from careful consideration of the target population. Optimal integration requires tailoring workflows to meet anticipated patient volume and designing workflow and implementation strategies to meet the unique needs of patients with varying AUD severity.

Impact of an intervention to implement provision of opioid use disorder medication among patients with and without co-occurring substance use disorders.

INTRODUCTION: Co-occurring substance use disorders (SUDs) are common among people with opioid use disorder (OUD) and known to hinder receipt of medications for OUD (MOUD). It is important to understand how MOUD care implemented outside of SUD specialty settings impacts access for patients with co-occurring SUDs. The Veterans Health Administration's (VA) Stepped Care for Opioid Use Disorder Train the Trainer (SCOUTT) initiative was implemented in primary care, mental health, and pain clinics in 18 VA facilities, and was found to increase MOUD receipt. This study assessed the SCOUTT initiative's impact among patients with and without co-occurring SUDs. METHODS: This study used a controlled interrupted time series design. We extracted electronic health record data for patients with OUD with visits in SCOUTT intervention or matched comparison clinics during the post-implementation year (9/1/2018-8/31/2019). We examined the monthly proportion of patients who received MOUD in SCOUTT intervention or comparison clinics (primary care, mental health, and pain clinics), or in a VA SUD specialty clinic (where patients may have been referred), during the pre- and post-implementation years. Segmented logistic regression models estimated pre-post changes in outcomes (immediate level change from the final month of the pre-implementation period to the first month of the post-implementation period, change in trend/slope) in intervention vs. comparison facilities, adjusting for patient characteristics and pre-implementation trends. We stratified analyses by the presence of co-occurring SUDs. RESULTS: Among patients without co-occurring SUDs, the pre-post trend/slope change in MOUD received in SCOUTT intervention or comparison clinics was greater in intervention vs. comparison facilities (adjusted odds ratio [aOR]: 1.06, 95% confidence interval [CI]: 1.02-1.10), and the immediate increase in MOUD received in SUD clinics was greater in intervention vs. comparison facilities (aOR: 1.12, 95% CI: 1.02-1.22). These changes did not significantly differ in intervention vs. comparison facilities among patients with co-occurring SUDs. CONCLUSIONS: The SCOUTT initiative may have increased MOUD receipt primarily among patients without co-occurring SUDs. Focusing on increasing MOUD receipt for patients with co-occurring SUDs may improve the overall effectiveness of MOUD implementation efforts.

Integrating Alcohol-Related Prevention and Treatment Into Primary Care: A Cluster Randomized Implementation Trial.

Importance: Unhealthy alcohol use is common and affects morbidity and mortality but is often neglected in medical settings, despite guidelines for both prevention and treatment. Objective: To test an implementation intervention to increase (1) population-based alcohol-related prevention with brief interventions and (2) treatment of alcohol use disorder (AUD) in primary care implemented with a broader program of behavioral health integration. Design, Setting, and Participants: The Sustained Patient-Centered Alcohol-Related Care (SPARC) trial was a stepped-wedge cluster randomized implementation trial, including 22 primary care practices in an integrated health system in Washington state. Participants consisted of all adult patients (aged ≥18 years) with primary care visits from January 2015 to July 2018. Data were analyzed from August 2018 to March 2021. Interventions: The implementation intervention included 3 strategies: practice facilitation; electronic health record decision support; and performance feedback. Practices were randomly assigned launch dates, which placed them in 1 of 7 waves and defined the start of the practice's intervention period. Main Outcomes and Measures: Coprimary outcomes for prevention and AUD treatment were (1) the proportion of patients who had unhealthy alcohol use and brief intervention documented in the electronic health record (brief intervention) for prevention and (2) the proportion of patients who had newly diagnosed AUD and engaged in AUD treatment (AUD treatment engagement). Analyses compared monthly rates of primary and intermediate outcomes (eg, screening, diagnosis, treatment initiation) among all patients who visited primary care during usual care and intervention periods using mixed-effects regression. Results: A total of 333 596 patients visited primary care (mean [SD] age, 48 [18] years; 193 583 [58%] female; 234 764 [70%] White individuals). The proportion with brief intervention was higher during SPARC intervention than usual care periods (57 vs 11 per 10 000 patients per month; P < .001). The proportion with AUD treatment engagement did not differ during intervention and usual care (1.4 vs 1.8 per 10 000 patients; P = .30). The intervention increased intermediate outcomes: screening (83.2% vs 20.8%; P < .001), new AUD diagnosis (33.8 vs 28.8 per 10 000; P = .003), and treatment initiation (7.8 vs 6.2 per 10 000; P = .04). Conclusions and Relevance: In this stepped-wedge cluster randomized implementation trial, the SPARC intervention resulted in modest increases in prevention (brief intervention) but not AUD treatment engagement in primary care, despite important increases in screening, new diagnoses, and treatment initiation. Trial Registration: ClinicalTrials.gov Identifier: NCT02675777.