Assessing Substance Use Disorder Symptoms with a Checklist among Primary Care Patients with Opioid Use Disorder and/or Long-Term Opioid Treatment: An Observational Study.

BACKGROUND: Primary care (PC) offers an opportunity to treat opioid use disorders (OUD). The Substance Use Symptom Checklist ("Checklist") can assess DSM-5 substance use disorder (SUD) symptoms in PC. OBJECTIVE: To test the psychometric properties of the Checklist among PC patients with OUD or long-term opioid therapy (LTOT) in Kaiser Permanente Washington (KPWA). DESIGN: Observational study using item response theory (IRT) and differential item functioning (DIF) analyses of measurement consistency across age, sex, race and ethnicity, and receipt of treatment. PATIENTS: Electronic health records (EHR) data were extracted for all adult PC patients visiting KPWA 3/1/15-8/30/2020 who had ≥ 1 Checklist documented and indication of either (a) clinically-recognized OUD (i.e., documented OUD diagnosis and/or OUD medication treatment) or (b) LTOT in the year prior to the checklist. MAIN MEASURE: The Checklist includes 11 items reflecting DSM-5 criteria for SUD. We described the prevalence of 2 SUD symptoms reported on the Checklist (consistent with mild-severe DSM-5 SUD). Analyses were conducted in the overall sample and in two subsamples (clinically-recognized OUD and LTOT only). KEY RESULTS: Among 2007 eligible patients, 39.9% endorsed ≥ 2 SUD symptoms (74.3% in the clinically-recognized OUD subsample and 13.1% in LTOT subsample). IRT indicated that a unidimensional model for the 11 checklist items had excellent fit (comparative fit index = 0.998) with high item-level discrimination parameters for the overall sample and both subsamples. DIF across age, race and ethnicity, and treatment was observed for one item each, but had minimal impact on expected number of criteria (0-11) patients endorse. CONCLUSIONS: The Substance Use Symptom Checklist measured SUD symptoms consistent with DSM-5 conceptualization (scaled, unidimensional) in patients with clinically-recognized OUD and LTOT and had similar measurement properties across demographic subgroups. The Checklist may support symptom assessment in patients with OUD and diagnosis in patients with LTOT.

Equivalence of Alcohol Use Disorder Symptom Assessments in Routine Clinical Care When Completed Remotely via Online Patient Portals Versus In Clinic via Paper Questionnaires: Psychometric Evaluation.

BACKGROUND: The National Institute on Alcohol Abuse and Alcoholism (NIAAA) recommends the paper-based or computerized Alcohol Symptom Checklist to assess alcohol use disorder (AUD) symptoms in routine care when patients report high-risk drinking. However, it is unknown whether Alcohol Symptom Checklist response characteristics differ when it is administered online (eg, remotely via an online electronic health record [EHR] patient portal before an appointment) versus in clinic (eg, on paper after appointment check-in). OBJECTIVE: This study evaluated the psychometric performance of the Alcohol Symptom Checklist when completed online versus in clinic during routine clinical care. METHODS: This cross-sectional, psychometric study obtained EHR data from the Alcohol Symptom Checklist completed by adult patients from an integrated health system in Washington state. The sample included patients who had a primary care visit in 2021 at 1 of 32 primary care practices, were due for annual behavioral health screening, and reported high-risk drinking on the behavioral health screen (Alcohol Use Disorder Identification Test-Consumption score ≥7). After screening, patients with high-risk drinking were typically asked to complete the Alcohol Symptom Checklist-an 11-item questionnaire on which patients self-report whether they had experienced each of the 11 AUD criteria listed in the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5) over a past-year timeframe. Patients could complete the Alcohol Symptom Checklist online (eg, on a computer, smartphone, or tablet from any location) or in clinic (eg, on paper as part of the rooming process at clinical appointments). We examined sample and measurement characteristics and conducted differential item functioning analyses using item response theory to examine measurement consistency across these 2 assessment modalities. RESULTS: Among 3243 patients meeting eligibility criteria for this secondary analysis (2313/3243, 71% male; 2271/3243, 70% White; and 2014/3243, 62% non-Hispanic), 1640 (51%) completed the Alcohol Symptom Checklist online while 1603 (49%) completed it in clinic. Approximately 46% (752/1640) and 48% (764/1603) reported ≥2 AUD criteria (the threshold for AUD diagnosis) online and in clinic (P=.37), respectively. A small degree of differential item functioning was observed for 4 of 11 items. This differential item functioning produced only minimal impact on total scores used clinically to assess AUD severity, affecting total criteria count by a maximum of 0.13 criteria (on a scale ranging from 0 to 11). CONCLUSIONS: Completing the Alcohol Symptom Checklist online, typically prior to patient check-in, performed similarly to an in-clinic modality typically administered on paper by a medical assistant at the time of the appointment. Findings have implications for using online AUD symptom assessments to streamline workflows, reduce staff burden, reduce stigma, and potentially assess patients who do not receive in-person care. Whether modality of DSM-5 assessment of AUD differentially impacts treatment is unknown.

Bariatric Surgery and Suicide Risk in Patients With Obesity.

OBJECTIVE: In a large multisite cohort of Veterans who underwent Roux-en-Y gastric bypass or laparoscopic sleeve gastrectomy, we compared the 5-year suicidal ideation and attempt rates with matched nonsurgical controls. BACKGROUND: Bariatric surgery has significant health benefits but has also been associated with adverse mental health outcomes. METHODS: Five-year rates of suicidal ideation and suicide attempts of Veterans who underwent Roux-en-Y gastric bypass or laparoscopic sleeve gastrectomy from the fiscal year 2000-2016 to matched nonsurgical controls using sequential stratification using cumulative incidence functions (ideation cohort: n=38,199; attempt cohort: n=38,661 after excluding patients with past-year outcome events). Adjusted differences in suicidal ideation and suicide attempts were estimated using a Cox regression with a robust sandwich variance estimator. RESULTS: In the matched cohorts for suicidal ideation analyses, the mean age was 53.47 years and the majority were males (78.7%) and White (77.7%). Over 40% were treated for depression (41.8%), had a nonrecent depression diagnosis (40.9%), and 4.1% had past suicidal ideation or suicide attempts >1 year before index. Characteristics of the suicide attempt cohort were similar. Regression results found that risk of suicidal ideation was significantly higher for surgical patients (adjusted hazard ratio=1.21, 95% CI: 1.03-1.41), as was risk of suicide attempt (adjusted hazard ratio=1.62, 95% CI: 1.22-2.15). CONCLUSIONS: Bariatric surgery appears to be associated with a greater risk of suicidal ideation and attempts than nonsurgical treatment of patients with severe obesity, suggesting that patients need careful monitoring for suicidal ideation and additional psychological support after bariatric surgery.

The Effect of Bariatric Surgery on Long-term Depression Treatment in Patients With Obesity.

OBJECTIVE: In a large multisite cohort of Veterans who underwent Roux-en-Y gastric bypass (RYGB) or laparoscopic sleeve gastrectomy (LSG), initiation of (ie, incident) and persistence of (ie, continuation of preoperative) depression treatment are compared with matched nonsurgical controls. BACKGROUND: Bariatric surgery has been associated with short-term improvements in depression but less is known about longer term outcomes. METHODS: In a retrospective cohort study, we matched 1713 Veterans with depression treatment who underwent bariatric surgery in Veterans Administration bariatric centers from fiscal year 2001 to 2016 to 15,056 nonsurgical controls using sequential stratification and examined the persistence of depression treatment via generalized estimating equations. Incidence of depression treatment was compared using Cox regression models between 2227 surgical patients and 20,939 matched nonsurgical controls without depression treatment at baseline. RESULTS: In surgical patients with depression treatment at baseline, the use of postsurgical depression treatment declined over time for both surgical procedures, but postsurgical patients had greater use of depression treatment at 5 years [RYGB: odds ratio=1.24, 95% confidence interval (CI): 1.04-1.49; LSG: odds ratio=1.27, 95% CI: 1.04-1.56] compared with controls. Among those without depression treatment at baseline, bariatric surgery was associated with a higher incidence of depression treatment compared with matched controls (RYGB: hazard ratio=1.34, 95% CI: 1.17-1.53; LSG: hazard ratio at 1-5 years=1.27, 95% CI: 1.10-1.47). CONCLUSIONS: Bariatric surgery was associated with a greater risk of postoperative incident depression treatment and greater persistence of postoperative depression treatment. Depression may worsen for some patients after bariatric surgery, so clinicians should carefully monitor their patients for depression postoperatively.

Practical Assessment of Alcohol Use Disorder in Routine Primary Care: Performance of an Alcohol Symptom Checklist.

BACKGROUND: Alcohol use disorder (AUD) is highly prevalent but underrecognized and undertreated in primary care settings. Alcohol Symptom Checklists can engage patients and providers in discussions of AUD-related care. However, the performance of Alcohol Symptom Checklists when they are used in routine care and documented in electronic health records (EHRs) remains unevaluated. OBJECTIVE: To evaluate the psychometric performance of an Alcohol Symptom Checklist in routine primary care. DESIGN: Cross-sectional study using item response theory (IRT) and differential item functioning analyses of measurement consistency across age, sex, race, and ethnicity. PATIENTS: Patients seen in primary care in the Kaiser Permanente Washington Healthcare System who reported high-risk drinking on the Alcohol Use Disorder Identification Test Consumption screening measure (AUDIT-C ≥ 7) and subsequently completed an Alcohol Symptom Checklist between October 2015 and February 2020. MAIN MEASURE: Alcohol Symptom Checklists with 11 items assessing AUD criteria defined in the Diagnostic and Statistical Manual for Mental Disorders, 5th edition (DSM-5), completed by patients during routine medical care and documented in EHRs. KEY RESULTS: Among 11,464 patients who screened positive for high-risk drinking and completed an Alcohol Symptom Checklist (mean age 43.6 years, 30.5% female), 54.1% reported ≥ 2 DSM-5 AUD criteria (threshold for AUD diagnosis). IRT analyses demonstrated that checklist items measured a unidimensional continuum of AUD severity. Differential item functioning was observed for some demographic subgroups but had minimal impact on accurate measurement of AUD severity, with differences between demographic subgroups attributable to differential item functioning never exceeding 0.42 points of the total symptom count (of a possible range of 0-11). CONCLUSIONS: Alcohol Symptom Checklists used in routine care discriminated AUD severity consistently with current definitions of AUD and performed equitably across age, sex, race, and ethnicity. Integrating symptom checklists into routine care may help inform clinical decision-making around diagnosing and managing AUD.

Practical assessment of DSM-5 alcohol use disorder criteria in routine care: High test-retest reliability of an Alcohol Symptom Checklist.

BACKGROUND: Alcohol use disorder (AUD) is underdiagnosed and undertreated in medical settings, in part due to a lack of AUD assessment instruments that are reliable and practical for use in routine care. This study evaluates the test-retest reliability of a patient-report Alcohol Symptom Checklist questionnaire when it is used in routine care, including primary care and mental health specialty settings. METHODS: We performed a pragmatic test-retest reliability study using electronic health record (EHR) data from Kaiser Permanente Washington, an integrated health system in Washington state. The sample included 454 patients who reported high-risk drinking on a behavioral health screen and completed two Alcohol Symptom Checklists 1 to 21 days apart. Subgroups of these patients who completed both checklists in primary care (n = 271) or mental health settings (n = 79) were also examined. The primary measure was an Alcohol Symptom Checklist on which patients self-reported whether they experienced each of the 11 AUD criteria within the past year, as defined by the Diagnostic and Statistical Manual of Mental Disorders-5th edition (DSM-5). RESULTS: Alcohol Symptom Checklists completed in routine care and documented in EHRs had excellent test-retest reliability for measuring AUD criterion counts (ICC = 0.79, 95% CI: 0.76 to 0.82). Test-retest reliability estimates were also high and not significantly different for the subsamples of patients who completed both checklists in primary care (ICC = 0.82, 95% CI: 0.77 to 0.85) or mental health settings (ICC = 0.74, 95% CI: 0.62 to 0.83). Test-retest reliability was not moderated by having a past two-year AUD diagnosis, nor by the age or sex of the patient completing it. CONCLUSIONS: Alcohol Symptom Checklists can reliably and pragmatically assess AUD criteria in routine care among patients who screen positive for high-risk drinking. The Alcohol Symptom Checklist may be a valuable tool in supporting AUD-related care and monitoring AUD criteria longitudinally in routine primary care and mental health settings.

An Alcohol Symptom Checklist identifies high rates of alcohol use disorder in primary care patients who screen positive for depression and high-risk drinking.

BACKGROUND: Although alcohol use disorder can complicate depression management, there is no standard process for assessing AUD symptoms (i.e., AUD diagnostic criteria) in primary care for patients who screen positive for depression. This study characterizes the association between depressive symptoms and high-risk drinking reported by primary care patients on screening measures in routine care. Then, using data from a novel clinical program, this study characterizes the association between depressive symptoms and AUD symptoms reported by primary care patients with high-risk drinking via an Alcohol Symptom Checklist. METHODS: In this cross-sectional study, electronic health record data were obtained from patients who visited 33 Kaiser Permanente Washington primary care clinics between 03/2018 and 02/2020 and completed depression (PHQ-2) and alcohol consumption (AUDIT-C) screening measures as part of routine care (N = 369,943). Patients who reported high-risk drinking (AUDIT-C scores 7-12) also completed an Alcohol Symptom Checklist where they reported the presence or absence of 11 AUD criteria as defined by the DSM-5 (N = 8,184). Generalized linear models estimated and compared the prevalence of high-risk drinking (AUDIT-C scores 7-12) and probable AUD (2-11 AUD symptoms on Alcohol Symptom Checklists) for patients with and without positive depression screens. RESULTS: Patients who screened positive for depression had a 131% higher prevalence of high-risk drinking than those who screened negative (5.2% vs. 2.2%; p < 0.001). Among patients with high-risk drinking, positive depression screens were associated with a significantly higher prevalence of probable AUD (69.8% vs. 48.0%; p < 0.001), with large differences in the prevalence of probable AUD observed with increasing PHQ-2 scores (e.g., probable AUD prevalence of 37.6%, 55.3% and 65.2%, for PHQ-2 scores of 0, 1, and 2, respectively). Although the overall prevalence of high-risk drinking was higher for male patients, similar patterns of association between depression screens, high-risk drinking, and AUD symptoms were observed for male and female patients. CONCLUSIONS: Patients with positive depression screens are more likely to have high-risk drinking. Large percentages of patients with positive depression screens and high-risk drinking report symptoms consistent with AUD to healthcare providers when given the opportunity to do so using an Alcohol Symptom Checklist.

Baseline representativeness of patients in clinics enrolled in the PRimary care Opioid Use Disorders treatment (PROUD) trial: comparison of trial and non-trial clinics in the same health systems.

BACKGROUND: Pragmatic primary care trials aim to test interventions in "real world" health care settings, but clinics willing and able to participate in trials may not be representative of typical clinics. This analysis compared patients in participating and non-participating clinics from the same health systems at baseline in the PRimary care Opioid Use Disorders treatment (PROUD) trial. METHODS: This observational analysis relied on secondary electronic health record and administrative claims data in 5 of 6 health systems in the PROUD trial. The sample included patients 16-90 years at an eligible primary care visit in the 3 years before randomization. Each system contributed 2 randomized PROUD trial clinics and 4 similarly sized non-trial clinics. We summarized patient characteristics in trial and non-trial clinics in the 2 years before randomization ("baseline"). Using mixed-effect regression models, we compared trial and non-trial clinics on a baseline measure of the primary trial outcome (clinic-level patient-years of opioid use disorder (OUD) treatment, scaled per 10,000 primary care patients seen) and a baseline measure of the secondary trial outcome (patient-level days of acute care utilization among patients with OUD). RESULTS: Patients were generally similar between the 10 trial clinics (n = 248,436) and 20 non-trial clinics (n = 341,130), although trial clinics' patients were slightly younger, more likely to be Hispanic/Latinx, less likely to be white, more likely to have Medicaid/subsidized insurance, and lived in less wealthy neighborhoods. Baseline outcomes did not differ between trial and non-trial clinics: trial clinics had 1.0 more patient-year of OUD treatment per 10,000 patients (95% CI: - 2.9, 5.0) and a 4% higher rate of days of acute care utilization than non-trial clinics (rate ratio: 1.04; 95% CI: 0.76, 1.42). CONCLUSIONS: trial clinics and non-trial clinics were similar regarding most measured patient characteristics, and no differences were observed in baseline measures of trial primary and secondary outcomes. These findings suggest trial clinics were representative of comparably sized clinics within the same health systems. Although results do not reflect generalizability more broadly, this study illustrates an approach to assess representativeness of clinics in future pragmatic primary care trials.

Barriers and facilitators to changing drinking and receiving alcohol-related care: Interviews with Veterans Health Administration primary care patients who indicated interest but did not enroll in an alcohol care management intervention trial.

Background: Most people with alcohol use disorder do not receive treatment, and primary care (PC)-based management of alcohol use disorder is a key strategy to close this gap. Understanding PC patients' perspectives on changing drinking and receiving alcohol-related care is important for this goal, particularly among those who decline alcohol-related care. This study examined perspectives on barriers and facilitators to changing drinking and receiving alcohol-related care among Veterans Health Administration (VA) PC patients who indicated interest but did not enroll in the Choosing Healthier drinking Options In primary CarE trial (CHOICE), which tested a PC-based alcohol care management intervention. Methods: VA PC patients with frequent heavy drinking who indicated interest in CHOICE but did not enroll were invited to participate. Twenty-seven patients completed in-person, semi-structured interviews. Interview transcripts were analyzed using iterative deductive and inductive content analysis. Results: Participants were mostly men (96%) and White (59%), and the mean age was 48. Seventy-four percent met criteria for alcohol use disorder, and the median number of past-week standard drinks was 41.5. Participants reported fewer alcohol-related problems, lower importance of/readiness to change drinking, and higher confidence in their ability to change than patients who enrolled in the CHOICE trial. Barriers fell into 5 domains: drinking fulfills need(s); reducing drinking or treatment is not needed; treatment is not effective/not acceptable; alcohol-related stigma; and practical barriers. Facilitators fell into 4 domains: reasons to change drinking; social support; treatment is acceptable/meets patients' needs; and practical facilitators. Participants discussed how Veteran identity and military experiences impacted drinking and willingness to receive care, which amplified multiple barriers/facilitators. Conclusions: This study identified barriers and facilitators to changing drinking and receiving alcohol-related care among VA PC patients who indicated interest but did not enroll in an alcohol care management trial. Findings can inform patient-centered interventions and support clinicians in engaging patients in care.

Clinical documentation of patient-reported medical cannabis use in primary care: Toward scalable extraction using natural language processing methods.

Background: Most states have legalized medical cannabis, yet little is known about how medical cannabis use is documented in patients' electronic health records (EHRs). We used natural language processing (NLP) to calculate the prevalence of clinician-documented medical cannabis use among adults in an integrated health system in Washington State where medical and recreational use are legal. Methods: We analyzed EHRs of patients ≥18 years old screened for past-year cannabis use (November 1, 2017-October 31, 2018), to identify clinician-documented medical cannabis use. We defined medical use as any documentation of cannabis that was recommended by a clinician or described by the clinician or patient as intended to manage health conditions or symptoms. We developed and applied an NLP system that included NLP-assisted manual review to identify such documentation in encounter notes. Results: Medical cannabis use was documented for 16,684 (5.6%) of 299,597 outpatient encounters with routine screening for cannabis use among 203,489 patients seeing 1,274 clinicians. The validated NLP system identified 54% of documentation and NLP-assisted manual review the remainder. Language documenting reasons for cannabis use included 125 terms indicating medical use, 28 terms indicating non-medical use and 41 ambiguous terms. Implicit documentation of medical use (e.g., "edible THC nightly for lumbar pain") was more common than explicit (e.g., "continues medical cannabis use"). Conclusions: Clinicians use diverse and often ambiguous language to document patients' reasons for cannabis use. Automating extraction of documentation about patients' cannabis use could facilitate clinical decision support and epidemiological investigation but will require large amounts of gold standard training data.

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.

Alcohol Use and Antiretroviral Adherence Among Patients Living with HIV: Is Change in Alcohol Use Associated with Change in Adherence?

Alcohol use increases non-adherence to antiretroviral therapy (ART) among persons living with HIV (PLWH). Dynamic longitudinal associations are understudied. Veterans Aging Cohort Study (VACS) data 2/1/2008-7/31/16 were used to fit linear regression models estimating changes in adherence (% days with ART medication fill) associated with changes in alcohol use based on annual clinically-ascertained AUDIT-C screening scores (range - 12 to + 12, 0 = no change) adjusting for demographics and initial adherence. Among 21,275 PLWH (67,330 observations), most reported no (48%) or low-level (39%) alcohol use initially, with no (55%) or small (39% ≤ 3 points) annual change. Mean initial adherence was 86% (SD 21%), mean annual change was - 3.1% (SD 21%). An inverted V-shaped association was observed: both increases and decreases in AUDIT-C were associated with greater adherence decreases relative to stable scores [p < 0.001, F (4, 21,274)]. PLWH with dynamic alcohol use (potentially indicative of alcohol use disorder) should be considered for adherence interventions.

RESUMEN: El consumo de alcohol aumenta el no-cumplimiento a la terapia antirretroviral (TARV) entre las personas que viven con VIH. No se han estudiado lo suficiente las dinámicas asociaciones longitudinales. Los datos del Estudio de la Envejecimiento de Cohorte de Veteranos (EECV) (1/2/2008­31/7/2016) fueron usados para encajar modelos de regresión lineal estimando los cambios en cumplimiento (% de días con medicaciones TARV surtidas) asociados con los cambios en el consumo de alcohol basado en los resultados anuales de las evaluaciones AUDIT-C, determinadas clínicamente, (una gama de -12 a + 12, 0 = cero cambio) adaptándose a las estadísticas demográficas y cumplimiento inicial. Entre 21,275 personas que viven con VIH (67,330 observaciones), la mayoría reportó ningún (48%) o bajos niveles del (39%) consumo de alcohol inicialmente, con ningún (55%) o muy pequeño (39% ≤ 3 puntos) cambio anual. la media inicial de cumplimiento fue 86% (DE 21%). La media de cambio anual fue -3.1% (DE 21%). Se observó una asociación de forma V invertida: tanto los aumentos como las disminuciones en AUDIT-C fueron asociados con mayor disminuciones de cumplimiento en comparación con resultados estables (p < 0.001, F (4, 21,274)). Personas que viven con VIH con el consumo dinámico de alcohol (potencialmente indicativo de un trastorno por consumo de alcohol) deben ser considerados por intervenciones de cumplimiento.

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.

Routine Assessment of Symptoms of Substance Use Disorders in Primary Care: Prevalence and Severity of Reported Symptoms.

BACKGROUND: Most patients with substance use disorders (SUDs) never receive treatment and SUDs are under-recognized in primary care (PC) where patients can be treated or linked to treatment. Asking PC patients to directly report SUD symptoms on questionnaires might help identify SUDs but to our knowledge, this approach is previously untested. OBJECTIVE: To describe the prevalence and severity of DSM-5 SUD symptoms reported by PC patients as part of routine care. DESIGN: Cross-sectional study using secondary data. PARTICIPANTS: A total of 241,265 adult patients who visited one of 25 PC sites in an integrated health system in Washington state and had alcohol, cannabis, or other drug use screening documented in their EHRs (March 2015-July 2018) were included in main analyses if they had a positive screen for high-risk substance use defined as AUDIT-C score 7-12 points, or report of past-year daily cannabis use or any other drug use. MAIN MEASURES: The main outcome was number of SUD symptoms based on Diagnostic and Statistical Manual, 5th edition (DSM-5), reported on Symptom Checklists (0-11) for alcohol or other drugs: 2-3 mild; 4-5 moderate; 6-11 severe. RESULTS: Of screened patients, 16,776 (5.7%) reported high-risk use of alcohol (2.4%), cannabis (3.9%), and/or other drugs (1.7%), and 65.0-69.9% of those completed Symptom Checklists. Of those with high-risk alcohol use, 52.5% (95% CI 50.9-54.0%) reported ≥ 2 symptoms consistent with mild-severe alcohol use disorders. Of those reporting daily cannabis use, 29.8% (28.6-30.9%) reported ≥ 2 symptoms consistent with mild-severe SUDs. Of those reporting any other drug use, 37.5% (35.7-39.3%) reported ≥ 2 symptoms consistent with mild-severe SUDs. CONCLUSIONS AND RELEVANCE: Many PC patients who screened positive for high-risk substance use reported symptoms consistent with DSM-5 SUDs on self-report Symptom Checklists. Use of SUD Symptom Checklists could support PC providers in making SUD diagnoses and initiating discussions of substance use.

Effect of a Care Management Intervention on 12-Month Drinking Outcomes Among Patients With and Without DSM-IV Alcohol Dependence at Baseline.

BACKGROUND: The CHOICE care management intervention did not improve drinking relative to usual care (UC) for patients with frequent heavy drinking at high risk of alcohol use disorders. Patients with alcohol dependence were hypothesized to benefit most. We conducted preplanned secondary analyses to test whether the CHOICE intervention improved drinking relative to UC among patients with and without baseline DSM-IV alcohol dependence. METHODS: A total of 304 patients reporting frequent heavy drinking from 3 VA primary care clinics were randomized (stratified by DSM-IV alcohol dependence, sex, and site) to UC or the patient-centered, nurse-delivered, 12-month CHOICE care management intervention. Primary outcomes included percent heavy drinking days (%HDD) using 28-day timeline follow-back and a "good drinking outcome" (GDO)-abstaining or drinking below recommended limits and no alcohol-related symptoms on the Short Inventory of Problems at 12 months. Generalized estimating equation binomial regression models (clustered on provider) with interaction terms between dependence and intervention group were fit. RESULTS: At baseline, 59% of intervention and UC patients had DSM-IV alcohol dependence. Mean drinking outcomes improved for all subgroups. For participants with dependence, 12-month outcomes did not differ for intervention versus UC patients (%HDD 37% versus 38%, p = 0.76 and GDO 16% versus 16%, p = 0.77). For participants without dependence, %HDD did not differ between intervention (41%) and UC (31%) patients (p = 0.12), but the proportion with GDO was significantly higher among UC participants (26% versus 13%, p = 0.046). Neither outcome was significantly modified by dependence (interaction p values 0.19 for %HDD and 0.10 for GDO). CONCLUSIONS: Among participants with frequent heavy drinking, care management had no benefit relative to UC for patients with dependence, but UC may have had benefits for those without dependence. TRIAL REGISTRATION: ClinicalTrials.gov NCT01400581.

Level of Alcohol Use Associated with HIV Care Continuum Targets in a National U.S. Sample of Persons Living with HIV Receiving Healthcare.

We evaluated associations between levels of alcohol use and HIV care continuum components using national Veterans Aging Cohort Study data for all patients with HIV and AUDIT-C screening (2/1/2008-9/30/2014). Poisson regression models evaluated associations between alcohol use levels (non-drinking, low-, medium-, high-, and very high-level drinking) and: (1) engagement with care (documented CD4 cells/µl or viral load copies/ml labs), (2) ART treatment (≥ 1 prescription), and (3) viral suppression (HIV RNA < 500 copies/ml) within one year. Among 33,224 patients, alcohol use level was inversely associated with all care continuum outcomes (all p < 0.001). Adjusted prevalence of care engagement ranged from 77.8% (95% CI 77.1-78.4%) for non-drinking to 69.1% (66.6-71.6%) for high-level drinking. The corresponding range for ART treatment was 74.0% (73.3-74.7%) to 60.1% (57.3-62.9%) and for viral suppression was 57.3% (56.5-58.1%) to 38.3% (35.6-41.1%). Greater alcohol use is associated with suboptimal HIV treatment across the HIV care continuum.

Increased Rates of Documented Alcohol Counseling in Primary Care: More Counseling or Just More Documentation?

BACKGROUND: Clinical performance measures often require documentation of patient counseling by healthcare providers. Little is known about whether such measures encourage delivery of counseling or merely its documentation. OBJECTIVE: To assess changes in provider documentation of alcohol counseling and patient report of receiving alcohol counseling in the Veterans Administration (VA) from 2009 to 2012. DESIGN: Retrospective time-series analysis. PARTICIPANTS: A total of 5413 men who screened positive for unhealthy alcohol use at an outpatient visit and responded to a confidential mailed survey regarding alcohol counseling from a VA provider in the prior year. MAIN MEASURES: Rates of provider documentation of alcohol counseling in the electronic health record and patient report of such counseling on the survey were assessed over 4 fiscal years. Annual rates were calculated overall and with patients categorized into four mutually exclusive groups based on their own reports of alcohol counseling (yes/no) and whether alcohol counseling was documented by a provider (yes/no). KEY RESULTS: Provider documentation of alcohol counseling increased 23.6% (95% CI: 17.0, 30.2), from 59.4% to 83.0%, while patient report of alcohol counseling showed no significant change (4.0%, 95% CI: -2.3, 10.3), increasing from 66.1% to 70.1%. An 18.7% (95% CI: 11.7, 25.7) increase in the proportion of patients who reported counseling that was documented by a provider largely reflected a 14.7% decline (95% CI: 8.5, 20.8) in the proportion of patients who reported alcohol counseling that was not documented by a provider. The proportion of patients who did not report counseling but whose providers documented it did not show a significant change (4.9%, 95%CI: 0.0, 9.9). CONCLUSIONS: If patient report is accurate, increased rates of documented alcohol counseling in the VA from 2009 to 2012 predominantly reflected improved documentation of previously undocumented counseling rather than delivery of additional counseling or increased documentation of counseling that did not meaningfully occur.

Barriers to and Facilitators of Alcohol Use Disorder Pharmacotherapy in Primary Care: A Qualitative Study in Five VA Clinics.

BACKGROUND: Three medications are FDA-approved and recommended for treating alcohol use disorders (AUD) but they are not offered to most patients with AUD. Primary care (PC) may be an optimal setting in which to offer and prescribe AUD medications, but multiple barriers are likely. OBJECTIVE: This qualitative study used social marketing theory, a behavior change approach that employs business marketing techniques including "segmenting the market," to describe (1) barriers and facilitators to prescribing AUD medications in PC, and (2) beliefs of PC providers after they were segmented into groups more and less willing to prescribe AUD medications. DESIGN: Qualitative, interview-based study. PARTICIPANTS: Twenty-four providers from five VA PC clinics. APPROACH: Providers completed in-person semi-structured interviews, which were recorded, transcribed, and analyzed using social marketing theory and thematic analysis. Providers were divided into two groups based on consensus review. KEY RESULTS: Barriers included lack of knowledge and experience, beliefs that medications cannot replace specialty addiction treatment, and alcohol-related stigma. Facilitators included training, support for prescribing, and behavioral staff to support follow-up. Providers more willing to prescribe viewed prescribing for AUD as part of their role as a PC provider, framed medications as a potentially effective "tool" or "foot in the door" for treating AUD, and believed that providing AUD medications in PC might catalyze change while reducing stigma and addressing other barriers to specialty treatment. Those less willing believed that medications could not effectively treat AUD, and that treating AUD was the role of specialty addiction treatment providers, not PC providers, and would require time and expertise they do not have. CONCLUSIONS: We identified barriers to and facilitators of prescribing AUD medications in PC, which, if addressed and/or capitalized on, may increase provision of AUD medications. Providers more willing to prescribe may be the optimal target of a customized implementation intervention to promote changes in prescribing.

Association of Alcohol Misuse With Sexual Identity and Sexual Behavior in Women Veterans.

BACKGROUND: Sexual minority women report greater alcohol misuse than heterosexual women in the general population, with more pronounced differences found among younger age groups. It is unknown whether these differences exist among women veterans. OBJECTIVE: We evaluated differences in alcohol misuse across two dimensions of sexual orientation (identity and behavior) among women veterans, and examined whether these differences were modified by age. METHODS: Women veterans were recruited via the internet to participate in an online survey. Participants provided information on their self-reported sexual identity and behavior and responded to the validated 3-item Alcohol Use Disorders Identification Test-Consumption questionnaire (AUDIT-C). Regression models were used to compare the prevalence of alcohol misuse (AUDIT-C ≥ 3) and severity (AUDIT-C scores) across sexual identity and behavior and to test effect modification by age. RESULTS: Among the 702 participants (36% lesbian/bisexual), prevalence and severity of alcohol misuse varied by both sexual identity and behavior, but there were significant interactions with age. Prevalence and severity of alcohol misuse were higher among relatively younger self-identified lesbians compared to heterosexual women. Similarly, both prevalence and severity of alcohol misuse were generally higher among younger women who had any sex with women compared to those who had sex only with men. CONCLUSIONS/IMPORTANCE: In this online study of women veterans, younger sexual minority women were more likely to screen positive for alcohol misuse, and they had more severe alcohol misuse, than their heterosexual counterparts. Prevention and treatment efforts focused specifically on sexual minority women veterans may be needed.