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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.
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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.
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Alcoholismo , Psicometría , Humanos , Masculino , Femenino , Psicometría/métodos , Persona de Mediana Edad , Adulto , Encuestas y Cuestionarios , Estudios Transversales , Alcoholismo/diagnóstico , Alcoholismo/psicología , Portales del Paciente/estadística & datos numéricos , Evaluación de Síntomas/métodos , Washingtón , Adulto Joven , AncianoRESUMEN
AIMS: Among individuals with alcohol use disorder (AUD), sleep disturbances are pervasive and contribute to the etiology and maintenance of AUD. However, despite increased attention toward the relationship between alcohol use and sleep, limited empirical research has systematically examined whether reductions in drinking during treatment for AUD are associated with improvements in sleep problems. METHODS: We used data from a multisite, randomized, controlled trial that compared 6 months of treatment with gabapentin enacarbil extended-release with placebo for adults with moderate-to-severe AUD (N = 346). The Timeline Follow-back was used to assess WHO risk drinking level reductions and the Pittsburgh Sleep Quality Index was used to assess sleep quality over the prior month at baseline and the end of treatment. RESULTS: Sleep problem scores in the active medication and placebo groups improved equally. Fewer sleep problems were noted among individuals who achieved at least a 1-level reduction (B = -0.99, 95% confidence interval (CI) [-1.77, -0.20], P = .014) or at least a 2-level reduction (B = -0.80, 95% CI [-1.47, -0.14], P = .018) in WHO risk drinking levels at the end of treatment. Reductions in drinking, with abstainers excluded from the analysis, also predicted fewer sleep problems at the end of treatment (1-level: B = -1.01, 95% CI [-1.83, -0.20], P = .015; 2-level: B = -0.90, 95% CI [-1.59, -0.22], P = .010). CONCLUSIONS: Drinking reductions, including those short of abstinence, are associated with improvements in sleep problems during treatment for AUD. Additional assessment of the causal relationships between harm-reduction approaches to AUD and improvements in sleep is warranted.
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Alcoholismo , Adulto , Humanos , Consumo de Bebidas Alcohólicas/terapia , Alcoholismo/complicaciones , Alcoholismo/tratamiento farmacológico , Organización Mundial de la Salud , Ensayos Clínicos Controlados Aleatorios como AsuntoRESUMEN
OBJECTIVES: This study aimed to evaluate the validity of World Health Organization (WHO) risk drinking level reductions as meaningful endpoints for clinical practice and research. This study examined whether such reductions were associated with a lower likelihood of a current alcohol use disorder (AUD) diagnosis and fewer AUD criteria. METHODS: We conducted a secondary data analysis to address these objectives using data from a multisite randomized controlled trial of gabapentin enacarbil extended release in treating moderate to severe AUD among adults (N = 346). Participants received gabapentin enacarbil extended release or placebo for 6 months. The timeline follow-back was used to assess WHO risk drinking level reductions, and the Mini-International Neuropsychiatric Interview was used to assess Diagnostic and Statistical Manual of Mental Disorders (Fifth Edition) AUD diagnosis and criteria at baseline (past year) and end of treatment (past month). RESULTS: Most participants (80.1%) achieved at least a 1-level reduction in the WHO risk drinking levels from baseline to end of treatment, and nearly half of participants (49.8%) achieved at least a 2-level reduction. At least a 1-level reduction or at least a 2-level reduction in WHO risk drinking level predicted lower odds of an active AUD diagnosis (1-level: odds ratio, 0.74 [95% confidence interval (CI), 0.66-0.84]; 2-level: odds ratio, 0.71 [95% CI, 0.64-0.79]) and fewer AUD criteria (1-level: B , -1.66 [95% CI, -2.35 to -0.98]; 2-level: B , -1.76 [95% CI, -2.31 to -1.21]) at end of treatment. CONCLUSIONS: World Health Organization risk drinking level reductions correlate with Diagnostic and Statistical Manual of Mental Disorders (Fifth Edition) AUD diagnosis and criteria, providing further evidence for their use as endpoints in alcohol intervention trials, which has potential implications for broadening the base of AUD treatment.
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Alcoholismo , Organización Mundial de la Salud , Humanos , Masculino , Femenino , Adulto , Persona de Mediana Edad , Alcoholismo/diagnóstico , Alcoholismo/tratamiento farmacológico , Consumo de Bebidas Alcohólicas , Resultado del Tratamiento , Preparaciones de Acción RetardadaRESUMEN
INTRODUCTION: Substance use disorders (SUDs) are underdiagnosed in healthcare settings. The Substance Use Symptom Checklist (SUSC) is a practical, patient-report questionnaire that has been used to assess SUD symptoms based on Diagnostic and Statistical Manual of Mental Disorders-5th edition (DSM-5) criteria. This study evaluates the test-retest reliability of SUSCs completed in primary and mental health care settings. METHODS: We identified 1194 patients who completed two SUSCs 1-21 days apart as part of routine care after reporting daily cannabis use and/or any past-year other drug use on behavioral health screens. Test-retest reliability of SUSC scores was evaluated within the full sample, subsamples who completed both checklists in primary care (n=451) or mental health clinics (n=512) where SUSC implementation differed, and subgroups defined by sex, insurance status, age, and substance use reported on behavioral health screens. RESULTS: In the full sample, test-retest reliability was high for indices reflecting the number of SUD symptoms endorsed (ICC=0.75, 95% CI:0.72-0.77) and DSM-5 SUD severity (kappa=0.72, 95% CI:0.69-0.75). These reliability estimates were higher in primary care (ICC=0.81, 95% CI:0.77-0.84; kappa=0.79, 95% CI:0.75-0.82, respectively) than in mental health clinics (ICC=0.74, 95% CI:0.70-0.78; kappa=0.73, 95% CI:0.68-0.77). Reliability differed by age and substance use reported on behavioral health screens, but not by sex or insurance status. CONCLUSIONS: The SUSC has good-to-excellent test-retest reliability when completed as part of routine primary or mental health care. Symptom checklists can reliably measure symptoms consistent with DSM-5 SUD criteria, which may aid SUD-related care in primary care and mental health settings.
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Lista de Verificación , Trastornos Relacionados con Sustancias , Humanos , Manual Diagnóstico y Estadístico de los Trastornos Mentales , Salud Mental , Reproducibilidad de los Resultados , Instituciones de Atención Ambulatoria , Trastornos Relacionados con Sustancias/diagnóstico , Trastornos Relacionados con Sustancias/terapia , Atención Primaria de SaludRESUMEN
BACKGROUND: The Alcohol Use Disorders Identification Test-Consumption (AUDIT-C) is a three-item screening measure of unhealthy alcohol use that is widely used in healthcare settings. Evidence shows high test-retest reliability of the AUDIT-C in research samples, but most studies had limited external validity and used small samples that could not be used to evaluate reliability across demographic subgroups and/or screening modalities. This study evaluates the test-retest reliability of the AUDIT-C completed in routine care in a large primary care sample, including across demographic subgroups defined by age, sex, race, ethnicity, and screening modality (i.e., completed in-clinic or online). METHODS: We used electronic health record (EHR) data from Kaiser Permanente Washington. The sample included 18,491 adult primary care patients who completed two AUDIT-C screens 1-21 days apart as part of routine care in 2021. Test-retest reliability was evaluated for AUDIT-C total scores (0-12) and for a binary measure indicating unhealthy alcohol use (scores ≥3 women, ≥4 men). Using previously established cutoffs, we interpreted reliability coefficients >0.75 as indicating "excellent" reliability. RESULTS: AUDIT-C screens completed in routine care and documented in EHRs had excellent test-retest reliability for total scores (ICC = 0.87, 95% CI: 0.87-0.87) and the binary indicator of unhealthy alcohol use (κ = 0.79, 95% CI: 0.78-0.80). Reliability coefficients were good to excellent across all demographic groups and for in-clinic and online modalities. Higher reliability was seen when both screens were completed through online patient portals (ICC = 0.93, 95% CI: 0.93-0.93) versus in-clinic (ICC = 0.81, 95% CI: 0.79-0.82) or when one screen was completed using each modality (ICC = 0.83, 95% CI: 0.82-0.83). Lower reliability was seen in American Indian/Alaska Native (ICC = 0.82, 95% CI: 0.75-0.87) and multiracial individuals (ICC = 0.82, 95% 0.80-0.84). CONCLUSIONS: In real-world routine care conditions, AUDIT-C screens have excellent test-retest reliability across demographic subgroups and modalities (online and in-clinic). Future research should examine why reliability varies slightly across modalities and demographic subgroups.
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BACKGROUND: Abstinence has historically been considered the preferred goal of alcohol use disorder (AUD) treatment. However, most individuals with AUD do not want to abstain and many are able to reduce their drinking successfully. Craving is often a target of pharmacological and behavioral interventions for AUD, and reductions in craving may signal recovery. Whether reductions in drinking during AUD treatment are associated with reductions in craving has not been well examined. METHODS: We conducted secondary analyses of data from three AUD clinical trials (N's= 1327, 346, and 200). Drinking reductions from baseline to the end of treatment were measured as changes in World Health Organization (WHO) risk drinking levels; alcohol craving was measured using validated self-report measures. Regression analyses tested whether drinking reductions were associated with end-of-treatment craving reductions; moderation analyses tested whether associations between drinking reduction and end-of-treatment craving differed across AUD severity. RESULTS: Reductions of at least 1 or at least 2 WHO risk drinking levels were associated with lower craving (all p's < 0.05). Results were substantively similar after removing abstainers at the end-of-treatment. Associations between drinking reductions and craving were generally not moderated by AUD severity. CONCLUSIONS: Individuals with WHO risk drinking level reductions reported significantly lower craving, as compared to those who did not achieve meaningful reductions in drinking. The results demonstrate the utility of WHO risk drinking levels as AUD clinical trial endpoints and provide evidence that drinking reductions mitigate craving.
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OBJECTIVE: The Alcohol Addiction Research Domain Criteria (AARDoC) is an organizational framework for assessing heterogeneity in addictive disorders organized across the addiction cycle domains of incentive salience, negative emotionality, and executive functioning and may have benefits for precision medicine. Recent work found pretreatment self-report items mapped onto the addiction cycle domains and predicted 1- and 3-year alcohol use disorder treatment outcomes. Given the potential utility of the addiction cycle domains for predicting relevant treatment outcomes, this study sought to evaluate the longitudinal measurement invariance of the domains. METHOD: We conducted a secondary analysis of individuals with alcohol use disorder (n = 1,383, 30.9% female, 76.8% non-Hispanic White, 11.2% Hispanic) who participated in the COMBINE study. Eleven items assessed at pre- and posttreatment were included in exploratory structural equation modeling (ESEM) and longitudinal invariance analyses. RESULTS: The pre- and posttreatment ESEM models had factor loadings consistent with the three addiction cycle domains and fit the data well. The ESEM factor structure was invariant from pre- to posttreatment (representing configural invariance) and metric invariance (factor loadings) was largely supported, but analyses failed to support scalar invariance (item-level thresholds) of the addiction cycle domains. CONCLUSIONS: A three-factor structure representing addiction cycle domains can be modeled using brief self-report measures pre- and posttreatment. Individuals demonstrated a downward shift in the level of item endorsement, indicating improvement with treatment. Although this 11-item measure might be useful at baseline for informing treatment decisions, results indicate the need to exercise caution in comparing the addiction cycle domains pre- to posttreatment within persons. (PsycInfo Database Record (c) 2023 APA, all rights reserved).
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BACKGROUND: Brief cannabis screening followed by standardized assessment of symptoms may support diagnosis and treatment of cannabis use disorder (CUD). This study tested whether the probability of a medical provider diagnosing and treating CUD increased with the number of substance use disorder (SUD) symptoms documented in patients' EHRs. METHODS: This observational study used EHR and claims data from an integrated healthcare system. Adult patients were included who reported daily cannabis use and completed the Substance Use Symptom Checklist, a scaled measure of DSM-5 SUD symptoms (0-11), during routine care 3/1/2015-3/1/2021. Logistic regression estimated associations between SUD symptom counts and: 1) CUD diagnosis; 2) CUD treatment initiation; and 3) CUD treatment engagement, defined based on Healthcare Effectiveness Data and Information Set (HEDIS) ICD-codes and timelines. We tested moderation across age, gender, race, and ethnicity. RESULTS: Patients (N=13,947) were predominantly middle-age, male, White, and non-Hispanic. Among patients reporting daily cannabis use without other drug use (N=12,568), the probability of CUD diagnosis, treatment initiation, and engagement increased with each 1-unit increase in Symptom Checklist score (p's<0.001). However, probabilities of diagnosis, treatment, and engagement were low, even among those reporting ≥2 symptoms consistent with SUD: 14.0% diagnosed (95% CI: 11.7-21.6), 16.6% initiated treatment among diagnosed (11.7-21.6), and 24.3% engaged in treatment among initiated (15.8-32.7). Only gender moderated associations between Symptom Checklist and diagnosis (p=0.047) and treatment initiation (p=0.012). Findings were similar for patients reporting daily cannabis use with other drug use (N=1379). CONCLUSION: Despite documented symptoms, CUD was underdiagnosed and undertreated in medical settings.
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Cannabis , Alucinógenos , Abuso de Marihuana , Trastornos Relacionados con Sustancias , Adulto , Humanos , Masculino , Persona de Mediana Edad , Abuso de Marihuana/complicaciones , Abuso de Marihuana/diagnóstico , Abuso de Marihuana/terapia , Atención Primaria de Salud , Factores de Riesgo , Trastornos Relacionados con Sustancias/complicaciones , Trastornos Relacionados con Sustancias/diagnóstico , Trastornos Relacionados con Sustancias/terapia , FemeninoRESUMEN
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.
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Instituciones de Atención Ambulatoria , Trastornos Relacionados con Opioides , Humanos , Impulso (Psicología) , Análisis de Series de Tiempo Interrumpido , Modelos Logísticos , Trastornos Relacionados con Opioides/epidemiologíaAsunto(s)
Buprenorfina , Estimulantes del Sistema Nervioso Central , Metanfetamina , Trastornos Relacionados con Opioides , Humanos , Buprenorfina/uso terapéutico , Metanfetamina/efectos adversos , Pacientes Ambulatorios , Tratamiento de Sustitución de Opiáceos , Estimulantes del Sistema Nervioso Central/efectos adversos , Trastornos Relacionados con Opioides/tratamiento farmacológicoRESUMEN
BACKGROUND: Methadone, a cornerstone of opioid use disorder treatments for many decades, is an essential tool for combatting the opioid epidemic. However, requirements for observing methadone dosing in person through direct observed therapy (DOT) impose significant barriers for many patients. Digital technology can facilitate remote DOT, which could reduce barriers to methadone treatment. Currently, there are limited data on the usability of such technology among patients and counselors in methadone treatment settings. OBJECTIVE: The primary objective of this study was to assess the workload, usability, and engagement of a video-based DOT mobile app for patients with opioid use disorder receiving methadone treatment. The secondary objective was to assess the workload, usability, and engagement of the provider-facing app portal used by counselors. METHODS: Patients (n=12) and counselors (n=3) who previously tried video DOT for methadone through a smartphone app in an opioid treatment program participated in usability testing sessions. Participants completed essential tasks for video DOT, then provided ratings of workload (NASA Task Load Index), usability (modified System Usability Scale), and engagement (modified Engagement Scale) with the core features of the video DOT program. RESULTS: Patients and counselors reported low mental, physical, and temporal demands, successful performance, low effort, and low frustration associated with activities. Patients reported high usability (mean 85, SD 9.5) and engagement (mean 3.8, SD 1.1); counselors reported moderate usability (mean 43.3, SD 17.7) and engagement (mean 2.81, SD 0.63). CONCLUSIONS: A mobile health app that facilitates video-based DOT for methadone required a low workload for patients and counselors and was highly usable for patients in an opioid treatment program; however, there are opportunities to improve usability and engagement for the counselor-facing portal.
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BACKGROUND: In the United States, methamphetamine-related overdoses have tripled from 2015 to 2020 and continue to rise. However, efficacious treatments such as contingency management (CM) are often unavailable in health systems. OBJECTIVE: We conducted a single-arm pilot study to evaluate the feasibility, engagement, and usability of a fully remotely delivered mobile health CM program offered to adult outpatients who used methamphetamine and were receiving health care within a large university health system. METHODS: Participants were referred by primary care or behavioral health clinicians between September 2021 and July 2022. Eligibility criteria screening was conducted by telephone and included self-reported methamphetamine use on ≥5 out of the past 30 days and a goal of reducing or abstaining from methamphetamine use. Eligible participants who agreed to take part then completed an initial welcome phase that included 2 videoconference calls to register for and learn about the CM program and 2 "practice" saliva-based substance tests prompted by a smartphone app. Participants who completed these welcome phase activities could then receive the remotely delivered CM intervention for 12 consecutive weeks. The intervention included approximately 24 randomly scheduled smartphone alerts requesting a video recording of themselves taking a saliva-based substance test to verify recent methamphetamine abstinence, 12 weekly calls with a CM guide, 35 self-paced cognitive behavioral therapy modules, and multiple surveys. Financial incentives were disbursed via reloadable debit cards. An intervention usability questionnaire was completed at the midpoint. RESULTS: Overall, 37 patients completed telephone screenings, with 28 (76%) meeting the eligibility criteria and consenting to participate. Most participants who completed a baseline questionnaire (21/24, 88%) self-reported symptoms consistent with severe methamphetamine use disorder, and most had other co-occurring non-methamphetamine substance use disorders (22/28, 79%) and co-occurring mental health disorders (25/28, 89%) according to existing electronic health records. Overall, 54% (15/28) of participants successfully completed the welcome phase and were able to receive the CM intervention. Among these participants, engagement with substance testing, calls with CM guides, and cognitive behavioral therapy modules varied. Rates of verified methamphetamine abstinence in substance testing were generally low but varied considerably across participants. Participants reported positive opinions about the intervention's ease of use and satisfaction with the intervention. CONCLUSIONS: Fully remote CM can be feasibly delivered within health care settings lacking existing CM programs. Although remote delivery may help reduce barriers to treatment access, many patients who use methamphetamine may struggle to engage with initial onboarding. High rates of co-occurring psychiatric conditions in the patient population may also contribute to uptake and engagement challenges. Future efforts could leverage greater human-to-human connection, more streamlined onboarding procedures, larger incentives, longer durations, and the incentivization of non-abstinence-based recovery goals to increase uptake and engagement with fully remote mobile health-based CM.
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BACKGROUND: The Alcohol Use Disorders Identification Test-Consumption version (AUDIT-C) has been robustly validated as a point-in-time screen for unhealthy alcohol use, but less is known about the significance of changes in AUDIT-C scores from routine screenings over time. Unhealthy alcohol use and depression commonly co-occur, and changes in drinking often co-occur with changes in depression symptoms. We assess the associations between changes in AUDIT-C scores and changes in depression symptoms reported on brief screens completed in routine care. METHODS: The study sample included 198,335 primary care patients who completed two AUDIT-C screens 11 to 24 months apart and the Patient Health Questionnaire-2 (PHQ-2) depression screen on the same day as each AUDIT-C. Both screening measures were completed as part of routine care within a large health system in Washington state. AUDIT-C scores were categorized to reflect five drinking levels at both time points, resulting in 25 subgroups with different change patterns. For each of the 25 subgroups, within-group changes in the prevalence of positive PHQ-2 depression screens were characterized using risk ratios (RRs) and McNemar's tests. RESULTS: Patient subgroups with increases in AUDIT-C risk categories generally experienced increases in the prevalence of positive depression screens (RRs ranging from 0.95 to 2.00). Patient subgroups with decreases in AUDIT-C risk categories generally experienced decreases in the prevalence of positive depression screens (RRs ranging from 0.52 to 1.01). Patient subgroups that did not have changes in AUDIT-C risk categories experienced little or no change in the prevalence of positive depression screens (RRs ranging from 0.98 to 1.15). CONCLUSIONS: As hypothesized, changes in alcohol consumption reported on AUDIT-C screens completed in routine care were associated with changes in depression screening results. Results support the validity and clinical utility of monitoring changes in AUDIT-C scores over time as a meaningful measure of changes in drinking.
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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.
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Alcoholismo , Buprenorfina , Abuso de Marihuana , Trastornos Relacionados con Opioides , Humanos , Salud de los Veteranos , Trastornos Relacionados con Opioides/epidemiología , Pacientes Ambulatorios , Analgésicos Opioides , Tratamiento de Sustitución de OpiáceosRESUMEN
Importance: Substance use disorders (SUDs) are underrecognized in primary care, where structured clinical interviews are often infeasible. A brief, standardized substance use symptom checklist could help clinicians assess SUD. Objective: To evaluate the psychometric properties of the Substance Use Symptom Checklist (hereafter symptom checklist) used in primary care among patients reporting daily cannabis use and/or other drug use as part of population-based screening and assessment. Design, Setting, and Participants: This cross-sectional study was conducted among adult primary care patients who completed the symptom checklist during routine care between March 1, 2015, and March 1, 2020, at an integrated health care system. Data analysis was conducted from June 1, 2021, to May 1, 2022. Main Outcomes and Measures: The symptom checklist included 11 items corresponding to SUD criteria in the Diagnostic and Statistical Manual for Mental Disorders (Fifth Edition) (DSM-5). Item response theory (IRT) analyses tested whether the symptom checklist was unidimensional and reflected a continuum of SUD severity and evaluated item characteristics (discrimination and severity). Differential item functioning analyses examined whether the symptom checklist performed similarly across age, sex, race, and ethnicity. Analyses were stratified by cannabis and/or other drug use. Results: A total of 23â¯304 screens were included (mean [SD] age, 38.2 [5.6] years; 12â¯554 [53.9%] male patients; 17â¯439 [78.8%] White patients; 20â¯393 [87.5%] non-Hispanic patients). Overall, 16â¯140 patients reported daily cannabis use only, 4791 patients reported other drug use only, and 2373 patients reported both daily cannabis and other drug use. Among patients with daily cannabis use only, other drug use only, or both daily cannabis and other drug use, 4242 (26.3%), 1446 (30.2%), and 1229 (51.8%), respectively, endorsed 2 or more items on the symptom checklist, consistent with DSM-5 SUD. For all cannabis and drug subsamples, IRT models supported the unidimensionality of the symptom checklist, and all items discriminated between higher and lower levels of SUD severity. Differential item functioning was observed for some items across sociodemographic subgroups but did not result in meaningful change (<1 point difference) in the overall score (0-11). Conclusions and Relevance: In this cross-sectional study, a symptom checklist, administered to primary care patients who reported daily cannabis and/or other drug use during routine screening, discriminated SUD severity as expected and performed well across subgroups. Findings support the clinical utility of the symptom checklist for standardized and more complete SUD symptom assessment to help clinicians make diagnostic and treatment decisions in primary care.
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Cannabis , Trastornos Relacionados con Sustancias , Adulto , Humanos , Masculino , Femenino , Lista de Verificación , Psicometría , Estudios Transversales , Trastornos Relacionados con Sustancias/diagnóstico , Atención Primaria de SaludRESUMEN
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.
Asunto(s)
Buprenorfina , Trastornos Relacionados con Opioides , Veteranos , Humanos , Buprenorfina/uso terapéutico , Salud Mental , Dolor , Trastornos Relacionados con Opioides/tratamiento farmacológico , Trastornos Relacionados con Opioides/epidemiología , Atención Primaria de Salud , Analgésicos Opioides/uso terapéutico , Tratamiento de Sustitución de OpiáceosRESUMEN
Background: Alcohol use disorder (AUD) treatments, including medications, are increasingly offered via telehealth.Objective: This study characterizes 90-day treatment retention and changes in objectively measured blood alcohol concentration (BAC) in a large cohort receiving AUD telehealth.Methods: Patients received AUD treatment through Ria, a virtual (telehealth) program offering AUD treatment that is tailored to patient goals (e.g. abstinence or controlled drinking). Patients were encouraged to complete breathalyzer readings twice daily for measurement-based care. We characterized rates of 90-day treatment retention (i.e. completing a BAC reading or medical/coaching encounter on the 90th day or later) and used growth curve analyses to model changes in daily estimated peak BAC over 90 days.Results: Of 4121 patients (51.5% women), 50.1% had 90-day treatment retention (n = 2066, 52.2% women). Most patients received prescriptions for AUD medications (84.6%) and completed encounters with medical providers (86.7%) and coaches (86.1%). Patients with 90-day retention provided 184,817 BAC readings in the first 90 days. Growth curve analyses revealed significant reductions in daily estimated peak BAC (p < .001) from a mean of 0.092 (day 1) to 0.038 (day 90). Similar magnitudes of BAC reduction were observed for men and women and for patients with abstinence and controlled drinking goals.Conclusion: Telehealth appears to be a viable approach to delivering AUD treatments in a manner that promotes drinking reductions. Telehealth approaches can yield reductions in objectively measured BAC, including for some patient subgroups that have historically faced greater stigma in AUD treatment settings, such as women and people with non-abstinence drinking goals.
Asunto(s)
Alcoholismo , Telemedicina , Masculino , Humanos , Femenino , Alcoholismo/tratamiento farmacológico , Nivel de Alcohol en Sangre , Consumo de Bebidas AlcohólicasRESUMEN
BACKGROUND AND AIMS: The Opioid Use Disorder (OUD) Cascade of Care is a public health model that has been used to measure population-level OUD risk, treatment engagement, retention, service and outcome indicators. However, no studies have examined its relevance for American Indian and Alaska Native (AI/AN) communities. Thus, we aimed to understand (1) the utility of existing stages and (2) the relative 'fit' of the OUD Cascade of Care from a tribal perspective. DESIGN, SETTING, PARTICIPANTS AND MEASUREMENTS: Qualitative analysis of in-depth interviews with 20 individuals who were knowledgeable regarding the treatment of OUD in an Anishinaabe tribal setting in Minnesota, USA. Community member roles included clinicians, peer support specialists and cultural practitioners, among others. Thematic analysis was used to analyze the data. FINDINGS: Participants identified the key transition points of prevention, assessment, inpatient/outpatient pathways and recovery as relevant to their community. They re-imagined an Aanji'bide (Changing our Paths) model of opioid recovery and change that was non-linear; included developmental stage and individual pathways; and demonstrated resilience through connection to culture/spirituality, community and others. CONCLUSIONS: Community members living/working in a rural tribal nation in Minnesota, USA identified non-linearity and cultural connection as key elements to include in an Anishinaabe-centered model of opioid recovery and change.
Asunto(s)
Asistencia Sanitaria Culturalmente Competente , Indígenas Norteamericanos , Trastornos Relacionados con Opioides , Atención Dirigida al Paciente , Humanos , Minnesota , Trastornos Relacionados con Opioides/diagnóstico , Trastornos Relacionados con Opioides/etnología , Trastornos Relacionados con Opioides/terapia , Estados Unidos , Asistencia Sanitaria Culturalmente Competente/etnología , Asistencia Sanitaria Culturalmente Competente/métodos , Población Rural , Atención Dirigida al Paciente/métodosRESUMEN
BACKGROUND: Screening for unhealthy alcohol use in primary care may help identify patients at risk for negative health outcomes. AIMS: This study examined the associations between 1) screening with the AUDIT-C (alcohol consumption) and 2) an Alcohol Symptom Checklist (symptoms of alcohol use disorder) and subsequent-year hospitalizations. METHODS: This retrospective cohort study was conducted in 29 primary care clinics in Washington State. Patients were screened in routine care (10/1/2016-2/1/2019) with the AUDIT-C (0-12) and administered the Alcohol Symptom Checklist (0-11) if they had AUDIT-C score ≥ 7. All-cause hospitalizations were measured within 1 year of the AUDIT-C and Alcohol Symptom Checklist. AUDIT-C and Alcohol Symptom Checklist scores were categorized based on previously used cut-points. FINDINGS: Of 305,376 patients with AUDIT-Cs, 5.3% of patients were hospitalized in the following year. AUDIT-C scores had a J-shaped relationship with hospitalizations, with risk for all-cause hospitalizations higher for patients with the AUDIT-C scores 9-12 (12.1%; 95% CI: 10.6-13.7%, relative to a comparison group of those with AUDIT-C scores 1-2 (female)/1-3 (male) (3.7%; 95% CI: 3.6-3.8%), adjusted for socio-demographics. Patients with AUDIT-C ≥ 7 and Alcohol Symptom Checklist scores reflecting severe AUD were at increased risk of hospitalization (14.6%, 95% CI: 11.9-17.9%) relative to those with lower scores. CONCLUSIONS: Higher AUDIT-C scores were associated with higher incidence of hospitalizations except among people with low-level drinking. Among patients with AUDIT-C ≥ 7, the Alcohol Symptom Checklist identified patients at increased risk of hospitalization. This study helps demonstrate the potential clinical utility of the AUDIT-C and Alcohol Symptom Checklist.