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

Variations in documentation of alcohol use disorder (AUD) diagnoses across race, ethnicity, and sex in a health system that assesses AUD symptoms as part of routine primary care

INTRODUCTION

Prior studies have highlighted potential inequities in provider-documented alcohol use disorder (AUD) across race, ethnicity, and sex. Whether subgroup differences in AUD reflect true variation or diagnostic disparities is unknown. This study aims to describe variations in the prevalence of provider-documented AUD across race, ethnicity, and sex: 1) after adjustment for alcohol consumption, and 2) after additional adjustment for patient-reported AUD symptoms.

METHODS

In Kaiser Permanente Washington, patients with high-risk drinking (AUDIT-C score 7-12; 2.4 % of screened patients) complete a validated Alcohol Symptom Checklist of DSM-5 AUD symptoms with results documented in electronic health records. This study included Asian, Black, Latine, and White patients in primary care settings (03/2015-02/2022) who indicated high-risk drinking and thus completed an Alcohol Symptom Checklist. The prevalence of AUD was estimated for women and men across race or ethnic groups using marginally standardized generalized linear models. Models were first unadjusted, then adjusted for consumption (AUDIT-C scores 7-12), and then consumption plus AUD symptom counts (0-11).

RESULTS

Among 14,442 patients with high-risk drinking (6.0 % Asian, 5.8 % Black, 7.8 % Latine, 80.4 % White; 32.1 % women), provider-documented AUD increased with alcohol consumption and the number of AUD symptoms. The prevalence of AUD across 8 subgroups defined by race, ethnicity, and sex varied in analyses adjusted for alcohol consumption alone (range 11.6 % [95 % CI: 9.3-14.4] to 20.2 % [18.9-21.5]). However, after adjustment for both alcohol consumption and AUD symptoms, the prevalence of AUD ranged from 11.2 % [95 % CI: 7.9-15.6] to 15.0 % [95 % CI: 13.9-16.3] in women, and from 11.0 % [95 % CI: 8.7-13.8] to 15.1 % [95 % CI: 14.3-16.0] in men. AUD did not appear to vary across race or ethnicity.

CONCLUSIONS

In this study of primary care patients with high-risk drinking in a regional healthcare system that routinely assesses AUD symptoms, variations in provider-documented AUD diagnosis across race, ethnicity, and sex were observed after adjusting for alcohol consumption but were diminished after adjusting for AUD symptoms. This may suggest that among patients with similar alcohol consumption and AUD symptoms, intersectional variations in AUD diagnosis may be less apparent. Assessing AUD severity with Alcohol Symptom Checklists may help support equitable clinical AUD diagnosing.

Evaluating a 30-day alcohol abstinence challenge in heavy-drinking individuals with and without chronic pain: Feasibility, safety, and perceived benefits

INTRODUCTION

To combat high-risk alcohol consumption, we introduced a 30-day alcohol abstinence challenge targeted at heavy drinkers with and without chronic pain. Our study aimed to assess the challenge's feasibility and safety and to explore its perceived benefits. Our exploratory aim was to identify participants' coping strategies during the challenge.

METHODS

Our single-arm study recruited heavy drinkers from a pain clinic and a university setting (n = 34, 64.7% chronic pain). Participants underwent a modified community-based 30-day challenge, which included motivational interviewing, an individualized start date, and weekly phone check-ins.

RESULTS

We found the 30-day challenge was feasible and safe; 72.3% of eligible heavy drinkers participated in the challenge with no serious adverse events. Most challengers (94.1%) reported some benefit from the challenge, which included improvements in alcohol withdrawal symptoms, sleep, and alcohol abstinence self-efficacy, but not in pain. We identified 25 perceived benefits and 21 coping strategies.

CONCLUSION

Our study confirms that a 30-day alcohol abstinence challenge is a feasible and safe intervention for heavy drinkers with and without chronic pain, yielding notable health benefits. The challenge also facilitated the development of effective coping strategies. Future studies should explore the long-term benefits of such interventions in broader outpatient settings.

Do electronic health records used by primary care practices support recommended alcohol-related care?

Objective

The quality of alcohol-related prevention and treatment in US primary care is poor. The purpose of this study was to describe the extent to which Electronic Health Records (EHRs) used by 167 primary care practices across 7 states currently include the necessary prompts, clinical support, and performance reporting essential for improving alcohol-related prevention and treatment in primary care.

Materials and Methods

Experts from five regional quality improvement programs identified basic EHR features needed to support evidence-based alcohol-related prevention (ie, screening and brief intervention) and treatment of alcohol use disorders (AUD). Data were collected regarding whether EHRs included these features.

Results

EHRs from 21 vendors were used by the primary care practices. For prevention, 62% of the 167 practices' EHRs included a validated screening questionnaire, 46% automatically scored the screening instrument, 62% could report the percent screened, and 37% could report the percent screening positive. Only 7% could report the percent offered brief intervention. For alcohol treatment, 49% of practices could report the percent diagnosed with AUD, 58% and 91% allowed documentation of referral and treatment with AUD medication, respectively. Only 3% could report the percent of patients diagnosed with AUD who received treatment.

Discussion

Most EHRs observed across 167 primary care practices across 7 US states lacked basic functionality necessary to support evidence-based alcohol-related prevention and AUD treatment. Only 3% and 7% of EHRs, respectively, included the ability to report widely recommended quality measures needed to improve the quality of recommended alcohol-related prevention and treatment in primary care.

Conclusion

Improving EHR functionality is likely necessary before alcohol-related primary care can be improved.

New Alcohol-related Condition Diagnoses Are Associated With Opioid Tapers Among Patients Receiving Long-term Opioid Therapy

OBJECTIVES

The study sought to describe the association between alcohol-related conditions (ARCs) and long-term opioid therapy (LTOT) dose trajectories among patients with chronic pain. We explored if ARCs moderated the association between LTOT tapers and mortality.

METHODS

We conducted a retrospective cohort study of 3912 patients receiving LTOT. The association of ARCs before initiating LTOT with subsequent LTOT dose trajectories (increasing, decreasing, stable) was assessed using multinomial regression models. The association of LTOT trajectories with subsequently diagnosed new (incident) ARC was assessed using competing risks regression models. Lastly, we explored whether ARCs moderated the association between LTOT trajectories and all-cause mortality using Cox-proportional hazards models.

RESULTS

Overall, 6.2% (n = 244) of patients receiving LTOT were diagnosed with an ARC prior to initiating LTOT. There was no association between an ARC prior to LTOT initiation with subsequent LTOT trajectory. Among patients without an ARC diagnosis before initiating LTOT, newly diagnosed ARCs were made in 1.3% (n = 50) of patients. Patients in the decreasing LTOT trajectory were twice as likely to be diagnosed with new ARCs compared to those in the stable LTOT trajectory (adjusted hazard ratio, 2.23 [95% CI, 1.15-4.29]). The presence of ARCs did not significantly moderate the relationship between LTOT trajectories and mortality risk.

CONCLUSIONS

Patients in the decreasing LTOT trajectory are at a higher risk of developing a new ARC. Implementing routine alcohol use screening among patients with LTOT taper would enable early identification for alcohol use. Interventions to reduce alcohol use may mitigate harms associated with LTOT taper.

Diagnosis of Alcohol Use Disorder and Alcohol-Associated Liver Disease

Harmful alcohol use and alcohol use disorder (AUD) are common worldwide, and rates of alcohol-associated liver disease (ALD) are also increasing. AUD is a disease that is treatable and can be diagnosed and managed, and recovery from AUD through abstinence or reductions in drinking is possible. Management of AUD among individuals with ALD is increasingly being addressed via integrated medical and psychosocial treatment teams that can support reductions in drinking and prevent progression of liver disease. Early diagnosis of AUD and ALD can improve lives and reduce mortality.

Incidence of Hospitalizations Involving Alcohol Withdrawal Syndrome in a Primary Care Population

Importance

Alcohol withdrawal syndrome (AWS) is an important cause and complication of hospitalizations. Although common and preventable, the incidence of AWS during hospitalizations is poorly described.

Objective

To evaluate the incidence and proportional incidence of hospitalizations involving AWS in an adult primary care population overall and across patient characteristics.

Design, Setting, and Participants

This retrospective cohort study used electronic health records and insurance claims from Kaiser Permanente Washington (KPWA) between July 1, 2018, and June 30, 2022. The study included adults with 1 or more primary care visits during this period or the year prior, where primary care included annual standardized alcohol screening using the Alcohol Use Disorders Identification Test-Consumption (AUDIT-C).

Exposures

Age, sex, race, Hispanic ethnicity, AUDIT-C scores, and comorbid diagnoses.

Main Outcome and Measures

Hospitalizations involving AWS were defined by diagnosis codes documented during hospitalizations (incidence numerator). Time enrolled in KPWA determined person-enrolled-years (incidence denominator). Proportional incidence was calculated as the incidence of hospitalizations involving AWS divided by the incidence of all-cause hospitalizations. Proportional incidence was also estimated for hospitalizations involving other common chronic conditions (chronic obstructive pulmonary disease, diabetes, heart failure, and hypertension), which were also defined using hospital diagnosis codes.

Results

Among 544 825 adults engaged in primary care (mean [SD] age, 47.0 [17.9] years; 310 069 [56.9%] female; 3656 [0.7%] American Indian or Alaska Native, 55 206 [10.1%] Asian, 25 406 [4.7%] Black, 5204 [1.0%] Native Hawaiian or Other Pacific Islander, 365 780 [67.1%] White, 19 791 [3.6%] multiracial, 15 963 [2.9%] other races, and 53 819 [9.9%] unknown race; 33 987 [6.2%] Hispanic, 414 269 [76.0%] not Hispanic, and 96 569 [17.7%] unknown ethnicity), incidence of hospitalizations involving AWS was 169 (95% CI, 159-179) per 100 000 person-enrolled-years overall but as high as 15 347 (95% CI, 13 502-17 331) in patients with other alcohol-attributable diagnoses. The proportional incidence of hospitalizations involving AWS was 2.3% overall, with variation by age, sex, and AUDIT-C scores (eg, 9%-11% in male patients aged 30-49 years and 23%-44% in patients with high-risk AUDIT-C scores of 7-12 points). In most cases, among adults younger than 60 years, proportional incidence of hospitalizations involving AWS matched or surpassed that of other common chronic conditions (chronic obstructive pulmonary disease, diabetes, heart failure, and hypertension).

Conclusions and Relevance

In this cohort study of a large primary care population served by an integrated health system, AWS hospitalizations were common, especially in male patients, younger age groups, and individuals with high-risk alcohol use. During hospitalizations, the burden of AWS was similar to or exceeded complications of other chronic diseases that receive greater medical attention.

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.

Prevalence of alcohol use disorders documented in electronic health records in primary care across intersections of race or ethnicity, sex, and socioeconomic status

BACKGROUND

Diagnosis of alcohol use disorder (AUD) in primary care is critical for increasing access to alcohol treatment. However, AUD is underdiagnosed and may be inequitably diagnosed due to societal structures that determine access to resources (e.g., structural racism that limits opportunities for some groups and influences interpersonal interactions in and beyond health care). This study described patterns of provider-documented AUD in primary care across intersections of race, ethnicity, sex, and community-level socioeconomic status (SES).

METHODS

This cross-sectional study used EHR data from a regional healthcare system with 35 primary care clinics that included adult patients who completed alcohol screenings between 3/1/2015 and 9/30/2020. The prevalence of provider-documented AUD in primary care based on International Classification of Diseases-9 (ICD-9) and ICD-10 diagnoses was compared across intersections of race, ethnicity, sex, and community-level SES.

RESULTS

Among 439,375 patients, 6.6% were Latine, 11.0% Asian, 5.4% Black, 1.3% Native Hawaiian/Pacific Islander (NH/PI), 1.5% American Indian/Alaska Native (AI/AN), and 74.2% White, and 58.3% women. The overall prevalence of provider-documented AUD was 1.0% and varied across intersecting identities. Among women, the prevalence was highest for AI/AN women with middle SES, 1.5% (95% CI 1.0-2.3), and lowest for Asian women with middle SES, 0.1% (95% CI 0.1-0.2). Among men, the prevalence was highest for AI/AN men with high and middle SES, 2.0% (95% CI 1.1-3.4) and 2.0% (95% CI 1.2-3.2), respectively, and lowest for Asian men with high SES, 0.5% (95% CI 0.3-0.7). Black and Latine patients tended to have a lower prevalence of AUD than White patients, across all intersections of sex and SES except for Black women with high SES. There were no consistent patterns of the prevalence of AUD diagnosis that emerged across SES.

CONCLUSION

The prevalence of provider-documented AUD in primary care was highest in AI/AN men and women and lowest in Asian men and women. Findings of lower prevalence of provider-documented AUD in Black and Hispanic than White patients across most intersections of sex and SES differed from prior studies. Findings may suggest that differences in access to resources, which vary in effects across these identity characteristics and lived experiences, influence the diagnosis of AUD in clinical care.

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.

Does This Patient Have Alcohol Use Disorder?: The Rational Clinical Examination Systematic Review

Importance

The accuracy of screening tests for alcohol use disorder (defined as a problematic pattern of alcohol use leading to clinically significant impairment or distress) requires reassessment to align with the latest definition in the Diagnostic and Statistical Manual of Mental Disorders (Fifth Edition) (DSM-5).

Objective

To assess the diagnostic accuracy of screening tools in identifying individuals with alcohol use disorder as defined in the DSM-5.

Data Sources and Study Selection

The databases of MEDLINE and Embase were searched (January 2013-February 2023) for original studies on the diagnostic accuracy of brief screening tools to identify alcohol use disorder according to the DSM-5 definition. Because diagnosis of alcohol use disorder does not include excessive alcohol use as a criterion, studies of screening tools that identify excessive or high-risk drinking among younger (aged 9-18 years), older (aged ≥65 years), and pregnant persons also were retained.

Data Extraction and Synthesis

Sensitivity, specificity, and likelihood ratios (LRs) were calculated. When appropriate, a meta-analysis was performed to calculate a summary LR.

Results

Of 4303 identified studies, 35 were retained (N = 79 633). There were 11 691 individuals with alcohol use disorder or a history of excessive drinking. Across all age categories, a score of 8 or greater on the Alcohol Use Disorders Identification Test (AUDIT) increased the likelihood of alcohol use disorder (LR, 6.5 [95% CI, 3.9-11]). A positive screening result using AUDIT identified alcohol use disorder better among females (LR, 6.9 [95% CI, 3.9-12]) than among males (LR, 3.8 [95% CI, 2.6-5.5]) (P = .003). An AUDIT score of less than 8 reduced the likelihood of alcohol use disorder similarly for both males and females (LR, 0.33 [95% CI, 0.20-0.52]). The abbreviated AUDIT-Consumption (AUDIT-C) has sex-specific cutoff scores of 4 or greater for males and 3 or greater for females, but was less useful for identifying alcohol use disorder (males: LR, 1.8 [95% CI, 1.5-2.2]; females: LR, 2.0 [95% CI, 1.8-2.3]). The AUDIT-C appeared useful for identifying measures of excessive alcohol use in younger people (aged 9-18 years) and in those older than 60 years of age. For those younger than 18 years of age, the National Institute on Alcohol Abuse and Alcoholism age-specific drinking thresholds were helpful for assessing the likelihood of alcohol use disorder at the lowest risk threshold (LR, 0.15 [95% CI, 0.11-0.21]), at the moderate risk threshold (LR, 3.4 [95% CI, 2.8-4.1]), and at the highest risk threshold (LR, 15 [95% CI, 12-19]). Among persons who were pregnant and screened within 48 hours after delivery, an AUDIT score of 4 or greater identified those more likely to have alcohol use disorder (LR, 6.4 [95% CI, 5.1-8.0]), whereas scores of less than 2 for the Tolerance, Worried, Eye-Opener, Amnesia and Cut-Down screening tool and the Tolerance, Annoyed, Cut-Down and Eye-Opener screening tool identified alcohol use disorder similarly (LR, 0.05 [95% CI, 0.01-0.20]).

Conclusions and Relevance

The AUDIT screening tool is useful to identify alcohol use disorder in adults and in individuals within 48 hours postpartum. The National Institute on Alcohol Abuse and Alcoholism youth screening tool is helpful to identify children and adolescents with alcohol use disorder. The AUDIT-C appears useful for identifying various measures of excessive alcohol use in young people and in older adults.

Tools to implement measurement-based care (MBC) in the treatment of opioid use disorder (OUD): toward a consensus

BACKGROUND

The prevalence and associated overdose death rates from opioid use disorder (OUD) have dramatically increased in the last decade. Despite more available treatments than 20 years ago, treatment access and high discontinuation rates are challenges, as are personalized medication dosing and making timely treatment changes when treatments fail. In other fields such as depression, brief measures to address these tasks combined with an action plan-so-called measurement-based care (MBC)-have been associated with better outcomes. This workgroup aimed to determine whether brief measures can be identified for using MBC for optimizing dosing or informing treatment decisions in OUD.

METHODS

The National Institute on Drug Abuse Center for the Clinical Trials Network (NIDA CCTN) in 2022 convened a small workgroup to develop consensus about clinically usable measures to improve the quality of treatment delivery with MBC methods for OUD. Two clinical tasks were addressed: (1) to identify the optimal dose of medications for OUD for each patient and (2) to estimate the effectiveness of a treatment for a particular patient once implemented, in a more granular fashion than the binary categories of early or sustained remission or no remission found in The Diagnostic and Statistical Manual of Mental Disorders, fifth edition (DSM-5).

DISCUSSION

Five parameters were recommended to personalize medication dose adjustment: withdrawal symptoms, opioid use, magnitude (severity and duration) of the subjective effects when opioids are used, craving, and side effects. A brief rating of each OUD-specific parameter to adjust dosing and a global assessment or verbal question for side-effects was viewed as sufficient. Whether these ratings produce better outcomes (e.g., treatment engagement and retention) in practice deserves study. There was consensus that core signs and symptoms of OUD based on some of the 5 DSM-5 domains (e.g., craving, withdrawal) should be the basis for assessing treatment outcome. No existing brief measure was found to meet all the consensus recommendations. Next steps would be to select, adapt or develop de novo items/brief scales to inform clinical decision-making about dose and treatment effectiveness. Psychometric testing, assessment of acceptability and whether the use of such scales produces better symptom control, quality of life (QoL), daily function or better prognosis as compared to treatment as usual deserves investigation.

Establishing language and ethnic equivalence for health-related quality of life item banks and testing their efficiency via computerised adaptive testing simulations

PURPOSE

We aimed to (1) establish linguistic and ethnic equivalence (i.e. lack of bias) for the items in the English and Chinese versions of the Singapore Health and Well Being (SHAWS) Physical Functioning (PF), Positive Mindset (PM) and Social Relationship (SR) item banks (IBs); and (2) evaluate the preliminary efficiency of these IBs using Computer Adaptive Testing (CAT) simulations.

METHODS

In this cross-sectional study, 671, 670, and 672 subjects answered 55, 48 and 30 items of the PF, PM, and SR IBs, respectively. Rasch analysis was conducted to assess each IB's psychometric properties, particularly the presence of differential item functioning (DIF) for language and ethnicity. A set of performance criteria related to removing items that displayed notable DIF were employed. CAT simulations determined the mean number of items for high, moderate, and moderate-low measurement precisions (stopping rule: SEM 0.300, 0.387. 0.521, respectively).

RESULTS

Half of subjects were >50 years old (40.9% PF, 42.1% PM, 41.4% SR), Chinese (50.7% PF, 51.0% PM, 50.6% SR) and female (50.0% PF. 49.4% PM, 52.8% SR) respectively. Rasch analysis revealed 4 items with DIF for the PF IB, 9 items with DIF for the PM IB and 2 items with DIF for the SR IB. In CAT simulations, the mean number of items administered was 8.5, 21.6 and 14.5 for the PF, PM and SR IBs, respectively (SEM 0.300), 5.1, 13.0, 8.0 for PF, PM and SR IBs, respectively (SEM 0.387) and 3.1, 5.3 and 4.1 for PF, PM and SR IBs, respectively (SEM 0.521).

CONCLUSION

The PF, PM and SR IBs to measure health-related quality of life revealed minimal DIF for language and ethnicity after remedial efforts. CAT simulations demonstrated that these IBs were efficient, especially when the stopping rule was set at moderate precision, and support the implementation of the SHAWS IBs into routine clinical care.

Evidence-Based Assessment of Substance Use Disorder

The current review describes updated information on the evidence-based assessment of substance use disorder. We offer an overview of the state of the science for substance-related assessment targets, instruments (screening, diagnosis, outcome and treatment monitoring, and psychosocial functioning and wellbeing) and processes (relational and technical) as well as recommendations for each of these three components. We encourage assessors to reflect on their own biases, beliefs, and values, including how those relate to people that use substances, and to view the individual as a whole person. It is important to consider a person's profile of symptoms and functioning inclusive of strengths, comorbidities, and social and cultural determinants. Collaborating with the patient to select the assessment target that best fits their goals and integration of assessment information in a holistic manner is critical. We conclude by providing recommendations for assessment targets, instruments, and processes as well as recommendations for comprehensive substance use disorder assessment, and describe future directions for research.

Promoting alcohol treatment engagement post-hospitalization with brief intervention, medications and CBT4CBT: protocol for a randomized clinical trial in a diverse patient population

BACKGROUND

Alcohol use disorder (AUD) commonly causes hospitalization, particularly for individuals disproportionately impacted by structural racism and other forms of marginalization. The optimal approach for engaging hospitalized patients with AUD in treatment post-hospital discharge is unknown. We describe the rationale, aims, and protocol for Project ENHANCE (ENhancing Hospital-initiated Alcohol TreatmeNt to InCrease Engagement), a clinical trial testing increasingly intensive approaches using a hybrid type 1 effectiveness-implementation approach.

METHODS

We are randomizing English and/or Spanish-speaking individuals with untreated AUD (n = 450) from a large, urban, academic hospital in New Haven, CT to: (1) Brief Negotiation Interview (with referral and telephone booster) alone (BNI), (2) BNI plus facilitated initiation of medications for alcohol use disorder (BNI + MAUD), or (3) BNI + MAUD + initiation of computer-based training for cognitive behavioral therapy (CBT4CBT, BNI + MAUD + CBT4CBT). Interventions are delivered by Health Promotion Advocates. The primary outcome is AUD treatment engagement 34 days post-hospital discharge. Secondary outcomes include AUD treatment engagement 90 days post-discharge and changes in self-reported alcohol use and phosphatidylethanol. Exploratory outcomes include health care utilization. We will explore whether the effectiveness of the interventions on AUD treatment engagement and alcohol use outcomes differ across and within racialized and ethnic groups, consistent with disproportionate impacts of AUD. Lastly, we will conduct an implementation-focused process evaluation, including individual-level collection and statistical comparisons between the three conditions of costs to providers and to patients, cost-effectiveness indices (effectiveness/cost ratios), and cost-benefit indices (benefit/cost ratios, net benefit [benefits minus costs). Graphs of individual- and group-level effectiveness x cost, and benefits x costs, will portray relationships between costs and effectiveness and between costs and benefits for the three conditions, in a manner that community representatives also should be able to understand and use.

CONCLUSIONS

Project ENHANCE is expected to generate novel findings to inform future hospital-based efforts to promote AUD treatment engagement among diverse patient populations, including those most impacted by AUD.

CLINICAL TRIAL REGISTRATION

Clinicaltrials.gov identifier: NCT05338151.

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.

Psychometric Performance of a Substance Use Symptom Checklist to Help Clinicians Assess Substance Use Disorder in Primary Care

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 23 304 screens were included (mean [SD] age, 38.2 [5.6] years; 12 554 [53.9%] male patients; 17 439 [78.8%] White patients; 20 393 [87.5%] non-Hispanic patients). Overall, 16 140 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.

Association between clinical measures of unhealthy alcohol use and subsequent year hospital admissions in a primary care population

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.

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.

Hazardous drinking and alcohol use disorders

Alcohol is one of the most widely consumed psychoactive drugs globally. Hazardous drinking, defined by quantity and frequency of consumption, is associated with acute and chronic morbidity. Alcohol use disorders (AUDs) are psychiatric syndromes characterized by impaired control over drinking and other symptoms. Contemporary aetiological perspectives on AUDs apply a biopsychosocial framework that emphasizes the interplay of genetics, neurobiology, psychology, and an individual's social and societal context. There is strong evidence that AUDs are genetically influenced, but with a complex polygenic architecture. Likewise, there is robust evidence for environmental influences, such as adverse childhood exposures and maladaptive developmental trajectories. Well-established biological and psychological determinants of AUDs include neuroadaptive changes following persistent use, differences in brain structure and function, and motivational determinants including overvaluation of alcohol reinforcement, acute effects of environmental triggers and stress, elevations in multiple facets of impulsivity, and lack of alternative reinforcers. Social factors include bidirectional roles of social networks and sociocultural influences, such as public health control strategies and social determinants of health. An array of evidence-based approaches for reducing alcohol harms are available, including screening, pharmacotherapies, psychological interventions and policy strategies, but are substantially underused. Priorities for the field include translating advances in basic biobehavioural research into novel clinical applications and, in turn, promoting widespread implementation of evidence-based clinical approaches in practice and health-care systems.

Alcohol Use

Unhealthy alcohol use-the consumption of alcohol at a level that has caused or has the potential to cause adverse physical, psychological, or social consequences-is common, underrecognized, and undertreated. For example, data from the 2020 National Survey on Drug Use and Health indicate that 7.0% of adults reported heavy alcohol use in the previous month, and only 4.2% of adults with alcohol use disorder received treatment. Primary care is an important setting for optimizing screening and treatment of unhealthy alcohol use to promote individual and public health.

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.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12913-022-08408-1.

Alcoholism and American healthcare: The case for a patient safety approach

Alcoholism, more professionally termed alcohol use disorder (AUD), is a widespread and costly behavioral health condition. The aims of this paper are draw attention to systemic gaps in care for patients with AUD and advocate for patient safety leaders to partner with both the mainstream medical and substance abuse treatment communities to reduce harm in this patient population. The authors performed a narrative review of the literature on the current state of AUD treatment and patient safety, finding extensive evidence that patients with AUD usually go undiagnosed, unreferred and untreated. When they do receive AUD treatment, little evidence was found to indicate that a patient safety approach is incorporated into their care. Behavioral medicine is virgin territory for the patient safety movement. Medical care and behavioral medicine in the United States currently constitute two separate and unequal systems generally lacking in pathways of communication or care coordination for AUD patients. Significant barriers include institutional culture, individual and systemic bias against those with AUD, and health care infrastructure, especially the separation of medical and behavioral treatment. It is the authors’ conclusion that care of patients with AUD is unsafe. We advocate for the patient safety approach common in American hospitals to be extended to AUD treatment. Experienced patient safety leaders are in the strongest position to initiate collaboration between the mainstream medical and substance abuse treatment communities to reduce harm for this patient population.

Delivering Remote Measurement-Based Care in Community Addiction Treatment: Engagement and Usability Over a 6-Month Clinical Pilot

Objective

Measurement-based care (MBC) is an evidence-based practice in which patients routinely complete standardized measures throughout treatment to help monitor clinical progress and inform clinical decision-making. Despite its potential benefits, MBC is rarely used in community-based substance use disorder (SUD) treatment. In this pilot study, we evaluated the feasibility of incorporating a digital and remotely delivered MBC system into SUD treatment within a community setting by characterizing patients' and clinicians' engagement with and usability ratings toward the MBC system that was piloted.

Methods

A pilot study was conducted with 30 patients receiving SUD treatment and eight clinicians providing SUD treatment in a large, publicly funded addiction and mental health treatment clinic. Services as usual within the clinic included individual psychotherapy, case management, group therapy, peer support, and medication management for mental health and SUD, including buprenorphine. Patients who enrolled in the pilot continued to receive services as usual and were automatically sent links to complete a 22-item questionnaire, called the weekly check-in, via text message or email weekly for 24 weeks. Results of the weekly check-in were summarized on a clinician-facing web-based dashboard. Engagement was characterized by calculating the mean number of weekly check-ins completed by patients and the mean number times clinicians logged into the MBC system. Ratings of the MBC system's usability and clinical utility were provided by patients and clinicians.

Results

Patient participants (53.3% male, 56.7% white, 90% Medicaid enrolled) completed a mean of 20.60 weekly check-ins (i.e., 85.8% of the 24 expected per patient). All but one participating clinician with a patient enrolled in the study logged into the clinician-facing dashboard at least once, with an average of 12.20 logins per clinician. Patient and clinician ratings of usability and clinical utility were favorable: most patients agreed with statements that the weekly check-in was easy to navigate and aided self-reflection. All clinicians who completed usability questionnaires agreed with statements indicating that the dashboard was easy to navigate and that it provided meaningful information for SUD treatment.

Conclusions

A digital and remotely delivered MBC system can yield high rates of patient and clinician engagement and high ratings of usability and clinical utility when added into SUD treatment as usual. The success of this clinical pilot may be attributable, in part, to the user-centered design processes that were used to develop and refine the MBC system that was piloted. Future efforts may focus on strategies to test whether MBC can be sustainably implemented and offers clinical benefits to patients in community SUD treatment settings.

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-5^th 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.