Study protocol: a cluster-randomized trial implementing Sustained Patient-centered Alcohol-related Care (SPARC trial)

Test-retest reliability of DSM-5 substance use symptom checklists used in primary care and mental health care settings

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.

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.

High test-retest reliability of the Alcohol Use Disorders Identification Test-Consumption (AUDIT-C) questionnaire completed by primary care patients in routine care

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.

Perspectives of clinical stakeholders and patients from four VA liver clinics to tailor practice facilitation for implementing evidence-based alcohol-related care

BACKGROUND

Unhealthy alcohol use (UAU) is particularly dangerous for people with chronic liver disease. Liver clinics may be an important setting in which to provide effective alcohol-related care by integrating evidence-based strategies, such as brief intervention and medications for alcohol use disorder. We conducted qualitative interviews with clinical stakeholders and patients at liver clinics in four Veterans Health Administration (VA) medical centers to understand barriers and facilitators of integrating alcohol-related care and to support tailoring of a practice facilitation implementation intervention.

METHODS

Data collection and analysis were guided by the Consolidated Framework for Implementation Research (CFIR). Interviews were transcribed and qualitatively analyzed using a Rapid Assessment Process (RAP) guided by the CFIR.

RESULTS

We interviewed 46 clinical stakeholders and 41 patient participants and analyzed findings based on the CFIR. Clinical stakeholders described barriers and facilitators that ranged from operations/clinic resource-based (e.g., time and capacity, desire for additional provider types, referral processes) to individual perspective and preference-based (e.g., supportiveness of leadership, individual experiences/beliefs). Patient participants shared barriers and facilitators that ranged from relationship-based (e.g., trusting the provider and feeling judged) to resource and education-based (e.g., connection to a range of treatment options, education about impact of alcohol). Many barriers and facilitators to integrating alcohol-related care in liver clinics were similar to those identified in other clinical settings (e.g., time, resources, role clarity, stigmatizing beliefs). However, some barriers (e.g., fellow-led care and lack of integration of liver clinics with addictions specialists) and facilitators (e.g., presence of quality improvement staff in clinics and integrated pharmacists and behavioral health specialists) were more unique to liver clinics.

CONCLUSIONS

These findings support the possibility of integrating alcohol-related care into liver clinics but highlight the importance of tailoring efforts to account for variation in provider beliefs and experiences and clinic resources. The barriers and facilitators identified in these interviews were used to tailor a practice facilitation implementation intervention in each clinic setting.

Association between cannabis use disorder symptom severity and probability of clinically-documented diagnosis and treatment in a primary care sample

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.

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

BACKGROUND

Alcohol use disorders (AUD) are prevalent and often go untreated. Patients are commonly screened for AUD in primary care, but existing treatment programs are failing to meet demand. Digital therapeutics include novel mobile app-based treatment approaches which may be cost-effective treatment options to help fill treatment gaps. The goal of this study was to identify implementation needs and workflow design considerations for integrating digital therapeutics for AUD into primary care.

METHODS

We conducted qualitative interviews with clinicians, care delivery leaders, and implementation staff (n = 16) in an integrated healthcare delivery system in the United States. All participants had experience implementing digital therapeutics for depression or substance use disorders in primary care. Interviews were designed to gain insights into adaptations needed to optimize existing clinical processes, workflows, and implementation strategies for use with alcohol-focused digital therapeutics. Interviews were recorded and transcribed and then analyzed using a rapid analysis process and affinity diagramming.

RESULTS

Qualitative themes were well represented across health system staff roles. Participants were enthusiastic about digital therapeutics for AUD, anticipated high patient demand for such a resource, and made suggestions for successful implementation. Key insights regarding the implementation of digital therapeutics for AUD and unhealthy alcohol use from our data include: (1) implementation strategy selection must be driven by digital therapeutic design and target population characteristics, (2) implementation strategies should seek to minimize burden on clinicians given the large numbers of patients with AUD who are likely to be interested in and eligible for digital therapeutics, and (3) digital therapeutics should be offered alongside many other treatment options to accommodate individual patients' AUD severity and treatment goals. Participants also expressed confidence that previous implementation strategies used with other digital therapeutics such as clinician training, electronic health record supports, health coaching, and practice facilitation would be effective for the implementation of digital therapeutics for AUD.

CONCLUSIONS

The implementation of digital therapeutics for AUD would benefit from careful consideration of the target population. Optimal integration requires tailoring workflows to meet anticipated patient volume and designing workflow and implementation strategies to meet the unique needs of patients with varying AUD severity.

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.

Alcohol treatment discussions and clinical outcomes among patients with alcohol-related cirrhosis

BACKGROUND

Alcohol cessation is the cornerstone of treatment for alcohol-related cirrhosis. This study evaluated associations between medical conversations about alcohol use disorder (AUD) treatment, AUD treatment engagement, and mortality.

METHODS

This retrospective cohort study included all patients with ICD-10 diagnosis codes for cirrhosis and AUD who were engaged in hepatology care in a single healthcare system in 2015. Baseline demographic, medical, liver disease, and AUD treatment data were assessed. AUD treatment discussions and initiation, alcohol cessation, and subsequent 5-year mortality were collected. Multivariable models were used to assess the factors associated with subsequent AUD treatment and 5-year mortality.

RESULTS

Among 436 patients with cirrhosis due to alcohol, 65 patients (15%) received AUD treatment at baseline, including 48 (11%) receiving behavioral therapy alone, 11 (2%) receiving pharmacotherapy alone, and 6 (1%) receiving both. Over the first year after a baseline hepatology visit, 37 patients engaged in AUD treatment, 51 were retained in treatment, and 14 stopped treatment. Thirty percent of patients had hepatology-documented AUD treatment recommendations and 26% had primary care-documented AUD treatment recommendations. Most hepatology (86%) and primary care (88%) recommendations discussed behavioral therapy alone. Among patients with ongoing alcohol use at baseline, AUD treatment one year later was significantly, independently associated with AUD treatment discussions with hepatology (adjusted odds ratio (aOR): 3.23, 95% confidence interval (CI): 1.58, 6.89) or primary care (aOR: 2.95; 95% CI: 1.44, 6.15) and negatively associated with having Medicaid insurance (aOR: 0.43, 95% CI: 0.18, 0.93). When treatment was discussed in both settings, high rates of treatment ensued (aOR: 10.72, 95% CI: 3.89, 33.52). Over a 5-year follow-up period, 152 (35%) patients died. Ongoing alcohol use, age, hepatic decompensation, and hepatocellular carcinoma were significantly associated with mortality in the final survival model.

CONCLUSION

AUD treatment discussions were documented in less than half of hepatology and primary care encounters in patients with alcohol-related cirrhosis, though such discussions were significantly associated with receipt of AUD treatment.

Study protocol for a factorial-randomized controlled trial evaluating the implementation, costs, effectiveness, and sustainment of digital therapeutics for substance use disorder in primary care (DIGITS Trial)

BACKGROUND

Experts recommend that treatment for substance use disorder (SUD) be integrated into primary care. The Digital Therapeutics for Opioids and Other SUD (DIGITS) Trial tests strategies for implementing reSET® and reSET-O®, which are prescription digital therapeutics for SUD and opioid use disorder, respectively, that include the community reinforcement approach, contingency management, and fluency training to reinforce concept mastery. This purpose of this trial is to test whether two implementation strategies improve implementation success (Aim 1) and achieve better population-level cost effectiveness (Aim 2) over a standard implementation approach.

METHODS/DESIGN

The DIGITS Trial is a hybrid type III cluster-randomized trial. It examines outcomes of implementation strategies, rather than studying clinical outcomes of a digital therapeutic. It includes 22 primary care clinics from a healthcare system in Washington State and patients with unhealthy substance use who visit clinics during an active implementation period (up to one year). Primary care clinics implemented reSET and reSET-O using a multifaceted implementation strategy previously used by clinical leaders to roll-out smartphone apps ("standard implementation" including discrete strategies such as clinician training, electronic health record tools). Clinics were randomized as 21 sites in a 2x2 factorial design to receive up to two added implementation strategies: (1) practice facilitation, and/or (2) health coaching. Outcome data are derived from electronic health records and logs of digital therapeutic usage. Aim 1's primary outcomes include reach of the digital therapeutics to patients and fidelity of patients' use of the digital therapeutics to clinical recommendations. Substance use and engagement in SUD care are additional outcomes. In Aim 2, population-level cost effectiveness analysis will inform the economic benefit of the implementation strategies compared to standard implementation. Implementation is monitored using formative evaluation, and sustainment will be studied for up to one year using qualitative and quantitative research methods.

DISCUSSION

The DIGITS Trial uses an experimental design to test whether implementation strategies increase and improve the delivery of digital therapeutics for SUDs when embedded in a large healthcare system. It will provide data on the potential benefits and cost-effectiveness of alternative implementation strategies.

CLINICALTRIALS

gov Identifier: NCT05160233 (Submitted 12/3/2021). https://clinicaltrials.gov/ct2/show/NCT05160233.

What Do Adolescents and Their Parents Need From Mental Health Integration in Primary Care? A Qualitative Exploration of Design Insights

INTRODUCTION

The design of integrated adolescent mental health care should address needs and preferences of patients and parents/guardians.

METHOD

We conducted interviews and focus groups with adolescents aged 13-17 years who received care at Kaiser Permanente Washington in 2020 and interviews with parents of such adolescents. We sought to (1) understand the challenges of primary care-based mental health and substance use screening and care for adolescents and (2) identify program design solutions. Sessions were audio-recorded, transcribed, and coded. Thematic analysis was applied to identify key challenges and design solutions.

RESULTS

Emerging themes from interviews (n = 41) and focus groups (n = 10) were summarized in five overarching design principles: Engagement, Privacy, Communication, Choice, and Ease. Each design principle was expanded for operationalization within a new health system program.

DISCUSSION

Health systems serving adolescents in primary care may consider application of these design principles to the development of mental health integration programs.

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.

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

BACKGROUND

Alcohol use disorder (AUD) is highly prevalent but underrecognized and undertreated in primary care settings. Alcohol Symptom Checklists can engage patients and providers in discussions of AUD-related care. However, the performance of Alcohol Symptom Checklists when they are used in routine care and documented in electronic health records (EHRs) remains unevaluated.

OBJECTIVE

To evaluate the psychometric performance of an Alcohol Symptom Checklist in routine primary care.

DESIGN

Cross-sectional study using item response theory (IRT) and differential item functioning analyses of measurement consistency across age, sex, race, and ethnicity.

PATIENTS

Patients seen in primary care in the Kaiser Permanente Washington Healthcare System who reported high-risk drinking on the Alcohol Use Disorder Identification Test Consumption screening measure (AUDIT-C ≥ 7) and subsequently completed an Alcohol Symptom Checklist between October 2015 and February 2020.

MAIN MEASURE

Alcohol Symptom Checklists with 11 items assessing AUD criteria defined in the Diagnostic and Statistical Manual for Mental Disorders, 5th edition (DSM-5), completed by patients during routine medical care and documented in EHRs.

KEY RESULTS

Among 11,464 patients who screened positive for high-risk drinking and completed an Alcohol Symptom Checklist (mean age 43.6 years, 30.5% female), 54.1% reported ≥ 2 DSM-5 AUD criteria (threshold for AUD diagnosis). IRT analyses demonstrated that checklist items measured a unidimensional continuum of AUD severity. Differential item functioning was observed for some demographic subgroups but had minimal impact on accurate measurement of AUD severity, with differences between demographic subgroups attributable to differential item functioning never exceeding 0.42 points of the total symptom count (of a possible range of 0-11).

CONCLUSIONS

Alcohol Symptom Checklists used in routine care discriminated AUD severity consistently with current definitions of AUD and performed equitably across age, sex, race, and ethnicity. Integrating symptom checklists into routine care may help inform clinical decision-making around diagnosing and managing AUD.

Using practice facilitation to improve alcohol-related care in primary care: a mixed-methods pilot study protocol

Background

Alcohol use is a significant risk factor for disability and death in U.S. adults, and approximately one out of every six Veterans seen in primary care (PC) report unhealthy alcohol use. Unhealthy alcohol use is associated with increased risk for poor medical outcomes, substantial societal costs, and death, including suicide. Based on substantial evidence from randomized controlled trials and the U.S. Preventive Services Task Force, VA/DoD clinical guidelines stipulate that all Veterans screening positive for unhealthy alcohol use should receive evidence-based alcohol care in PC, including brief counseling interventions (BI) and additional treatment (e.g., pharmacotherapy) for those with alcohol use disorders (AUD). The VA pioneered implementing alcohol screening and BI in PC, yet substantial implementation gaps remain. To improve alcohol-related care, this study will conduct a pilot study to assess whether a multi-faceted evidence-based implementation strategy—practice facilitation—has the potential to improve PC-based alcohol-related care at a single VA clinic.

Methods

We will first recruit and conduct qualitative interviews with Veterans with unhealthy alcohol use (n = 20–25) and PC stakeholders (N = 10–15) to understand barriers and facilitators to high-quality alcohol care and use results to refine and hone the multifaceted practice facilitation intervention. Qualitative interviews, analysis, and refinement of the intervention will be guided by the Consolidated Framework for Implementation Research (CFIR). Focus groups with a small sample of PC providers and staff (n = 5–7) will be used to further refine the practice facilitation intervention and assess its acceptability and feasibility. The refined practice facilitation intervention will then be offered in the PC clinic to assess implementation (e.g., reach) and effectiveness (reduced drinking) outcomes based on the RE-AIM framework.

Discussion

This research directly addresses one of the largest public health crises of our time, as alcohol kills more people than opioids and is associated with increased risk of suicide. If successful, this pilot may generate an intervention with far-reaching effects on adverse outcomes experienced by Veterans with unhealthy alcohol use, including increased access to care and suicide prevention.

Trial registration Clinicaltrials.gov identifier: NCT04565899; Date of registration: 9/25/2020

Supplementary Information

The online version contains supplementary material available at 10.1186/s13722-022-00300-x.

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.

Approaches for implementing digital interventions for alcohol use disorders in primary care: A qualitative, user-centered design study

Background

Digital interventions, such as smartphone apps, can be effective in treating alcohol use disorders (AUD). However, efforts to integrate digital interventions into primary care have been challenging. To inform successful implementation, we sought to understand how patients and clinicians preferred to use apps in routine primary care.

Methods

This study combined user-centered design and qualitative research methods, interviewing 18 primary care patients with AUD and nine primary care clinicians on topics such as prior experiences with digital tools, and design preferences regarding approaches for offering apps for AUD in primary care. Interviews were recorded and transcribed for template analysis whereby a priori codes were based on interview topics and refined through iterative coding. New codes and cross-cutting themes emerged from the data.

Results

Patient participants with AUD indicated they would be more likely to engage in treatment if primary care team members were involved in their use of apps. They also preferred to see clinicians “invested” and recommended that clinicians ask about app use and progress during follow-up appointments or check-ins. Clinician participants valued the opportunity to offer apps to their patients but noted that workflows would need to be tailored to individual patient needs. Time pressures, implementation complexity, and lack of appropriate staffing were cited as barriers. Clinicians proposed concrete solutions (e.g., education, tools, and staffing models) that could improve their ability to use apps within the constraints of primary care and suggested that some patients could potentially use apps without clinician support.

Conclusions

A user-centered approach to engaging patients in digital alcohol interventions in primary care may require personalized support for both initiation and follow-up. Meeting patients’ needs likely require increased staffing and efficient workflows in primary care. Health systems should consider offering multiple pathways for enrolling patients in apps to accommodate individual preferences and contextual barriers.

Plain Language Summary

Healthcare systems have begun using app-based treatments to help patients manage their health conditions, including alcohol use disorders. Some apps have been tested in research studies and appear to be effective. However, it is difficult for healthcare teams to offer apps to patients. Clinicians must engage in new activities that they have not done before, such as “teaching” patients to use apps and checking in on their use of the apps. Identifying how to use apps in routine healthcare is critical to their successful implementation. This study interviewed 27 people, including healthcare providers and patients in primary care, to uncover the most optimal ways to offer apps to patients with alcohol use disorders. The interviews combined the use of qualitative research methods and user-centered design. Results suggest that to use to address alcohol use disorders, primary care teams should be prepared to offer personalized support to patients. Both patient and clinician interviewees said that the steps required to use apps must be intuitive and simple. Patients could gain more benefits if clinicians introduced the apps and guided patients to use them, as opposed to making apps available for patients to download and use on their own. However, the exact approach to offering apps would depend on a given patient’s preferences and the extent that staffing was available in the clinic to support patients. Health systems should be prepared to offer and support patients in their use of apps, which should accommodate patient preferences and the constraints of the clinic.

The Organizational Financial Context of Publicly-Funded Mental Health Clinics: Development and Preliminary Psychometric Evaluation of the Agency Financial Status Scales

Funding is a major barrier to implementation of evidence-based practices (EBPs) in publicly-funded community mental health clinics (CMHCs). Understanding how best to deploy implementation strategies that address this barrier requires greater clarity on the financial context within agencies. We developed the Agency Financial Status Scales (AFSS) to assess employee perceptions of the level of three hypothesized and theoretical funding related constructs in organizations: (a) perceptions of financial health, (b) financial attitudes toward EBPs, and (c) strategic financial climate. This investigation serves as a preliminary evaluation of this measure. Participants were 239 therapists and 40 supervisors from 25 publicly-funded CMHCs providing outpatient mental health services for young people. Confirmatory factor analysis was used to investigate the latent trait structure of the items. Internal consistency, interrater agreement, concordance between therapists and supervisors, and convergent validity were also examined. A two-factor model measuring perceptions of financial health and strategic financial climate best fit the data. For both of these scales, alpha reliability was acceptable and agreement statistics provided moderate support for aggregation at the organizational level. Analyses supported the convergent validity of the scales. The development and preliminary evaluation of the AFSS is an important first step in understanding the financial context of publicly-funded CMHCs. Though findings from this investigation are promising, additional development and testing are needed to develop a more thorough understanding of the constructs and to improve the validity and reliability of this measure.

Self-reported Access to Firearms Among Patients Receiving Care for Mental Health and Substance Use

Question

Did patients respond to a standard question about firearm access on a mental health questionnaire, and, if so, how did they respond?

Findings

In this cross-sectional study of 128 802 patients receiving care for mental health and substance use, 83% of primary care patients answered a standard question about firearm access and 21% reported access. In mental health clinics, 92% of patients answered the question and 15% reported access.

Meaning

In this study, most patients reported firearm access on standard questionnaires; this screening practice may improve efforts to identify and engage patients at risk of suicide in discussions about securing firearms.

Importance

Firearms are the most common method of suicide, one of the “diseases of despair” driving increased mortality in the US over the past decade. However, routine standardized questions about firearm access are uncommon, particularly among adult populations, who are more often asked at the discretion of health care clinicians. Because standard questions are rare, patterns of patient-reported access are unknown.

Objective

To evaluate whether and how patients self-report firearm access information on a routine mental health monitoring questionnaire and additionally to examine sociodemographic and clinical associations of reported access.

Design, Setting, and Participants

Cross-sectional study of patients receiving care for mental health and/or substance use in primary care or outpatient mental health specialty clinics of Kaiser Permanente Washington, an integrated health insurance provider and care delivery system.

Main Outcomes and Measures

Electronic health records were used to identify patients who completed a standardized self-reported mental health monitoring questionnaire after a single question about firearm access was added from January 1, 2016, through December 31, 2019. Primary analyses evaluated response (answered vs not answered) and reported access (yes vs no) among those who answered, separately for patients seen in primary care and mental health. These analyses also evaluated associations between patient characteristics and reported firearm access. Data analysis took place from February 2020 through May 2021.

Results

Among patients (n = 128 802) who completed a mental health monitoring questionnaire during the study period, 74.4% (n = 95 875) saw a primary care clinician and 39.3% (n = 50 631) saw a mental health specialty clinician. The primary care and mental health samples were predominantly female (63.1% and 64.9%, respectively) and White (75.7% and 77.0%), with a mean age of 42.8 and 51.1 years. In primary care, 83.4% of patients answered the question about firearm access, and 20.9% of patients who responded to the firearm question reported having access. In mental health, 91.8% of patients answered the question, and 15.3% reported having access.

Conclusions and Relevance

In this cross-sectional study of adult patients receiving care for mental health and substance use, most patients answered a question about firearm access on a standardized mental health questionnaire. These findings provide a critical foundation to help advance understanding of the utility of standardized firearm access assessment and to inform development of practice guidelines and recommendations. Responses to standard firearm access questions used in combination with dialogue and decision-making resources about firearm access and storage may improve suicide prevention practices and outcomes.

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

Background

Digital interventions, such as websites and smartphone apps, can be effective in treating drug use disorders (DUDs). However, their implementation in primary care is hindered, in part, by a lack of knowledge on how patients might like these treatments delivered to them.

Objective

This study aims to increase the understanding of how patients with DUDs prefer to receive app-based treatments to inform the implementation of these treatments in primary care.

Methods

The methods of user-centered design were combined with qualitative research methods to inform the design of workflows for offering app-based treatments in primary care. Adult patients (n=14) with past-year cannabis, stimulant, or opioid use disorder from 5 primary care clinics of Kaiser Permanente Washington in the Seattle area participated in this study. Semistructured interviews were recorded, transcribed, and analyzed using qualitative template analysis. The coding scheme included deductive codes based on interview topics, which primarily focused on workflow design. Inductive codes emerged from the data.

Results

Participants wanted to learn about apps during visits where drug use was discussed and felt that app-related conversations should be incorporated into the existing care whenever possible, as opposed to creating new health care visits to facilitate the use of the app. Nearly all participants preferred receiving clinician support for using apps over using them without support. They desired a trusting, supportive relationship with a clinician who could guide them as they used the app. Participants wanted follow-up support via phone calls or secure messaging because these modes of communication were perceived as a convenient and low burden (eg, no copays or appointment travel).

Conclusions

A user-centered implementation of treatment apps for DUDs in primary care will require health systems to design workflows that account for patients’ needs for structure, support in and outside of visits, and desire for convenience.

Association Between Patterns of Alcohol Use and Short-Term Risk of Suicide Attempt Among Patients With and Without Reported Suicidal Ideation

OBJECTIVE

To evaluate the association between patterns of alcohol use and short-term risk of suicide attempt among patients with and without reported suicidal ideation.

METHODS

Kaiser Permanente Washington electronic health record data were used to identify mental health visits (1/1/2010-6/30/2015) with documented assessments for unhealthy alcohol use (AUDIT-C) and suicidal ideation (PHQ-9 ninth question). Logistic regression fit using generalized estimating equations were used to conduct visit-level analyses, accounting for correlation between individuals' assessments. Separate models evaluated the association between (1) level of alcohol consumption and (2) frequency of heavy episodic drinking (HED), in combination with suicidal ideation (any vs none), with suicide attempt within 90 days following each visit. Primary models adjusted for age, gender, race/ethnicity and visit year.

RESULTS

Of 59,705 visits (43,706 unique patients), 372 (0.62%) were followed by a suicide attempt within 90 days. The risk of suicide attempt was significantly higher for patients reporting suicidal ideation across all levels of alcohol consumption compared to patients reporting low-level alcohol use and no suicidal ideation, particularly high-level use (OR 9.77, 95% CI, 6.23-15.34). Similarly, risk of suicide attempt was higher for patients reporting suicidal ideation across all levels of HED relative to those reporting no HED or suicidal ideation, particularly HED monthly or more (OR 6.80, 95% CI 4.77-9.72). Among patients reporting no suicidal ideation, no associations were observed.

CONCLUSIONS

Findings underscore the potential value of offering alcohol-related care to patient reporting suicidal ideation. Additional strategies are needed to identify suicide risk among those reporting no suicidal ideation.

"I Felt I Was Reaching a Point with My Health": Understanding Reasons for Engagement and Acceptability of Treatment Services for Unhealthy Alcohol Use in Primary Care

INTRODUCTION/OBJECTIVES

Despite increasing need, there are large gaps in provision of care for unhealthy alcohol use. Primary care practices have become increasingly important in providing services for unhealthy alcohol use, yet little is known about the reasons patients engage in these services and their views on acceptability of such programs. The purpose of this study was to examine primary care patients' reasons for engagement, experiences with, and acceptability of a primary care practice-based program for treating unhealthy alcohol use.

METHODS

This qualitative study was conducted in a primary care practice that was developing a collaborative care model for treating unhealthy alcohol use in primary care. Semi-structured interviews were conducted with 24 primary care patients. Data were analyzed using conventional qualitative content analysis.

RESULTS

Findings suggest that patients engaged for both internal (concerns about drinking and health) and external reasons (family or provider concern). Patient experiences in the program were shaped by their affective responses (enjoyable, enlightening), as well as therapeutic benefits (gaining new insights about drinking; staff/provider support). Acceptability was driven by core program elements (medication, therapy, integration) as well as positive impacts on drinking cognition and behavior and flexible, patient-centered approaches.

CONCLUSIONS

Offering flexible and comprehensive programs with mutiple elements and both abstinence and moderation goals could also improve patient engagement and views on acceptability. Primary care practices will need to be thoughtful about the resources needed to implement these programs in terms of staffing, training, and program support.

Developing AHRQ's Feasibility Assessment Criteria for Wide-Scale Implementation of Patient-Centered Outcomes Research Findings

BACKGROUND

The Agency for Healthcare Research and Quality's (AHRQ) Patient-Centered Outcomes Research (PCOR) Dissemination and Implementation (D&I) Initiative identifies and prioritizes PCOR findings that could improve health care if widely implemented. To inform PCOR implementation investments, AHRQ sought to assess feasibility of widely implementing impactful PCOR findings with good strength of evidence in clinical practice.

OBJECTIVE

To develop criteria to assess the feasibility of widely implementing nominated PCOR findings.

METHODS

We reviewed literature and interviewed thirteen D&I experts to identify factors affecting feasibility of implementing PCOR findings. We grouped similar factors into themes. Fourteen technical expert panel (TEP) members discussed the face-validity and relative merits of the themes and additional factors, applied themes to fictional case studies, and prioritized themes for assessing feasibility. We developed criteria and guiding questions with a 3-point Likert scale. Seven D&I experts pilot-tested the criteria using sample nominations of PCOR findings. Experts represented diverse views of implementation from federal and state government agencies, research institutions, and quality improvement and advocacy organizations.

KEY RESULTS

We developed a set of three essential criteria for AHRQ to assess feasibility of widely implementing PCOR findings to be widely implementable: (1) acceptability to the implementers; (2) generalizability, adaptability, and ease of implementing with fidelity; and (3) alignment with external policies and incentives. Two supplemental criteria, (1) the presence of a plan or toolkit supporting implementation, or (2) evidence supporting implementation outside the research setting, can enhance reviewers' confidence in the intervention's feasibility. Each criterion includes "guiding questions" to parse out specific components that could be more readily assessed.

CONCLUSIONS

The criteria and guiding questions are a valuable tool for informing AHRQ's investment decisions regarding implementing PCOR findings. Although developed for AHRQ's needs, the criteria may help other funders and health care organizations determine the feasibility of implementing evidence-based practices.

Costs of using evidence-based implementation strategies for behavioral health integration in a large primary care system

OBJECTIVE

To describe the cost of using evidence-based implementation strategies for sustained behavioral health integration (BHI) involving population-based screening, assessment, and identification at 25 primary care sites of Kaiser Permanente Washington (2015-2018).

DATA SOURCES/STUDY SETTING

Project records, surveys, Bureau of Labor Statistics compensation data.

STUDY DESIGN

Labor and nonlabor costs incurred by three implementation strategies: practice coaching, electronic health records clinical decision support, and performance feedback.

DATA COLLECTION/EXTRACTION METHODS

Personnel time spent on these strategies was estimated for five broad roles: (a) project leaders and administrative support, (b) practice coaches, (c) clinical decision support programmers, (d) performance metric programmers, and (e) primary care local implementation team members.

PRINCIPAL FINDING

Implementation involved 286 persons, 18 131 person-hours, costing $1 587 139 or $5 per primary care visit with screening or $38 per primary care visit identifying depression, suicidal thoughts and/or alcohol or substance use disorders, in a single year. The majority of person-hours was devoted to project leadership (35%) and practice coaches (34%), and 36% of costs were for the first three sites.

CONCLUSIONS

When spread across patients screened in a single year, BHI implementation costs were well within the range for commonly used diagnostic assessments in primary care (eg, laboratory tests). This suggests that implementation costs alone should not be a substantial barrier to population-based BHI.

Cannabis use, other drug use, and risk of subsequent acute care in primary care patients

BACKGROUND

Cannabis and other drug use is associated with adverse health events, but little is known about the association of routine clinical screening for cannabis or other drug use and acute care utilization. This study evaluated whether self-reported frequency of cannabis or other drug use was associated with subsequent acute care.

METHOD

This retrospective cohort study used EHR and claims data from 8 sites in Washington State that implemented annual substance use screening. Eligible adult primary care patients (N = 47,447) completed screens for cannabis (N = 45,647) and/or other drug use, including illegal drug use and prescription medication misuse, (N = 45,255) from 3/3/15-10/1/2016. Separate single-item screens assessed frequency of past-year cannabis and other drug use: never, less than monthly, monthly, weekly, daily/almost daily. An indicator of acute care utilization measured any urgent care, emergency department visits, or hospitalizations ≤19 months after screening. Adjusted Cox proportional hazards models estimated risk of acute care.

RESULTS

Patients were predominantly non-Hispanic White. Those reporting cannabis use less than monthly (Hazard Ratio [HR] = 1.12, 95 % CI = 1.03-1.21) or daily (HR = 1.24; 1.10-1.39) had greater risk of acute care during follow-up than those reporting no use. Patients reporting other drug use less than monthly (HR = 1.34; 1.13-1.59), weekly (HR = 2.21; 1.46-3.35), or daily (HR = 2.53; 1.86-3.45) had greater risk of acute care than those reporting no other drug use.

CONCLUSION

Population-based screening for cannabis and other drug use in primary care may have utility for understanding risk of subsequent acute care. It is unclear whether findings will generalize to U.S. states with broader racial/ethnic diversity.

Practice facilitation to implement alcohol-related care in Veterans Health Administration liver clinics: a study protocol

Background

Alcohol-related care, including screening, brief intervention, and provision of/referral to medication or behavioral treatments for alcohol use disorder, could be delivered in liver clinics to better reach patients with chronic liver conditions. However, the provision of alcohol-related care in liver clinics is currently suboptimal. Practice facilitation is an evidence-based implementation strategy that may address barriers, harness facilitators, and optimize the implementation of alcohol-related care in liver clinic settings using a clinic-centered approach. We report the protocol of a study to test a practice facilitation intervention to implement alcohol-related care in four Veterans Health Administration liver clinics.

Methods

This study will employ a Hybrid Type 3 effectiveness-implementation design, in which implementation outcomes are considered primary and clinical outcomes secondary. Intervention and evaluation design were informed by the Consolidated Framework for Implementation Research. Qualitative data collected from clinical stakeholders and patients were used to tailor the intervention. The intervention involves a 6-month period of external practice facilitation, including regular meetings to identify clinic goals, challenges, and solutions; engagement of clinic champions; provision of training and development of educational materials for clinic staff and patients; and performance monitoring and feedback. Ongoing formative evaluation involves the collection of quantitative facilitator tracking data and qualitative data from meeting notes and patient interviews to describe intervention acceptability, feasibility, and adoption, and adjust implementation as needed. In the summative evaluation, implementation outcomes (clinic rates of screening, brief intervention, and treatment referral/receipt) and clinical outcomes (unhealthy alcohol use, liver health) will be assessed among patients in participating clinics using secondary electronic health record data and interrupted time series analysis.

Discussion

This will be the first study to our knowledge to test practice facilitation to implement alcohol-related care in liver clinic settings. Results from formative and summative evaluation will inform a framework for the successful implementation of effective alcohol-related care through practice facilitation in liver clinics, which may ultimately lead to better health outcomes for patients with chronic liver disease.

What constitutes "behavioral health"? Perceptions of substance-related problems and their treatment in primary care

Background

Integrating behavioral health in primary care is a widespread endeavor. Yet rampant variation exists in models and approaches. One significant question is whether frontline providers perceive that behavioral health includes substance use. The current study examined front line providers’: 1. definition of behavioral health, and 2. levels of comfort treating patients who use alcohol and other drugs. Frontline providers at two primary care clinics were surveyed using a 28-item instrument designed to assess their comfort and knowledge of behavioral health, including substance use. Two questions from the Integrated Behavioral Health Staff Perceptions Survey pertaining to confidence in clinics’ ability to care for patients’ behavioral health needs and comfort dealing with patients with behavioral health needs were used for the purposes of this report. Participants also self-reported their clinic role. Responses to these two items were assessed and then compared across roles. Chi square estimates and analysis of variance tests were used to examine relationships between clinic roles and comfort of substance use care delivery.

Results

Physicians, nurses/nurse practitioners, medical assistants, and other staff (N = 59) participated. Forty-nine participants included substance use in their definition of behavioral health. Participants reported the least comfort caring for patients who use substances (M = 3.5, SD = 1.0) compared to those with mental health concerns (M = 4.1, SD = 0.7), chronic medical conditions (M = 4.2, SD = 0.7), and general health concerns (M = 4.2, SD = 0.7) (p < 0.001). Physicians (M = 3.0, SD = 0.7) reported significantly lower levels of comfort than medical assistants (M = 4.2, SD = 0.9) (p < 0.001) caring for patients who use substances.

Conclusions

In a small sample of key stakeholders from two primary care clinics who participated in this survey, most considered substance use part of the broad umbrella of behavioral health. Compared to other conditions, primary care providers reported being less comfortable addressing patients’ substance use. Level of comfort varied by role, where physicians were least comfortable, and medical assistants most comfortable.

A review of nonpharmacological adjunctive treatment for postpartum women with opioid use disorder

INTRODUCTION

Over the past decade, opioid use disorder (OUD) among pregnant women has increased by over 400%. Although medication assisted treatment (MAT) provides necessary care for women with OUD, effective adjunctive nonpharmacological treatments have not been systematically identified. This is especially concerning for the postpartum period, which includes several unique risk factors (e.g., sleep deprivation, mood disturbances) for MAT non-adherence and relapse. This review summarizes the existing knowledge regarding nonpharmacological treatments for OUD during the postpartum period, as well as provides recommendations for the future.

METHODS

PubMed and PsycINFO were searched in July 2018 using combinations of 28 keywords. Eligibility criteria included: (1) coverage of postpartum period, (2) use of nonpharmacological treatment for OUD, (3) conducted in clinical samples, and (4) written in English.

RESULTS

A total of 4 out of 38 identified articles met eligibility criteria. Two of the studies offered weekly on-site group counseling, with one also offering monthly social worker meetings. The third study offered four sessions with a patient navigator during the postpartum period. The last offered an employment intervention. All four reported favorable effects on OUD at end of follow-up (range: 30 days postpartum to 1 year postpartum). However, the details of the interventions, methodologies, and abstinence rates were sparse.

DISCUSSION

Few published studies examine nonpharmacological OUD treatments specific to the postpartum period. Identification of adjunctive nonpharmacological treatments designed to the unique needs of postpartum women is of critical public health importance, and further research is needed.

Impact of Alcohol Use Disorder Treatment on Clinical Outcomes Among Patients With Cirrhosis

BACKGROUND AND AIMS

Despite the significant medical and economic consequences of coexisting alcohol use disorder (AUD) in patients with cirrhosis, little is known about AUD treatment patterns and their impact on clinical outcomes in this population. We aimed to characterize the use of and outcomes associated with AUD treatment in patients with cirrhosis.

APPROACH AND RESULTS

This retrospective cohort study included Veterans with cirrhosis who received Veterans Health Administration care and had an index diagnosis of AUD between 2011 and 2015. We assessed the baseline factors associated with AUD treatment (pharmacotherapy or behavioral therapy) and clinical outcomes for 180 days following the first AUD diagnosis code within the study time frame. Among 93,612 Veterans with cirrhosis, we identified 35,682 with AUD, after excluding 2,671 who had prior diagnoses of AUD and recent treatment. Over 180 days following the index diagnosis of AUD, 5,088 (14%) received AUD treatment, including 4,461 (12%) who received behavioral therapy alone, 159 (0.4%) who received pharmacotherapy alone, and 468 (1%) who received both behavioral therapy and pharmacotherapy. In adjusted analyses, behavioral and/or pharmacotherapy-based AUD treatment was associated with a significant reduction in incident hepatic decompensation (6.5% vs. 11.6%, adjusted odds ratio [AOR], 0.63; 95% confidence interval [CI], 0.52, 0.76), a nonsignificant decrease in short-term all-cause mortality (2.6% vs. 3.9%, AOR, 0.79; 95% CI, 0.57, 1.08), and a significant decrease in long-term all-cause mortality (51% vs. 58%, AOR, 0.87; 95% CI, 0.80, 0.96).

CONCLUSIONS

Most Veterans with cirrhosis and coexisting AUD did not receive behavioral therapy or pharmacotherapy treatment for AUD over a 6-month follow-up. The reductions in hepatic decompensation and mortality suggest that future studies should focus on delivering evidence-based AUD treatments to patients with coexisting AUD and cirrhosis.

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

BACKGROUND

Most patients with substance use disorders (SUDs) never receive treatment and SUDs are under-recognized in primary care (PC) where patients can be treated or linked to treatment. Asking PC patients to directly report SUD symptoms on questionnaires might help identify SUDs but to our knowledge, this approach is previously untested.

OBJECTIVE

To describe the prevalence and severity of DSM-5 SUD symptoms reported by PC patients as part of routine care.

DESIGN

Cross-sectional study using secondary data.

PARTICIPANTS

A total of 241,265 adult patients who visited one of 25 PC sites in an integrated health system in Washington state and had alcohol, cannabis, or other drug use screening documented in their EHRs (March 2015-July 2018) were included in main analyses if they had a positive screen for high-risk substance use defined as AUDIT-C score 7-12 points, or report of past-year daily cannabis use or any other drug use.

MAIN MEASURES

The main outcome was number of SUD symptoms based on Diagnostic and Statistical Manual, 5th edition (DSM-5), reported on Symptom Checklists (0-11) for alcohol or other drugs: 2-3 mild; 4-5 moderate; 6-11 severe.

RESULTS

Of screened patients, 16,776 (5.7%) reported high-risk use of alcohol (2.4%), cannabis (3.9%), and/or other drugs (1.7%), and 65.0-69.9% of those completed Symptom Checklists. Of those with high-risk alcohol use, 52.5% (95% CI 50.9-54.0%) reported ≥ 2 symptoms consistent with mild-severe alcohol use disorders. Of those reporting daily cannabis use, 29.8% (28.6-30.9%) reported ≥ 2 symptoms consistent with mild-severe SUDs. Of those reporting any other drug use, 37.5% (35.7-39.3%) reported ≥ 2 symptoms consistent with mild-severe SUDs.

CONCLUSIONS AND RELEVANCE

Many PC patients who screened positive for high-risk substance use reported symptoms consistent with DSM-5 SUDs on self-report Symptom Checklists. Use of SUD Symptom Checklists could support PC providers in making SUD diagnoses and initiating discussions of substance use.

Documented brief intervention associated with reduced linkage to specialty addictions treatment in a national sample of VA patients with unhealthy alcohol use with and without alcohol use disorders

BACKGROUND AND AIMS

Alcohol screening, brief intervention (BI) and referral to treatment is often considered stepped care, such that BI with referral links patients to treatment. A meta-analysis of randomized trials found no evidence that BI increases treatment for alcohol use disorder (AUD). This study aimed to determine whether BI is associated with receipt of treatment for AUD among patients receiving BI as part of routine care.

DESIGN

Regression analysis.

SETTING

US Veterans Health Administration (VA), in which BI is supported by performance measurement and electronic clinical reminders.

PARTICIPANTS

VA outpatients with positive Alcohol Use Disorders Identification Test Consumption screens (≥ 5) (n = 830,825) documented nationally from 1 October 2009 to 30 May 2013.

MEASUREMENTS

Regression models estimated the prevalence of receiving VA specialty addictions treatment within 0-365 days for patients with documented BI (advice to reduce/abstain within 0-14 days) compared to those without. Models clustered on patient and adjusted for demographics and mental health and substance use conditions were fit among all patients and stratified across documented past-year AUD diagnosis. Multiple secondary analyses assessed robustness of findings, including assessing repeated BI as a predictor.

FINDINGS

Among 830,825 VA outpatients with unhealthy alcohol use (1,172,606 positive screens), documented BI was associated with lower likelihood of receiving VA specialty addictions treatment [adjusted incidence rate ratio (aIRR) = 0.84, 95% confidence interval (CI) = 0.83-0.84]. Associations were similar for those with and without AUD (aIRR = 0.83, 95% CI = 0.82-0.84 and aIRR = 0.86, 95% CI = 0.83-0.88, respectively) and in most secondary analyses. However, among patients without AUD, documentation of more than one BI was associated with greater likelihood of treatment relative to no BI (aIRR = 1.75, 95% CI = 1.68-1.83).

CONCLUSIONS

In a national sample of US Veterans Health Administration patients with unhealthy alcohol use, documented brief intervention for alcohol use was associated with lower likelihood of receiving specialty addictions treatment regardless of alcohol use disorder diagnosis.

Addressing identification bias in the design and analysis of cluster-randomized pragmatic trials: a case study

Background

Pragmatic trials provide the opportunity to study the effectiveness of health interventions to improve care in real-world settings. However, use of open-cohort designs with patients becoming eligible after randomization and reliance on electronic health records (EHRs) to identify participants may lead to a form of selection bias referred to as identification bias. This bias can occur when individuals identified as a result of the treatment group assignment are included in analyses.

Methods

To demonstrate the importance of identification bias and how it can be addressed, we consider a motivating case study, the PRimary care Opioid Use Disorders treatment (PROUD) Trial. PROUD is an ongoing pragmatic, cluster-randomized implementation trial in six health systems to evaluate a program for increasing medication treatment of opioid use disorders (OUDs). A main study objective is to evaluate whether the PROUD intervention decreases acute care utilization among patients with OUD (effectiveness aim). Identification bias is a particular concern, because OUD is underdiagnosed in the EHR at baseline, and because the intervention is expected to increase OUD diagnosis among current patients and attract new patients with OUD to the intervention site. We propose a framework for addressing this source of bias in the statistical design and analysis.

Results

The statistical design sought to balance the competing goals of fully capturing intervention effects and mitigating identification bias, while maximizing power. For the primary analysis of the effectiveness aim, identification bias was avoided by defining the study sample using pre-randomization data (pre-trial modeling demonstrated that the optimal approach was to use individuals with a prior OUD diagnosis). To expand generalizability of study findings, secondary analyses were planned that also included patients newly diagnosed post-randomization, with analytic methods to account for identification bias.

Conclusion

As more studies seek to leverage existing data sources, such as EHRs, to make clinical trials more affordable and generalizable and to apply novel open-cohort study designs, the potential for identification bias is likely to become increasingly common. This case study highlights how this bias can be addressed in the statistical study design and analysis.

Trial registration

ClinicalTrials.gov, NCT03407638. Registered on 23 January 2018.

Short-term risk of suicide attempt associated with patterns of patient-reported alcohol use determined by routine AUDIT-C among adults receiving mental healthcare

OBJECTIVE

To evaluate the association between alcohol use routinely reported during outpatient mental healthcare visits and short-term risk of subsequent suicide attempt.

METHODS

Using a longitudinal retrospective-cohort design, electronic health records identified adult outpatient visits to a mental health provider (1/1/2010-6/30/2015) at Kaiser Permanente Washington with a documented Alcohol Use Disorders Identification Test-Consumption [AUDIT-C]. Suicide attempts within 90 days of AUDIT-C documentation were defined using death certificate cause-of-death and diagnosis codes (non-lethal). Visit-level analyses used generalized estimating equations to account for correlation between multiple AUDIT-Cs for individuals. Separate models evaluated the association between (1) level of consumption and (2) frequency of heavy drinking episodes and suicide attempts, adjusted for visit year, demographics, depressive symptom, and suicidal ideation.

RESULTS

Of 59,382 patient visits, 0.62% (N = 371) were followed by a suicide attempt within 90 days. Patients reporting high-level alcohol use were 1.77 times (95% CI, 1.22-2.57) more likely to attempt suicide than those reporting low-level use. Patients reporting daily or almost daily heavy drinking episodes were 2.33 times (95% CI, 1.38-3.93) more likely to attempt suicide than those reporting none.

CONCLUSIONS AND RELEVANCE

The AUDIT-C is a valuable tool for assessing patterns of patient-reported alcohol use associated with subsequent suicide attempt.

The 2019 addiction health services research conference: Insights, review, and abstracts

The 2019 Addiction Health Services Research (AHSR) Conference was held from October 16 to 18, 2019 in Park City, Utah. The conference was hosted by the Program for Addiction, Research, Clinical Care, Knowledge, and Advocacy within the Division of Epidemiology, Department of Internal Medicine at the University of Utah School of Medicine. AHSR is an annual conference to share discoveries, network with colleagues, and learn the most up-to-date research regarding how to identify, assess, and treat persons with addictions. This commentary contains 2019 AHSR specific goals and descriptions of content shared at this year's conference. Descriptions include information regarding pre-conference activities and conference plenaries, mentorship opportunities, and investigator awardees. Commentary also includes acknowledgments of those who assisted in making the 2019 AHSR Conference possible. Additionally, abstracts of the scientific research presented at the conference are included.

Making measurement-based care for addictions a reality in primary care

Three factors are important to consider when integrating measurement-based care for opioid use disorders into primary care: integration with other behavioral health and substance use disorders care, the availability of a brief, valid measure that is responsive to change, and implementation in a manner that fosters accurate reporting.

Integration of screening, assessment, and treatment for cannabis and other drug use disorders in primary care: An evaluation in three pilot sites

BACKGROUND

This pilot study evaluated whether use of evidence-based implementation strategies to integrate care for cannabis and other drug use into primary care (PC) as part of Behavioral Health Integration (BHI) increased diagnosis and treatment of substance use disorders (SUDs).

METHODS

Patients who visited the three pilot PC sites were eligible. Implementation strategies included practice coaching, electronic health record decision support, and performance feedback (3/2015-4/2016). BHI introduced annual screening for past-year cannabis and other drug use, a Symptom Checklist for DSM-5 SUDs, and shared decision-making about treatment options. Main analyses tested whether the proportions of PC patients diagnosed with, and treated for, new cannabis or other drug use disorders (CUDs and DUDs, respectively), differed significantly pre- and post-implementation.

RESULTS

Of 39,599 eligible patients, 57% and 59% were screened for cannabis and other drug use, respectively. Among PC patients reporting daily cannabis use (2%) or any drug use (1%), 51% and 37%, respectively, completed an SUD Symptom Checklist. The proportion of PC patients with newly diagnosed CUD increased significantly post-implementation (5 v 17 per 10,000 patients, p < 0.0001), but not other DUDs (10 vs 13 per 10,000, p = 0.24). The proportion treated for newly diagnosed CUDs did not increase post-implementation (1 vs 1 per 10,000, p = 0.80), but did for those treated for newly diagnosed other DUDs (1 vs 3 per 10,000, p = 0.038).

CONCLUSIONS

A pilot implementation of BHI to increase routine screening and assessment for SUDs was associated with increased new CUD diagnoses and a small increase in treatment of new other DUDs.