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ObjectiveIndividuals with unhealthy alcohol use and comorbid depression or anxiety may be vulnerable to alcohol use escalation in times of stress such as the COVID-19 pandemic. Among a cohort of individuals with pre-pandemic unhealthy drinking, we compared changes in alcohol use by whether people had a depression or anxiety diagnosis, and examined whether mental health treatment was related to these changes.MethodsUsing electronic health record data from Kaiser Permanente Northern California, we analyzed drinking changes during the pandemic (3/1/2020-6/30/2022) among adults identified in primary care with unhealthy alcohol use (exceeding daily/weekly recommended limits) pre-pandemic (1/1/2019-2/29/2020). Outcomes were mean changes in number of heavy drinking days (prior three months), drinks/week, drinks/day, and drinking days/week. Multivariable linear regression models were fit to: 1) compare outcomes of patients with depression or anxiety diagnoses to those without, and 2) among patients with depression or anxiety, estimate associations between mental health treatment and outcomes.ResultsThe sample included 62,924 adults with unhealthy alcohol use, of whom 12,281 (19.5%) had depression or anxiety. On average, alcohol use significantly decreased across all measures during the pandemic, but patients with depression or anxiety had greater decreases in drinks/week (adjusted mean difference [aMD] [CI]=-0.34 [-0.55, -0.12]) and drinking days/week (-0.15 [-0.20, -0.10]). No associations were found between mental health treatment and changes in drinking.ConclusionsContrary to expectations, patients with unhealthy alcohol use and depression or anxiety decreased alcohol use more than those without depression or anxiety during COVID-19, whether or not they accessed mental health services.

Background: Cannabis use disorders (CUDs) have increased with more individuals using cannabis, yet few receive treatment. Health systems have adopted the Healthcare Effectiveness Data and Information Set (HEDIS) quality measures of initiation and engagement in alcohol and other drug (AOD) dependence treatment, but little is known about the performance of these among patients with CUDs. Methods: This cohort study utilized electronic health records and claims data from 7 health care systems to identify patients with documentation of a new index CUD diagnosis (no AOD diagnosis ≤60 days prior) from International Classification of Diseases, Ninth revision, codes (October 1, 2014, to August 31, 2015). The adjusted prevalence of each outcome (initiation, engagement, and a composite of both) was estimated from generalized linear regression models, across index identification settings (inpatient, emergency department, primary care, addiction treatment, and mental health/psychiatry), AOD comorbidity (patients with CUD only and CUD plus other AOD diagnoses), and patient characteristics. Results: Among 15,202 patients with an index CUD diagnosis, 30.0% (95% confidence interval [CI]: 29.2-30.7%) initiated, 6.9% (95% CI: 6.2-7.7%) engaged among initiated, and 2.1% (95% CI: 1.9-2.3%) overall both initiated and engaged in treatment. The adjusted prevalence of outcomes varied across index identification settings and was highest among patients diagnosed in addiction treatment, with 25.0% (95% CI: 22.5-27.6%) initiated, 40.9% (95% CI: 34.8-47.0%) engaged, and 12.5% (95% CI: 10.0-15.1%) initiated and engaged. The adjusted prevalence of each outcome was generally highest among patients with CUD plus other AOD diagnosis at index diagnosis compared with those with CUD only, overall and across index identification settings, and was lowest among uninsured and older patients. Conclusion: Among patients with a new CUD diagnosis, the proportion meeting HEDIS criteria for initiation and/or engagement in AOD treatment was low and demonstrated variation across index diagnosis settings, AOD comorbidity, and patient characteristics, pointing to opportunities for improvement.

Background: Only 10% of patients with alcohol and other drug (AOD) disorders receive treatment. The AOD Initiation and Engagement in Treatment (AOD-IET) measure was added to the national Healthcare Effectiveness Data and Information Set (HEDIS) to improve access to care. This study identifies factors related to improving AOD-IET rates. Methods: We include data from 7 health systems with differing geographic, patient demographic, and organizational characteristics; all used a common Virtual Data Warehouse containing electronic health records and insurance claims data. Multilevel logistic regression models examined AOD-IET among adults (18+). Results: A total of 86,565 patients had an AOD diagnosis qualifying for the HEDIS denominator. The overall initiation rate was 27.9% with wide variation; the overall engagement rate was 11.5% and varied from 4.5% to 17.9%. Women versus men (odds ratio [OR] = 0.81, 95% confidence interval [CI] = 0.76-0.86); Hispanics (OR = 0.85, 95% CI = 0.79-0.91), black/African Americans (OR = 0.82, 95% CI = 0.75-0.90), and Asian Americans (OR = 0.83, 95% CI = 0.72-0.95) versus whites; and patients aged 65+ versus 18-29 (OR = 0.82, 95% CI = 0.74-0.90) had lower odds of initiation. Patients aged 30-49 versus 18-29 (OR = 1.11, 95% CI = 1.04-1.19) and those with prior psychiatric (OR = 1.26, 95% CI = 1.18-1.35) and medical (OR = 1.18, 95% CI = 1.10-1.26) conditions had higher odds of initiation. Identification in primary care versus other departments was related to lower odds of initiation (emergency department [ED]: OR = 1.55, 95% CI = 1.45-1.66; psychiatry/AOD treatment: OR = 3.58, 95% CI = 3.33-3.84; other outpatient: OR = 1.19, 95% CI = 1.06-1.32). Patients aged 30-49 versus 18-29 had higher odds of engagement (OR = 1.26, 95% CI = 1.10-1.43). Patients aged 65+ versus 18-29 (OR = 0.51, 95% CI = 0.43-0.62) and black/African Americans versus whites (OR = 0.64, 95% CI = 0.53-0.77) had lower odds. Those initiating treatment in psychiatry/AOD treatment versus primary care (OR = 7.02, 95% CI = 5.93-8.31) had higher odds of engagement; those in inpatient (OR = 0.40, 95% CI = 0.32-0.50) or other outpatient (OR = 0.73, 95% CI = 0.59-0.91) settings had lower odds. Discussion: Rates of initiation and engagement varied but were low. Findings identified age, race/ethnicity, co-occurring conditions, and department of identification as key factors associated with AOD-IET. Focusing on these could help programs develop interventions that facilitate AOD-IET for those less likely to receive care.

Background: Medical comorbidity may influence treatment initiation and engagement for alcohol and other drug (AOD) use disorders. We examined the association between medical comorbidity and Healthcare Effectiveness Data and Information Set (HEDIS) treatment initiation and engagement measures.Methods: We used electronic health record and insurance claims data from 7 US health care systems to identify patients with AOD use disorders between October 1, 2014, and August 15, 2015 (N = 86,565). Among patients identified with AOD use disorders in outpatient and emergency department (ED) settings, we examined how Charlson/Deyo comorbidity index scores and medical complications of AOD use were associated with treatment initiation. Among those who initiated treatment in inpatient and outpatient/ED settings, we also examined how comorbidity and AOD use-related medical complications were associated with treatment engagement. Analyses were conducted using generalized estimating equation logistic regression modeling.Results: Among patients identified as having an AOD diagnosis in outpatient and ED settings (n = 69,965), Charlson/Deyo comorbidity index scores of 2 or more were independently associated with reduced likelihood of initiation (risk ratio [RR] = 0.80, 95% confidence interval [CI] = 0.74, 0.86; reference score = 0), whereas prior-year diagnoses of cirrhosis (RR = 1.25, 95% CI = 1.12, 1.35) and pancreatic disease (RR = 1.34, 95% CI = 1.15, 1.56) were associated with greater likelihood of initiation. Among those who were identified in outpatient/ED settings and initiated, higher comorbidity scores were associated with lower likelihood of engagement (score 1: RR = 0.85, 95% CI = 0.76, 0.94; score 2+: RR = 0.61, 95% CI = 0.53, 0.71).Conclusion: Medical comorbidity was associated with lower likelihood of initiating or engaging in AOD treatment, but cirrhosis and pancreatic disease were associated with greater likelihood of initiation. Interventions to improve AOD treatment initiation and engagement for patients with comorbidities are needed, such as integrating medical and AOD treatment.

Background: Psychiatric comorbidity is common among patients with alcohol and other drug (AOD) use disorders. To better understand how psychiatric comorbidity influences AOD treatment access in health care systems, the present study examined treatment initiation and engagement among a large, diverse sample of patients with comorbid psychiatric and AOD use disorders. Methods: This study utilized data from a multisite observational study examining Healthcare Effectiveness Data and Information Set (HEDIS) measures of initiation and engagement in treatment (IET) among patients with AOD use disorders from 7 health care systems. Participants were aged 18 or older with at least 1 AOD index diagnosis between October 1, 2014, and August 15, 2015. Data elements extracted from electronic health records and insurance claims data included patient demographic characteristics, ICD-9 (International Classification of Diseases, Ninth Revision) diagnostic codes, and procedure codes. Descriptive analyses and multivariate logistic regression models were used to examine the relationship between patient-level factors and IET measures. Results: Across health care systems, out of a total of 86,565 patients who had at least 1 AOD index diagnosis during the study period, 66.2% (n = 57,335) patients also had a comorbid psychiatric disorder. Among patients with a comorbid psychiatric disorder, 34.9% (n = 19,998) initiated AOD treatment, and of those, 10.3% (n = 2,060) engaged in treatment. After adjusting for age, sex, and race/ethnicity, patients with comorbid psychiatric disorders were more likely to initiate (odds ratio [OR] = 3.20, 95% confidence interval [CI] = 3.08, 3.32) but no more likely to engage (OR = 0.56, 95% CI = 0.51, 0.61) in AOD treatment, compared with those without a comorbid psychiatric disorder. Conclusions: Findings suggest that identification of comorbid psychiatric disorders may increase initiation in AOD treatment. However, innovative efforts are needed to enhance treatment engagement both generally and especially for individuals without diagnosed psychiatric conditions.

ObjectivesConcomitant excessive alcohol consumption and benzodiazepine use is associated with adverse health outcomes. We examined associations of unhealthy alcohol use and other patient characteristics with benzodiazepine use.Study designA cross-sectional analysis of 2,089,525 Kaiser Permanente of Northern California outpatients screened for unhealthy alcohol use in primary care between November 1, 2014, and December 31, 2016.MethodsWe fit multivariable generalized linear models to estimate the associations between unhealthy alcohol use and benzodiazepine dispensation and, among patients who were dispensed a benzodiazepine, mean doses (in mean lorazepam-equivalent daily doses [LEDDs]) and prescription durations. We controlled for patient sex, age, race/ethnicity, estimated household income, Charlson Comorbidity Index (CCI) score, anxiety disorder, alcohol use disorder, insomnia, musculoskeletal pain, and epilepsy.ResultsIn the 12 months centered around (6 months before and 6 months after) the first alcohol-screening visit, 7.5% of patients used benzodiazepines. The following characteristics were independently associated with higher rates of benzodiazepine use, higher LEDD, and longer prescription duration: older age, white race/ethnicity, lower estimated household income, higher CCI score, and the presence of an anxiety disorder, insomnia, musculoskeletal pain, or epilepsy. Women and patients with an alcohol use disorder or unhealthy alcohol use, compared with men and patients with low-risk drinking or abstinence, were more likely to use a benzodiazepine; however, their LEDDs were lower and their prescription durations were shorter.ConclusionsBenzodiazepine use in primary care was associated with older age, female sex, white race/ethnicity, lower socioeconomic status, and unhealthy alcohol use. These findings may be applied to develop policies and interventions to promote judicious benzodiazepine use.

Background: Problematic use of alcohol and other drugs (AOD) is highly prevalent among people living with the human immunodeficiency virus (PLWH), and untreated AOD use disorders have particularly detrimental effects on human immunodeficiency virus (HIV) outcomes. The Healthcare Effectiveness Data and Information Set (HEDIS) measures of treatment initiation and engagement are important benchmarks for access to AOD use disorder treatment. To inform improved patient care, we compared HEDIS measures of AOD use disorder treatment initiation and engagement and health care utilization among PLWH and patients without an HIV diagnosis. Methods: Patients with a new AOD use disorder diagnosis documented between October 1, 2014, and August 15, 2015, were identified using electronic health records (EHR) and insurance claims data from 7 health care systems in the United States. Demographic characteristics, clinical diagnoses, and health care utilization data were also obtained. AOD use disorder treatment initiation and engagement rates were calculated using HEDIS measure criteria. Factors associated with treatment initiation and engagement were examined using multivariable logistic regression models. Results: There were 469 PLWH (93% male) and 86,096 patients without an HIV diagnosis (60% male) in the study cohort. AOD use disorder treatment initiation was similar in PLWH and patients without an HIV diagnosis (10% vs. 11%, respectively). Among those who initiated treatment, few engaged in treatment in both groups (9% PLWH vs. 12% patients without an HIV diagnosis). In multivariable analysis, HIV status was not significantly associated with either AOD use disorder treatment initiation or engagement. Conclusions: AOD use disorder treatment initiation and engagement rates were low in both PLWH and patients without an HIV diagnosis. Future studies need to focus on developing strategies to efficiently integrate AOD use disorder treatment with medical care for HIV.

INTRODUCTION: Rapid identification of individuals developing a psychotic spectrum disorder (PSD) is crucial because untreated psychosis is associated with poor outcomes and decreased treatment response. Lack of recognition of early psychotic symptoms often delays diagnosis, further worsening these outcomes. MET HODS: The proposed study is a cross-sectional, retrospective analysis of electronic health record data including clinician documentation and patient-clinician secure messages for patients aged 15-29 years with = 1 primary care encounter between 2017 and 2019 within 2 Kaiser Permanente regions. Patients with new-onset PSD will be distinguished from those without a diagnosis if they have = 1 PSD diagnosis within 12 months following the primary care encounter. The prediction model will be trained using a trisourced natural language processing feature extraction design and validated both within each region separately and in a modified combined sample. DISCUSSION: This proposed model leverages the strengths of the large volume of patient-specific data from an integrated electronic health record with natural language processing to identify patients at elevated chance of developing a PSD. This project carries the potential to reduce the duration of untreated psychosis and thereby improve long-term patient outcomes. [ABSTRACT FROM AUTHOR]

BackgroundHazardous alcohol use with depression may exacerbate health conditions and complicate medical care. We examined the rate of depression screening by alcohol use severity among primary care patients screened for hazardous alcohol use and, among those screened, examined patterns of significant depressive symptoms.MethodsUsing cross-sectional data from primary care patients (n = 2,894,906), we examined past-90-day alcohol use (number of typical drinking days/week and typical number of drinks consumed daily); depression screening rates (using the Patient Health Questionnaire 9 [PHQ-9]); and symptom severity, demographics, and prevalence of selected psychiatric diagnoses.ResultsWithin 30 days of routine, in-clinic alcohol use screening by medical assistants, 2.4% (n = 68,686) of patients also completed a PHQ-9; these patients were more likely to be female, younger, white, Medicaid insured, and to have a nondepressive psychiatric diagnosis and a lower Charlson comorbidity score. Abstainers and moderate drinkers (1 to 7 drinks/week or 1 to 4 drinks/week for women and individuals >65 years or for men ≤65 years, respectively) were less likely than hazardous drinkers (exceeding weekly limits) to complete the PHQ-9 or to have significant depressive symptoms (PHQ-9 score ≥10). Nonwhite patients with higher Charlson comorbidity scores were more likely to endorse significant depressive symptoms.ConclusionsOnly a small fraction of patients in this cohort were screened for depression. Nonwhite patients and those with higher comorbidity burden were more likely to report depression but less likely to be screened. These discrepancies between depression-screening rates and significant depressive symptoms suggest that screening for depression should be enhanced in these at-risk groups.

PURPOSE:Early intervention for adolescent substance use and mental health problems may mitigate potential harm. We examined patient outcomes from a pragmatic trial of two modalities of delivering screening, brief intervention, and referral to treatment (SBIRT) and usual care (UC) in pediatric primary care. METHODS:All clinic pediatricians (n = 52) were randomized to three arms: (1) pediatrician-only, in which pediatricians were trained to deliver SBIRT; (2) embedded behavioral clinician (BC), in which pediatricians were trained to refer eligible adolescents to a BC who administered SBIRT; and (3) UC. Using electronic health record data, changes in past year substance use and depression symptoms between the index visit and next screening visit were examined across treatment arms. RESULTS:Among patients who endorsed substance use and/or depression symptoms or were eligible for further assessments, brief interventions, and referrals based on clinician assessment at the index visit, 648 patients (mean age = 15.2 [standard deviation = 1.2]) were rescreened at a follow-up visit between 6 months and 2 years later. Among all patients, self-reported substance use rates did not differ over time or across arms, and depression symptoms increased over time. The embedded BC arm had lower odds of having depression symptoms at follow-up than the physician-only arm, and lower odds than the UC arm although not significant; we found no differences between the pediatrician-only and UC arms. CONCLUSIONS:The increase in depression symptoms over time highlights this population's vulnerability and the importance of developing appropriate interventions. An embedded BC in pediatric primary care trained in SBIRT may benefit patients with depression symptoms.

BackgroundChanges in substance use patterns stemming from opioid misuse, ongoing drinking problems, and marijuana legalization may result in new populations of patients with substance use disorders (SUDs) using emergency department (ED) resources. This study examined ED admission trends in a large sample of patients with alcohol, marijuana, and opioid use disorders in an integrated health system.MethodsIn a retrospective design, electronic health record (EHR) data identified patients with ≥1 of 3 common SUDs in 2010 (n = 17,574; alcohol, marijuana, or opioid use disorder) and patients without SUD (n = 17,574). Logistic regressions determined odds of ED use between patients with SUD versus controls (2010-2014); mixed-effect models examined 5-year differences in utilization; moderator models identified subsamples for which patients with SUD may have a greater impact on ED resources.ResultsOdds of ED use were higher at each time point (2010-2014) for patients with alcohol (odds ratio [OR] range: 5.31-2.13, Ps < .001), marijuana (OR range: 5.45-1.97, Ps < .001), and opioid (OR range: 7.63-4.19, Ps < .001) use disorders compared with controls; odds decreased over time (Ps < .001). Patients with opioid use disorder were at risk of high ED utilization; patients were 7.63 times more likely to have an ED visit in 2010 compared with controls and remained 5.00 (average) times more likely to use ED services. ED use increased at greater rates for patients with alcohol and opioid use disorders with medical comorbidities relative to controls (Ps < .045).ConclusionsED use is frequent in patients with SUDs who have access to private insurance coverage and integrated medical services. ED settings provide important opportunities in health systems to identify patients with SUDs, particularly patients with opioid use disorder, to initiate treatment and facilitate ongoing care, which may be effective for reducing excess medical emergencies and ED encounters.

ObjectiveMany adolescents needing specialty addiction or psychiatry treatment never access care. We examined initiation and engagement with addiction and/or psychiatry treatment among adolescents referred to treatment from a trial comparing two different modalities of delivering Screening, Brief Intervention and Referral to Treatment (SBIRT) to Usual Care in pediatric primary care. We hypothesized that both intervention arms would have higher initiation and engagement rates than usual care.MethodsWe randomized all pediatricians (n=52) in a pediatric primary care clinic to three arms: 1) pediatrician-only arm, in which pediatricians were trained to deliver SBIRT for substance use and/or mental health problems; 2) embedded-behavioral health clinician (embedded-BHC arm), in which pediatricians referred adolescents who endorsed substance use and/or mental health problems to a BHC; and 3) Usual Care (UC). We used electronic health record (EHR) data to examine specialty addiction and psychiatry treatment initiation and engagement rates after referral.ResultsAmong patients who screened positive for substance use and/or mental health problems and were referred to specialty addiction and/or psychiatry (n=333), those in the embedded-BHC arm had almost four times higher odds of initiating treatment than those in the pediatrician-only arm, OR=3.99, 95% CI=[1.99-8.00]. Compared to UC, those in the pediatrician-only arm had lower odds of treatment initiation (OR=0.53, 95% CI=[0.28-0.99]), while patients in the embedded-BHC arm had marginally higher odds (OR=1.83, 95% CI=[0.99-3.38]). Black patients and those with other/unknown race/ethnicity had lower odds of treatment initiation compared with white adolescents; there were no gender or age differences. We found no differences in treatment engagement across the three arms.ConclusionsEmbedded BHCs can have a significant positive impact on facilitating treatment initiation for pediatric primary care adolescents referred to addiction and/or psychiatry services.Clinical trials registrationClinicalTrials.gov #NCT02408952.

BackgroundMarijuana use disorder (MUD) is the most common illegal drug use disorder and its prevalence is increasing. It is associated with psychiatric and medical problems, but little is known about its impact on emergency department (ED) and inpatient utilization rates.DesignIn a retrospective cohort design, we used electronic health record (EHR) data to identify patients with MUD (n=2752) and demographically matched patients without MUD (n=2752) in 2010. Logistic regressions determined risk of ED and inpatient visits each year from 2010 to 2014 for MUD patients versus controls; mixed-effect growth models examined differences in utilization rates over 5-years. Patient characteristics predicting increased risk of utilization were examined among the MUD sample only.Key resultsRates of ED (OR=0.87, p

ObjectiveTo examine the odds associated with having medical comorbidities among patients with serious mental illness (SMI) in a large integrated health system.MethodIn a secondary analysis of electronic health record data, this study identified 25,090 patients with an ICD-9 SMI diagnosis of bipolar disorder (n=20,308) or schizophrenia (n=4782) and 25,090 controls who did not have a SMI, matched on age, gender, and medical home facility. Conditional logistic regressions compared the odds associated with having nine medical comorbidity categories and fifteen chronic or serious conditions among patients with SMI versus controls.ResultsResults showed having a SMI was associated with significantly higher odds of each medical comorbidity examined (p's1.5 times the odds of each condition (p's

BackgroundTreatment for alcohol use disorders (AUDs) has traditionally been abstinence oriented, but new research and regulatory guidelines suggest that low-risk drinking may also be an acceptable treatment outcome. However, little is known about long-term outcomes for patients who become low-risk drinkers posttreatment. This study explores a posttreatment low-risk drinking outcome as a predictor of future drinking and psychosocial outcomes over 9 years.MethodsStudy participants were adults with AUDs at treatment entry who received follow-up interviews 6 months posttreatment intake (N = 1,061) in 2 large randomized studies conducted at Kaiser Permanente Northern California, a large private, nonprofit, integrated health system. Six-month drinking status was defined as abstinent, low-risk (nonabstinent, no 5+ drinking days), or heavy drinking (1 or more days of 5+ drinks). Using logistic regression models, we explored the relationship between past 30-day drinking status at 6 months and odds of being abstinent or a low-risk drinker (compared to heavy drinking), and positive Addiction Severity Index psychosocial outcomes over 9 years (9-year follow-up rate of 73%).ResultsAbstainers and low-risk drinkers at 6 months had higher odds of recent abstinence/low-risk drinking over 9 years than heavy drinkers; abstainers had better drinking outcomes than low-risk drinkers. Additionally, among those with interview data, 95% of abstainers and 94% of low-risk drinkers at 6 months were abstinent/low-risk drinkers at 9 years; surprisingly, 89% of heavy drinkers at 6 months were also abstinent/low-risk drinkers although still significantly fewer than the other groups. Abstainers and low-risk drinkers at 6 months had better psychiatric outcomes, and abstainers had better family/social outcomes than heavy drinkers; medical outcomes did not differ. Low-risk drinkers and abstainers showed no reliable differences across psychosocial measures.ConclusionsThe findings suggest that a low-risk drinking outcome may be reasonable over the long-term for some alcohol-dependent individuals receiving addiction treatment.

ObjectivesWe examined prevalence of major medical conditions and extent of disease burden among patients with and without substance use disorders (SUDs) in an integrated health care system serving 3.8 million members.MethodsMedical conditions and SUDs were extracted from electronic health records in 2010. Patients with SUDs (n = 45,461; alcohol, amphetamine, barbiturate, cocaine, hallucinogen, and opioid) and demographically matched patients without SUDs (n = 45,461) were compared on the prevalence of 19 major medical conditions. Disease burden was measured as a function of 10-year mortality risk using the Charlson Comorbidity Index. P-values were adjusted using Hochberg's correction for multiple-inference testing within each medical condition category.ResultsThe most frequently diagnosed SUDs in 2010 were alcohol (57.6%), cannabis (14.9%), and opioid (12.9%). Patients with these SUDs had higher prevalence of major medical conditions than non-SUD patients (alcohol use disorders, 85.3% vs 55.3%; cannabis use disorders, 41.9% vs 23.0%; and opioid use disorders, 44.9% vs 26.1%; all P

ObjectiveIndividuals with behavioral health conditions (BHCs) smoke at high rates and have limited success with quitting, despite impressive gains in recent decades in reducing the overall prevalence of smoking in the United States. This study examined smoking disparities among individuals with BHCs within an integrated health care delivery system with convenient access to tobacco treatments.MethodsThe sample consisted of patients in an integrated health care delivery system in 2010-a group (N=155,733) with one or more of the five most prevalent BHCs (depressive disorders, anxiety disorders, substance use disorders, bipolar and related disorders, and attention-deficit hyperactivity disorder) and a group (N=155,733) without BHCs who were matched on age, sex, and medical home facility. The odds of smoking among patients with BHCs versus without BHCs were examined over four years using logistic regression generalized estimating equation models. Tobacco cessation medication utilization among a subset of smokers in 2010 was also examined.ResultsAlthough smoking prevalence decreased from 2010 to 2013 overall, the likelihood of smoking decreased significantly more slowly among patients with BHCs compared with patients without BHCs (p

ObjectiveTo examine the point prevalence of behavioral health conditions (BHCs) and co-occurring chronic medical conditions among adolescents in an integrated health system.MethodThe sample consisted of adolescents in an integrated health care system diagnosed with at least 1 of the 5 most prevalent BHCs in 2014 (n = 30,643), and patients without a BHC matched on age, sex, and medical home facility (n = 30,643). Electronic health record data was used to identify all adolescents aged 11 to 18 years with at least 1 BHC diagnosis on their diagnosis list, which included current and pre-existing diagnoses from an outpatient (including psychiatry and chemical dependency specialty treatment), inpatient, or emergency department visit at a Kaiser Permanente Northern California (KPNC) facility between January 1, 2014, and December 31, 2014. The odds of having general medical conditions and specific chronic diseases were compared between adolescents with and without BHCs.ResultsAmong adolescents with at least 1 BHC in 2014, the 5 most common BHCs were: depressive disorders (42%), anxiety disorders (40%), attention-deficit/hyperactivity disorders (ADHDs; 37%), substance use disorders (SUDs; 10%), and bipolar spectrum disorders (8%). Overall, patients with a BHC did not have higher odds of any medical comorbidity compared with non-BHC patients. However, compared to individuals without BHCs, adolescents with depression (odds ratio [OR] = 1.16, 95% CI = 1.08-1.26), anxiety (OR = 1.30, 95% CI = 1.20-1.41), and substance use (OR = 1.25, 95% CI = 1.05-1.49) disorders had significantly higher odds of any medical comorbidities; individuals with ADHD and bipolar disorder did not differ from patients without BHCs.ConclusionBHCs were common and were associated with a disproportionately higher burden of chronic medical disease among adolescents in a large, private health care delivery system. As comorbidity can lead to elevated symptom burden, functional impairment, and treatment complexity, the study findings call for implementation of effective collaborative models of care for these patients.

ImportanceEarly intervention for substance use is critical to improving adolescent outcomes. Studies have found promising results for Screening, Brief Intervention, and Referral to Treatment (SBIRT), but little research has examined implementation.ObjectiveTo compare SBIRT implementation in pediatric primary care among trained pediatricians, pediatricians working in coordination with embedded behavioral health care practitioners (BHCPs), and usual care (UC).Design, setting, and participantsThe study is a 2-year (November 1, 2011, through October 31, 2013), nonblinded, cluster randomized, hybrid implementation and effectiveness trial examining SBIRT implementation outcomes across 2 modalities of implementation and UC. Fifty-two pediatricians from a large general pediatrics clinic in an integrated health care system were randomized to 1 of 3 SBIRT implementation arms; patients aged 12 to 18 years were eligible.InterventionsTwo modes of SBIRT implementation, (1) pediatrician only (pediatricians trained to provide SBIRT) and (2) embedded BHCP (BHCP trained to provide SBIRT), and (3) UC.Main outcomes and measuresImplementation of SBIRT (primary outcome), which included assessments, brief interventions, and referrals to specialty substance use and mental health treatment.ResultsThe final sample included 1871 eligible patients among 47 pediatricians; health care professional characteristics did not differ across study arms. Patients in the pediatrician-only (adjusted odds ratio [AOR], 10.37; 95% CI, 5.45-19.74; P < .001) and the embedded BHCP (AOR, 18.09; 95% CI, 9.69-33.77; P < .001) arms had higher odds of receiving brief interventions compared with patients in the UC arm. Patients in the embedded BHCP arm were more likely to receive brief interventions compared with those in the pediatrician-only arm (AOR, 1.74; 95% CI, 1.31-2.31; P < .001). The embedded BHCP arm had lower odds of receiving a referral compared with the pediatrician-only (AOR, 0.58; 95% CI, 0.43-0.78; P < .001) and UC (AOR, 0.65; 95% CI, 0.48-0.89; P = .006) arms; odds of referrals did not differ between the pediatrician-only and UC arms.Conclusions and relevanceThe intervention arms had better screening, assessment, and brief intervention rates than the UC arm. Patients in the pediatrician-only and UC arms had higher odds of being referred to specialty treatment than those in the embedded BHCP arm, suggesting lingering barriers to having pediatricians fully address substance use in primary care. Findings also highlight age and ethnic groups less likely to receive these important services.Trial registrationClinicaltrials.gov Identifier: NCT02408952.

ObjectiveThe objective was to examine prevalence of behavioral health disorders (BHDs) and co-occurring chronic medical conditions in a 3.4 million-member integrated health system.MethodClinical databases identified 255,993 patients diagnosed with the most prevalent BHDs (cases): depression, anxiety, substance use, bipolar spectrum and attention deficit and hyperactivity (ADHD); non-BHD matched controls were created for all unique cases. Cases and controls were compared for prevalence of general medical conditions and specific chronic diseases and the Charlson Comorbidity Index (CMI).ResultsThe five most common BHDs were depression (58%), anxiety (42%), substance use (16%), bipolar spectrum (6%) and ADHD (4%). Compared to controls, patients with depression (80.1% vs. 66.3%), anxiety (78.0% vs. 63.0%), substance use (74.0% vs. 59.9%), bipolar (75.3% vs. 60.7%) and ADHD (60.6% vs. 53.1%; all P

BackgroundLower-risk drinking is increasingly being examined as a treatment outcome for some patients following addiction treatment. However, few studies have examined the relationship between drinking status (lower-risk drinking in particular) and healthcare utilization and cost, which has important policy implications.MethodsParticipants were adults with alcohol dependence and/or abuse diagnoses who received outpatient alcohol and other drug treatment in a private, nonprofit integrated healthcare delivery system and had a follow-up interview 6 months after treatment entry (N = 995). Associations between past 30-day drinking status at 6 months (abstinence, lower-risk drinking defined as nonabstinence and no days of 5+ drinking, and heavy drinking defined as 1 or more days of 5+ drinking) and repeated measures of at least 1 emergency department (ED), inpatient or primary care visit, and their costs over 5 years were examined using mixed-effects models. We modeled an interaction between time and drinking status to examine trends in utilization and costs over time by drinking group.ResultsHeavy drinkers and lower-risk drinkers were not significantly different from the abstainers in their cost or utilization at time 0 (i.e., 6 months postintake). Heavy drinkers had increasing odds of inpatient (p

BackgroundTreatment for alcohol disorders has traditionally been abstinence-oriented, but evaluating the merits of a low-risk drinking outcome as part of a primary treatment endpoint is a timely issue given new pertinent regulatory guidelines. This study explores a posttreatment low-risk drinking outcome as a predictor of future drinking and problem severity outcomes among individuals with alcohol use disorders in a large private, not for profit, integrated care health plan.MethodsStudy participants include adults with alcohol use disorders at 6 months (N = 995) from 2 large randomized studies. Logistic regression models were used to explore the relationship between past 30-day drinker status at 6 months posttreatment (abstinent [66%], low-risk drinking [14%] defined as nonabstinence and no days of 5+ drinking, and heavy drinking [20%] defined as 1 or more days of 5+ drinking) and 12-month outcomes, including drinking status and Addiction Severity Index measures of medical, psychiatric, family/social, and employment severity, controlling for baseline covariates.ResultsCompared to heavy drinkers, abstinent individuals and low-risk drinkers at 6 months were more likely to be abstinent or low-risk drinkers at 12 months (adj. ORs = 16.7 and 3.4, respectively; p < 0.0001); though, the benefit of abstinence was much greater than that of low-risk drinking. Compared to heavy drinkers, abstinent and low-risk drinkers were similarly associated with lower 12-month psychiatric severity (adj. ORs = 1.8 and 2.2, respectively, p < 0.01) and family/social problem severity (adj. OR = 2.2; p < 0.01). While abstinent individuals had lower 12-month employment severity than heavy drinkers (adj. OR = 1.9; p < 0.01), low-risk drinkers did not differ from heavy drinkers. The drinking groups did not differ on 12-month medical problem severity.ConclusionsCompared to heavy drinkers, low-risk drinkers did as well as abstinent individuals for many of the outcomes important to health and addiction policy. Thus, an endpoint that allows low-risk drinking may be tenable for individuals undergoing alcohol specialty treatment.

BackgroundTreatment for alcohol disorders has traditionally been abstinence-oriented, but evaluating the merits of a low-risk drinking outcome as part of a primary treatment endpoint is a timely issue given new pertinent regulatory guidelines. This study explores a posttreatment low-risk drinking outcome as a predictor of future drinking and problem severity outcomes among individuals with alcohol use disorders in a large private, not for profit, integrated care health plan.MethodsStudy participants include adults with alcohol use disorders at 6 months (N = 995) from 2 large randomized studies. Logistic regression models were used to explore the relationship between past 30-day drinker status at 6 months posttreatment (abstinent [66%], low-risk drinking [14%] defined as nonabstinence and no days of 5+ drinking, and heavy drinking [20%] defined as 1 or more days of 5+ drinking) and 12-month outcomes, including drinking status and Addiction Severity Index measures of medical, psychiatric, family/social, and employment severity, controlling for baseline covariates.ResultsCompared to heavy drinkers, abstinent individuals and low-risk drinkers at 6 months were more likely to be abstinent or low-risk drinkers at 12 months (adj. ORs = 16.7 and 3.4, respectively; p < 0.0001); though, the benefit of abstinence was much greater than that of low-risk drinking. Compared to heavy drinkers, abstinent and low-risk drinkers were similarly associated with lower 12-month psychiatric severity (adj. ORs = 1.8 and 2.2, respectively, p < 0.01) and family/social problem severity (adj. OR = 2.2; p < 0.01). While abstinent individuals had lower 12-month employment severity than heavy drinkers (adj. OR = 1.9; p < 0.01), low-risk drinkers did not differ from heavy drinkers. The drinking groups did not differ on 12-month medical problem severity.ConclusionsCompared to heavy drinkers, low-risk drinkers did as well as abstinent individuals for many of the outcomes important to health and addiction policy. Thus, an endpoint that allows low-risk drinking may be tenable for individuals undergoing alcohol specialty treatment.

BackgroundThis study examined stability of remission in patients who were abstainers and non-problem users at 1-year after entering private, outpatient alcohol and drug treatment. We examined: (a) How does risk of relapse change over time? (b) What was the risk of relapse for non-problem users versus abstainers? (c) What individual, treatment, and extra-treatment characteristics predicted time to relapse, and did these differ by non-problem use versus abstinence?MethodsThe sample consisted of 684 adults in remission (i.e., abstainers or non-problem users) 1 year following treatment intake. Participants were interviewed at intake, and 1, 5, 7, 9, and 11 years after intake. We used discrete-time survival analysis to examine when relapse is most likely to occur and predictors of relapse.ResultsRelapse was most likely at 5-year, and least likely at 11-year follow-up. Non-problem users had twice the odds of relapse compared to abstainers. Younger individuals and those with fewer 12-step meetings and shorter index treatment had higher odds of relapse than others. We found no significant interactions between non-problem use and the other covariates suggesting that significant predictors of outcome did not differ for non-problem users.ConclusionsNon-problem use is not an optimal 1-year outcome for those in an abstinence-oriented, heterogeneous substance use treatment program. Future research should examine whether these results are found in harm reduction treatment and self-help models, or in those with less severe problems. Results suggest treatment retention and 12-step participation are prognostic markers of long-term positive outcomes for those achieving remission at 1 year.

Abstract Objective This paper used data from a study of pediatric primary care provider (PCP) screening practices to examine barriers to and facilitators of adolescent alcohol and other drug (AOD) screening in pediatric primary care. Methods A web-based survey (N = 437) was used to examine the influence of PCP factors (attitudes and knowledge, training, self-efficacy, comfort with alcohol and drug issues); patient characteristics (age, gender, ethnicity, comorbidities and risk factors); and organizational factors (screening barriers, staffing resources, confidentiality issues) on AOD screening practices. Self-reported and electronic medical record (EMR)-recorded screening rates were also assessed. Results More PCPs felt unprepared to diagnose alcohol abuse (42%) and other drug abuse (56%) than depression (29%) (p

BackgroundThe treatment of alcohol and other drugs is now more commonly framed in terms of a chronic condition which requires ongoing monitoring. A model which includes continuing access to health care may optimize outcomes. Most studies of chronic care models have not included health care and have only examined short term effects.MethodsThe sample (n = 783) included consecutive admissions in ten public and private alcohol and other drug (AOD) treatment programs followed over seven years. The outcome was remission which was defined as alcohol and drug abstinence or non-problem use.ResultsIn the private sample, receiving health care services predicted remission across the seven years; however this did not occur in the public sample. More patients in the public treatment sample received AOD treatment readmissions each year, while more of those in the private sector received psychiatric and general health visits. Except for drug problem severity, there were no other clinical differences between the samples. There were no differences in the proportions of patients in the two sectors who received the full spectrum of chronic care services. In the final models, 12-step participation was markedly significant for both samples.ConclusionsModels of chronic care for substance use need to consider differences between private and public treatment and should take into account that individuals may not always have access, or avail themselves of services that may optimize long-term outcomes.

BackgroundElectronic health record (EHR)–based disease registries have aided health care professionals and researchers in increasing their understanding of chronic illnesses, including identifying patients with (or at risk of developing) conditions and tracking treatment progress and recovery. Despite excessive alcohol use being a major contributor to the global burden of disease and disability, no registries of alcohol problems exist. EHR-based data in Kaiser Permanente Northern California (KPNC), an integrated health system that conducts systematic alcohol screening, which provides specialty addiction medicine treatment internally and has a membership of over 4 million members that are highly representative of the US population with access to care, provide a unique opportunity to develop such a registry. ObjectiveOur objectives were to describe the development and implementation of a protocol for assembling the KPNC Adult Alcohol Registry, which may be useful to other researchers and health systems, and to characterize the registry cohort descriptively, including underlying health conditions. MethodsInclusion criteria were adult members with unhealthy alcohol use (using National Institute on Alcohol Abuse and Alcoholism guidelines), an alcohol use disorder (AUD) diagnosis, or an alcohol-related health problem between June 1, 2013, and May 31, 2019. We extracted patients’ longitudinal, multidimensional EHR data from 1 year before their date of eligibility through May 31, 2019, and conducted descriptive analyses. ResultsWe identified 723,604 adult patients who met the registry inclusion criteria at any time during the study period: 631,780 with unhealthy alcohol use, 143,690 with an AUD diagnosis, and 18,985 with an alcohol-related health problem. We identified 65,064 patients who met two or more criteria. Of the 4,973,195 adult patients with at least one encounter with the health system during the study period, the prevalence of unhealthy alcohol use was 13% (631,780/4,973,195), the prevalence of AUD diagnoses was 3% (143,690/4,973,195), and the prevalence of alcohol-related health problems was 0.4% (18,985/4,973,195). The registry cohort was 60% male (n=432,847) and 41% non-White (n=295,998) and had a median age of 41 years (IQR=27). About 48% (n=346,408) had a chronic medical condition, 18% (n=130,031) had a mental health condition, and 4% (n=30,429) had a drug use disorder diagnosis. ConclusionsWe demonstrated that EHR-based data collected during clinical care within an integrated health system could be leveraged to develop a registry of patients with alcohol problems that is flexible and can be easily updated. The registry’s comprehensive patient-level data over multiyear periods provides a strong foundation for robust research addressing critical public health questions related to the full course and spectrum of alcohol problems, including recovery, which would complement other methods used in alcohol research (eg, population-based surveys, clinical trials).