A patient activation intervention in primary care for patients with chronic pain on long term opioid therapy: results from a randomized control trial.

BACKGROUND: Given significant risks associated with long-term prescription opioid use, there is a need for non-pharmacological interventions for treating chronic pain. Activating patients to manage chronic pain has the potential to improve health outcomes. The ACTIVATE study was designed to evaluate the effectiveness of a 4-session patient activation intervention in primary care for patients on long-term opioid therapy. METHODS: The two-arm, pragmatic, randomized trial was conducted in two primary care clinics in an integrated health system from June 2015-August 2018. Consenting participants were randomized to the intervention (n = 189) or usual care (n = 187). Participants completed online and interviewer-administered surveys at baseline, 6- and 12- months follow-up. Prescription opioid use was extracted from the EHR. The primary outcome was patient activation assessed by the Patient Activation Measure (PAM). Secondary outcomes included mood, function, overall health, non-pharmacologic pain management strategies, and patient portal use. We conducted a repeated measure analysis and reported between-group differences at 12 months. RESULTS: At 12 months, the intervention and usual care arms had similar PAM scores. However, compared to usual care at 12 months, the intervention arm demonstrated: less moderate/severe depression (odds ratio [OR] = 0.40, 95%CI 0.18-0.87); higher overall health (OR = 3.14, 95%CI 1.64-6.01); greater use of the patient portal's health/wellness resources (OR = 2.50, 95%CI 1.42-4.40) and lab/immunization history (OR = 2.70, 95%CI 1.29-5.65); and greater use of meditation (OR = 2.72; 95%CI 1.61-4.58) and exercise/physical therapy (OR = 2.24, 95%CI 1.29-3.88). At 12 months, the intervention arm had a higher physical health measure (mean difference 1.63; 95%CI: 0.27-2.98). CONCLUSION: This trial evaluated the effectiveness of a primary care intervention in improving patient activation and patient-reported outcomes among adults with chronic pain on long-term opioid therapy. Despite a lack of improvement in patient activation, a brief intervention in primary care can improve outcomes such as depression, overall health, non-pharmacologic pain management, and engagement with the health system. TRIAL REGISTRATION: The study was registered on 10/27/14 on ClinicalTrials.gov (NCT02290223).

Patient and provider factors associated with receipt and delivery of brief interventions for unhealthy alcohol use in primary care.

BACKGROUND: Unhealthy alcohol use is a serious and costly public health problem. Alcohol screening and brief interventions are effective in reducing unhealthy alcohol consumption. However, rates of receipt and delivery of brief interventions vary significantly across healthcare settings, and relatively little is known about the associated patient and provider factors. METHODS: This study examines patient and provider factors associated with the receipt of brief interventions for unhealthy alcohol use in an integrated healthcare system, based on documented brief interventions in the electronic health record. Using multilevel logistic regression models, we retrospectively analyzed 287,551 adult primary care patients (and their 2952 providers) who screened positive for unhealthy drinking between 2014 and 2017. RESULTS: We found lower odds of receiving a brief intervention among patients exceeding daily or weekly drinking limits (vs. exceeding both limits), females, older age groups, those with higher medical complexity, and those already diagnosed with alcohol use disorders. Patients with other unhealthy lifestyle activities (e.g., smoking, no/insufficient exercise) were more likely to receive a brief intervention. We also found that female providers and those with longer tenure in the health system were more likely to deliver brief interventions. CONCLUSIONS: These findings point to characteristics that can be targeted to improve universal receipt of brief intervention.

Associations Between Psychiatric Disorders and Alcohol Consumption Levels in an Adult Primary Care Population.

BACKGROUND: Unhealthy alcohol use frequently co-occurs with psychiatric disorders; however, little is known about the relationship between psychiatric disorders and alcohol consumption levels. Understanding varying levels of unhealthy alcohol use among individuals with a variety of psychiatric disorders in primary care would provide valuable insight for tailoring interventions. METHODS: We conducted a cross-sectional study of 2,720,231 adult primary care patients screened for unhealthy alcohol use between 2014 and 2017 at Kaiser Permanente Northern California, using electronic health record data. Alcohol consumption level was classified as no reported use, low-risk use, and unhealthy use, per National Institute on Alcohol Abuse and Alcoholism guidelines. Unhealthy use was further differentiated into mutually exclusive groups: exceeding only daily limits, exceeding only weekly limits, or exceeding both daily and weekly limits. Multivariable multinomial logistic regression models were fit to examine associations between 8 past-year psychiatric disorders (depression, bipolar disorder, anxiety disorder, obsessive-compulsive disorder, schizophrenia, schizoaffective disorder, anorexia nervosa, and bulimia nervosa) and alcohol consumption levels, adjusting for sociodemographic and health characteristics. RESULTS: In the full sample [53% female, 48% White, mean (SD) age = 46 (18) years], patients with psychiatric disorders (except eating disorders), compared to those without, had lower odds of reporting low-risk and unhealthy alcohol use relative to no use. Among patients who reported any alcohol use (n = 861,427), patients with depression and anxiety disorder, compared to those without, had higher odds of exceeding only weekly limits and both limits; patients with bulimia nervosa were also more likely to exceed both limits. CONCLUSIONS: Findings suggest that patients with anxiety disorder, depression, and bulimia nervosa who drink alcohol are more likely to exceed recommended limits, increasing risk of developing more serious problems. Health systems and clinicians may wish to consider implementing more robust screening, assessment, and intervention approaches to support these vulnerable subgroups in limiting their drinking.

Patient characteristics associated with treatment initiation and engagement among individuals diagnosed with alcohol and other drug use disorders in emergency department and primary care settings.

Background: Treatment initiation and engagement rates for alcohol and other drug (AOD) use disorders differ depending on where the AOD use disorder was identified. Emergency department (ED) and primary care (PC) are 2 common settings where patients are identified; however, it is unknown whether characteristics of patients who initiate and engage in treatment differ between these settings. Methods: Patients identified with an AOD disorder in ED or PC settings were drawn from a larger study that examined Healthcare Effectiveness Data and Information Set (HEDIS) AOD treatment initiation and engagement measures across 7 health systems using electronic health record data (n = 54,321). Multivariable generalized linear models, with a logit link, clustered on health system, were used to model patient factors associated with initiation and engagement in treatment, between and within each setting. Results: Patients identified in the ED had higher odds of initiating treatment than those identified in PC (adjusted odds ratio [aOR] = 1.89, 95% confidence interval [CI] = 1.73-2.07), with no difference in engagement between the settings. Among those identified in the ED, compared with patients aged 18-29, older patients had higher odds of treatment initiation (age 30-49: aOR = 1.25, 95% CI = 1.12-1.40; age 50-64: aOR = 1.42, 95% CI = 1.26-1.60; age 65+: aOR = 1.27, 95% CI = 1.08-1.49). However, among those identified in PC, compared with patients aged 18-29, older patients were less likely to initiate (age 30-49: aOR = 0.81, 95% CI = 0.71-0.94; age 50-64: aOR = 0.68, 95% CI = 0.58-0.78; age 65+: aOR = 0.47, 95% CI = 0.40-0.56). Women identified in ED had lower odds of initiating treatment (aOR = 0.80, 95% CI = 0.72-0.88), whereas sex was not associated with treatment initiation in PC. In both settings, patients aged 65+ had lower odds of engaging compared with patients aged 18-29 (ED: aOR = 0.61, 95% CI = 0.38-0.98; PC: aOR = 0.42, 95% CI = 0.26-0.68). Conclusion: Initiation and engagement in treatment differed by sex and age depending on identification setting. This information could inform tailoring of future AOD interventions.

Psychiatric comorbidity and Healthcare Effectiveness Data and Information Set (HEDIS) measures of alcohol and other drug treatment initiation and engagement across 7 health care systems.

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.

The association between medical comorbidity and Healthcare Effectiveness Data and Information Set (HEDIS) measures of treatment initiation and engagement for alcohol and other drug use disorders.

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.

Factors associated with Healthcare Effectiveness Data and Information Set (HEDIS) alcohol and other drug measure performance in 2014-2015.

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.

Predictors of Healthcare Effectiveness Data and Information Set (HEDIS) treatment initiation and engagement among patients with opioid use disorder across 7 health systems.

Background: The prevalence of opioid use disorder (OUD) has increased rapidly in the United States and improving treatment access is critical. Among patients with OUD, we examined factors associated with the Healthcare Effectiveness Data and Information Set (HEDIS) performance measures of alcohol and other drug (AOD) treatment initiation and engagement. Methods: Electronic health record and claims data between October 1, 2014, and August 15, 2015, from 7 health systems were used to identify patients (n = 11,490) with a new index OUD diagnosis (no AOD diagnosis prior <60 days) based on International Classification of Diseases (ICD)-9 codes. Multivariable generalized linear models with a logit link clustered on health system were used to examine the associations of patient demographic and clinical characteristics, and department of index diagnosis, with HEDIS measures of treatment initiation and engagement. Results: The prevalence of OUD among all AOD diagnoses varied across health systems, as did rates of AOD initiation (5.7%-21.6%) and engagement (7.6%-24.6%). Those diagnosed in the emergency department (adjusted odds ratio [aOR] = 1.58, 95% confidence interval [CI] = 1.27,1.97) or psychiatry/AOD treatment (aOR = 2.92, 95% CI = 2.47,3.46) were more likely to initiate treatment compared with primary care. Older patients were less likely to initiate (age 50-64 vs. age 18-29: aOR = 0.42, 95% CI = 0.35, 0.51; age 65+ vs. age 18-29: aOR = 0.34, 95% CI = 0.26, 0.43), as were women (aOR = 0.72, 95% CI = 0.62, 0.85). Patients diagnosed in psychiatry/AOD treatment (aOR = 2.67, 95% CI = 1.98, 3.60) compared with primary care were more likely to engage in treatment. Those identified in an inpatient setting (aOR = 0.19, 95% CI = 0.14, 0.27 vs. primary care), those with medical comorbidity (aOR = 0.70, 95% CI = 0.52, 0.95), and older patients (age 50-64 vs. 18-29: aOR = 0.64, 95% CI = 0.46, 0.88; age 65+ vs. 18-29: aOR = 0.36, 95% CI = 0.22, 0.57) were less likely to engage in treatment. Conclusions: Rates of initiation and engagement for OUD patients vary widely with noticeable room for improvement, particularly in this critical time of the opioid crisis. Targeting patient and system factors may improve health system performance, which is key to improving patient outcomes.

Healthcare Effectiveness Data and Information Set (HEDIS) measures of alcohol and drug treatment initiation and engagement among people living with the human immunodeficiency virus (HIV) and patients without an HIV diagnosis.

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.

The prevalence of Healthcare Effectiveness Data and Information Set (HEDIS) initiation and engagement in treatment among patients with cannabis use disorders in 7 US health systems.

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.

Alcohol, marijuana, and opioid use disorders: 5-Year patterns and characteristics of emergency department encounters.

BACKGROUND: Changes 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. METHODS: In 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. RESULTS: Odds 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). CONCLUSIONS: ED 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.

Posttreatment Low-Risk Drinking as a Predictor of Future Drinking and Problem Outcomes Among Individuals with Alcohol Use Disorders: A 9-Year Follow-Up.

BACKGROUND: Treatment 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. METHODS: Study 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%). RESULTS: Abstainers 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. CONCLUSIONS: The findings suggest that a low-risk drinking outcome may be reasonable over the long-term for some alcohol-dependent individuals receiving addiction treatment.

Trajectories of remission and mortality over 13 years after intake to substance use treatment.

BACKGROUND: Little is known about the relationships between long-term patterns of substance use and mortality risk among substance use disorder (SUD) patients. OBJECTIVE: To determine distinct patterns of remission and relapse of SUD over time and examine their relationship with mortality. METHODS: The study site was Kaiser Permanente of Northern California. Data for 997 adults who entered substance use treatment between 1994 and 1996 and 4,241 non-SUD patients with similar demographic distributions (35% women in both groups) were analyzed. Latent class growth analysis identified distinct remission trajectory groups over 13 years among SUD patients, and survival analyses were conducted to examine the risk of death between remission trajectory groups, and SUD and non-SUD patients within each remission trajectory group. RESULTS: Three distinct remission trajectory groups were identified among SUD patients: 1) early relapse-low remission probabilities; 2) declining remission-decreasing remission probabilities; and 3) stable remission-stable remission probabilities across all time points. Among the SUD patients, the early relapse group had a higher risk of death than those stably remitted; stable and declining remission groups did not differ. Comparisons within each remission trajectory group showed that SUD patients in the early relapse and stable remission groups had higher risks of death compared with non-SUD patients; there were no differences within the declining group. CONCLUSIONS: SUD patients in the stable remission group had lower survival rates compared with non-SUD patients. These findings underline the importance of continuously addressing healthcare needs of individuals with SUD, even in the presence of long-term remission.

Alcohol and Drug Use and Aberrant Drug-Related Behavior Among Patients on Chronic Opioid Therapy.

OBJECTIVE: To better identify individuals on chronic opioid therapy (COT) at high risk for aberrant-drug related behavior (ADRB). We examine whether patients with low level alcohol and drug use have similar characteristics to those with alcohol and drug disorders. We then examined the relationship of alcohol and drug use to ADRBs among COT patients. METHODS: The sample was 972 randomly selected COT patients (age 21-80 years old) from a large health system in Northern California, USA, and interviewed in 2009. Logistic regression models were used to model the dependent variables of: alcohol use, illicit drug use, alcohol disorders, illicit drug disorders, and ADRBs. RESULTS: The odds of daily/weekly alcohol use were lower for those with a high daily opioid dose (120+ mg/day vs. <20 mg/day) (OR = 0.32, p < 0.010). Illicit drug disorders were associated with depression (OR = 2.31, p < .001) and being on a high daily opioid dose (OR = 5.51, p < .01). Participants with illicit drug use had higher odds of giving (OR = 2.57, p < 0.01) and receiving opioids from friends or family (OR = 3.25, p < 0.001), but disorder diagnoses were not associated with ADRBs. CONCLUSIONS: Findings reinforce that illicit drug use should be of high concern to clinicians prescribing opioids, and suggest it should be considered separately from alcohol use and alcohol disorders in the evaluation of ADRBs. Frequent alcohol use is low, but not uncommon, and suggests a need to discuss specific issues regarding safe use of opioids among persons who use alcohol that may differ from their risk of drug use.

Five-year healthcare utilization and costs among lower-risk drinkers following alcohol treatment.

BACKGROUND: Lower-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. METHODS: Participants 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. RESULTS: Heavy 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 < 0.01) and ED (p < 0.05) utilization over 5 years compared with abstainers. Lower-risk drinkers and abstainers did not significantly differ in their service use in any category over time. No differences were found in changes in primary care use among the 3 groups over time. The cost analyses paralleled the utilization results. Heavy drinkers had increasing ED (p < 0.05) and inpatient (p < 0.001) costs compared with the abstainers; primary care costs did not significantly differ. Lower-risk drinkers did not have significantly different medical costs compared with those who were abstinent over 5 years. However, post hoc analyses found lower-risk drinkers and heavy drinkers to not significantly differ in their ED use or costs over time. CONCLUSIONS: Performance measures for treatment settings that consider treatment outcomes may need to take into account both abstinence and reduction to nonheavy drinking. Future research should examine whether results are replicated in harm reduction treatment, or whether such outcomes are found only in abstinence-based treatment.

Racial and ethnic disparities in receipt of specialty treatment across risk profiles of adults with heavy alcohol use.

BACKGROUND: Variation in specialty treatment utilization for alcohol use disorder (AUD) by patient subgroups is poorly understood. This study examined whether and how patient risk profiles predict receipt of specialty treatment and whether there are disparities by race and ethnicity. METHODS: This cohort study included 206,956 adults with heavy alcohol use (that which exceeded National Institute on Alcohol Abuse and Alcoholism guidelines) between June 1, 2013 and December 31, 2014, using electronic health record data from Kaiser Permanente Northern California. Five risk profiles (characterized by daily or weekly heavy drinking and level of health risks) were identified in latent class analysis. Logistic regression models were fit to examine associations between risk profiles, race, ethnicity, and receipt of specialty treatment (including addiction medicine, psychiatry, or integrated behavioral health visits, and AUD pharmacotherapy), adjusting for other patient characteristics. Variation in the association between risk profiles and receipt of specialty treatment by race/ethnicity was also examined. RESULTS: Overall, 4.0% of patients received specialty treatment. Latino/Hispanic and Asian/Pacific Islander patients had lower odds of receiving specialty treatment than White patients (adjusted odds ratio [aOR] [95% CI] = 0.80 [0.75, 0.85], and 0.64 [0.59, 0.70], respectively). The substance use disorder and mental health disorder (SUD/MH) risk profile had the highest odds of receiving specialty treatment (10.46 [9.65, 11.34]). Associations between risk profiles and receipt of specialty treatment significantly differed by race/ethnicity. Black patients in the SUD/MH risk profile, and Hispanic/Latino patients in the risk profile with heavy daily drinking and more health risks, had lower odds of receiving specialty treatment than their White counterparts (adjusted ratio of odds ratios [aROR] [95% CI] = 0.69 [0.50, 0.94], and 0.79 [0.67, 0.92], respectively). CONCLUSIONS: This study provides new insights into racial/ethnic disparities in specialty treatment utilization for alcohol problems. Findings may help inform strategies for tailoring interventions to address heavy alcohol use.

Adolescent utilization of eating disorder higher level of care: roles of family-based treatment adherence and demographic factors.

BACKGROUND: Outpatient family-based treatment (FBT) is effective in treating restrictive eating disorders among adolescents. However, little is known about whether FBT reduces higher level of care (HLOC) utilization or if utilization of HLOC is associated with patient characteristics. This study examined associations between utilization of eating disorder related care (HLOC and outpatient treatment) and reported adherence to FBT and patient characteristics in a large integrated health system. METHODS: This retrospective cohort study examined 4101 adolescents who received care for restrictive eating disorders at Kaiser Permanente Northern California. A survey was sent to each medical center to identify treatment teams as high FBT adherence (hFBT) and low FBT adherence (lFBT). Outpatient medical and psychiatry encounters and HLOC, including medical hospitalizations and higher-level psychiatric care as well as patient characteristics were extracted from the EHR and examined over 12 months post-index. RESULTS: 2111 and 1990 adolescents were treated in the hFBT and lFBT, respectively. After adjusting for age, sex, race/ethnicity, initial percent median BMI, and comorbid mental health diagnoses, there were no differences in HLOC or outpatient utilization between hFBT and lFBT. Females had higher odds of any utilization compared with males. Compared to White adolescents, Latinos/Hispanics had lower odds of HLOC utilization. Asian, Black, and Latino/Hispanic adolescents had lower odds of psychiatric outpatient care than Whites. CONCLUSIONS: Reported FBT adherence was not associated with HLOC utilization in this sample. However, significant disparities across patient characteristics were found in the utilization of psychiatric care for eating disorders. More efforts are needed to understand treatment pathways that are accessible and effective for all populations with eating disorders.

Adolescents with restrictive eating treated by Family-Based Treatment (FBT) teams had better early weight gain but no differences in the use of intensive outpatient, residential, partial hospital programs or inpatient psychiatry care when compared to those treated by teams with a low adherence to the FBT approach. Factors such as sex, race, ethnicity, mood disorders, and suicidality were associated with the use of psychiatric services. These findings are consistent with previously documented systematic disparities in accessing psychiatric services across patient demographics and should be used to inform the development of proposed care models that are more inclusive and accessible to all patients.

Unhealthy Alcohol Use among Adults with Depression or Anxiety: Changes During COVID-19 and Associations with Mental Health Treatment.

OBJECTIVE: Individuals 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. METHODS: Using 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. RESULTS: The 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. CONCLUSIONS: Contrary 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.

Posttreatment low-risk drinking as a predictor of future drinking and problem outcomes among individuals with alcohol use disorders.

BACKGROUND: Treatment 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. METHODS: Study 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. RESULTS: Compared 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. CONCLUSIONS: Compared 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.

Risk profiles of adults with heavy alcohol use: Drinking patterns, behavioral and metabolic factors, health problems, and racial and ethnic disparities.

BACKGROUND: Heavy alcohol use is a growing risk factor for chronic disease, yet little is known about its co-occurrence with other risk factors and health problems. This study aimed to identify risk profiles of adults with heavy alcohol use and examined potential disparities by race and ethnicity. METHODS: This cross-sectional study included 211,333 adults with heavy alcohol use (in excess of daily or weekly limits recommended by National Institute on Alcohol Abuse and Alcoholism) between June 1, 2013 and December 31, 2014 in Kaiser Permanente Northern California. Latent class analysis was used to examine how heavy drinking patterns clustered with other behavioral and metabolic risk factors and health problems to form risk profiles. Multinomial logistic regression models were fit to examine associations between race, ethnicity, and risk profiles. RESULTS: A 5-class model was selected as best fitting the data and representing clinically meaningful risk profiles: (1) "heavy daily drinking and lower health risks" (DAILY, 44.3%); (2) "substance use disorder and mental health disorder" (SUD/MH, 2.3%); (3) "heavy weekly drinking and lower health risks" (WEEKLY, 19.6%); (4) "heavy daily drinking and more health risks" (DAILY-R, 18.5%); (5) "heavy weekly drinking and more health risks" (WEEKLY-R, 15.3%). American Indian or Alaska Native (AIAN) and Black patients had higher odds than White patients of being in the SUD/MH, DAILY-R, and WEEKLY-R profiles than the DAILY profile. AIAN, Black, and Latino/Hispanic patients had higher odds than White patients of being in the SUD/MH, DAILY-R, and WEEKLY-R profiles rather than the WEEKLY profile. CONCLUSIONS: AIAN, Black, and Latino/Hispanic patients with self-reported heavy drinking were more likely to be in risk profiles with greater alcohol consumption, more health risks, and higher morbidity. Targeted, culturally appropriate interventions for heavy alcohol use that may address other modifiable risk factors are needed to work towards health equity.