Discriminative validity of a substance use symptom checklist for moderate-severe DSM-5 cannabis use disorder (CUD) in primary care settings.

Background: The prevalence of cannabis use disorder (CUD) is increasing in the US and primary care providers need tools to identify patients with moderate-severe CUD to facilitate treatment. A single-item screen for cannabis (SIS-C) has outstanding discriminative validity for CUD. However, because the prevalence of moderate-severe CUD is typically low, the probability that an average patient who screens positive for daily cannabis has moderate-severe cannabis use disorder is low, making follow-up assessment important. Methods: This study reports the discriminative validity of a DSM-5 Substance Use Symptom Checklist ("Checklist") for moderate-severe CUD among 498 primary care patients who reported daily cannabis use on the SIS-C. We evaluated the performance of the Checklist (score 0-11) completed during routine care, compared to ≥4 DSM-5 CUD symptoms (moderate-severe CUD) on the Composite International Diagnostic Interview Substance Abuse Module from a confidential survey (reference standard). We estimated areas under receiver operating curve (AUROC), sensitivities, specificities, and post-test probabilities. Results: Of 498 eligible patients, 17 % met diagnostic criteria for moderate-severe CUD. The Checklist's AUROC for moderate-severe CUD was 0.77 (95 % CI: 0.71-0.83), and Checklist scores of 1-2 balanced sensitivity and specificity. Among patients from a population with average prevalence of CUD before screening (~6 % prevalence) and daily use on the SIS-C, a Checklist score of 3 indicated a post-test probability of 82.1 %. Conclusion: Overall performance of the Checklist was good and the high specificity made it useful for identifying patients likely to have moderate-severe CUD among those at average risk.

Association of psychiatric and substance use disorders with cannabis use and cannabis use disorder during early pregnancy in northern California.

AIMS: To estimate the strength of association between psychiatric disorders and substance use disorders (SUD), and cannabis use and cannabis use disorder (CUD) during early pregnancy. DESIGN: Observational study. SETTING: Kaiser Permanente Northern California, USA. PARTICIPANTS: 299 496 pregnancies from 227 555 individuals screened for cannabis use by self-report and a urine toxicology test at entrance to prenatal care in Kaiser Permanente Northern California during January 2011-December 2021 (excepting year 2020). The sample was 62.5% non-White, with a mean (standard deviation) age of 31.1 (5.5) years; 6.8% used cannabis; 0.2% had a CUD. MEASUREMENTS: Exposure variables included electronic health record-based psychiatric diagnoses of attention deficit hyperactivity, anxiety, bipolar, depressive, personality, posttraumatic stress and psychotic disorders; and alcohol, opioid, stimulant and tobacco use disorders, during the two years prior to pregnancy up to the day before the prenatal substance use screening date. Outcome variables were any cannabis use, frequency of self-reported cannabis use and CUD during early pregnancy. FINDINGS: Psychiatric disorder prevalence ranged from 0.2% (psychotic) to 14.3% (anxiety), and SUD ranged from 0.3% (stimulant/opioid) to 3.8% (tobacco). Psychiatric disorders were associated with cannabis use and CUD, with the strongest association for any use found for bipolar disorder (adjusted odds ratio [aOR] = 2.83; 95% confidence interval [CI] = 2.53-3.17) and the strongest association for CUD found for psychotic disorders (aOR = 10.01, 95% CI = 6.52-15.37). SUDs were associated with cannabis use and CUD, with the strongest association for any use found for tobacco use disorder (aOR = 4.03, 95% CI = 3.82-4.24) and the strongest association for CUD found for stimulant use disorder (aOR = 21.99, 95% CI = 16.53-29.26). Anxiety, bipolar, depressive disorders and tobacco use disorder were associated with greater odds of daily than monthly or less cannabis use. CONCLUSIONS: Psychiatric disorders and substance use disorders appear to be associated with elevated odds of any and frequent cannabis use as well as cannabis use disorder during early pregnancy. In most cases, the associations with cannabis outcomes were stronger for substance use disorders than other psychiatric disorders.

Patient Perspectives on Mental Health and Pain Management Support Needed Versus Received During Opioid Deprescribing.

Prescription opioid tapering has increased significantly over the last decade. Evidence suggests that tapering too quickly or without appropriate support may unintentionally harm patients. The aim of this analysis was to understand patients' experiences with opioid tapering, including support received or not received for pain control or mental health. Patients with evidence of opioid tapering from 6 health care systems participated in semi-structured, in-depth interviews; family members of suicide decedents with evidence of opioid tapering were also interviewed. Interviews were analyzed using thematic analysis. Participants included 176 patients and 16 family members. Results showed that 24% of the participants felt their clinicians checked in with them about their taper experiences while 41% reported their clinicians did not. A majority (68%) of individuals who experienced suicide behavior during tapering reported that clinicians did check in about mood and mental health changes specifically; however, 27% of that group reported no such check-in. More individuals reported negative experiences (than positive) with pain management clinics-where patients are often referred for tapering and pain management support. Patients reporting successful tapering experiences named shared decision-making and ability to adjust taper speed or pause tapering as helpful components of care. Fifty-six percent of patients reported needing more support during tapering, including more empathy and compassion (48%) and an individualized approach to tapering (41%). Patient-centered approaches to tapering include reaching out to monitor how patients are doing, involving patients in decision-making, supporting mental health changes, and allowing for flexibility in the tapering pace. PERSPECTIVE: Patients tapering prescription opioids desire more provider-initiated communication including checking in about pain, setting expectations for withdrawal and mental health-related changes, and providing support for mental health. Patients preferred opportunities to share decisions about taper speed and to have flexibility with pausing the taper as needed.

Comparing Cannabis Use for Pain to Use for Other Reasons in Primary Care Patients.

BACKGROUND: Medical cannabis is commonly used for chronic pain, but little is known about differences in characteristics, cannabis use patterns, and perceived helpfulness among primary care patients who use cannabis for pain versus nonpain reasons. METHODS: Among 1688 patients who completed a 2019 cannabis survey administered in a health system in Washington state, where recreational use is legal, participants who used cannabis for pain (n = 375) were compared with those who used cannabis for other reasons (n = 558) using survey and electronic health record data. We described group differences in participant characteristics, use patterns, and perceptions and applied adjusted multinomial logistic and modified Poisson regression. RESULTS: Participants who used cannabis for pain were significantly more likely to report using applied (50.7% vs 10.6%) and beverage cannabis products (19.2% vs 11.6%), more frequent use (47.1% vs 33.1% for use ≥2 times per day; 81.6% vs 69.7% for use 4 to 7 days per week), and smoking tobacco cigarettes (19.2% vs 12.2%) than those who used cannabis for other reasons. They were also significantly more likely to perceive cannabis as very/extremely helpful (80.5% vs 72.7%), and significantly less likely to use cannabis for nonmedical reasons (4.8% vs 58.8%) or report cannabis use disorder symptoms (51.7% vs 61.1%). DISCUSSION: Primary care patients who use cannabis for pain use it more frequently, often in applied and ingested forms, and have more co-use of tobacco, which may differentially impact safety and effectiveness. These findings suggest the need for different approaches to counseling in clinical care.

Nurse Care Management for Opioid Use Disorder Treatment: The PROUD Cluster Randomized Clinical Trial.

Importance: Few primary care (PC) practices treat patients with medications for opioid use disorder (OUD) despite availability of effective treatments. Objective: To assess whether implementation of the Massachusetts model of nurse care management for OUD in PC increases OUD treatment with buprenorphine or extended-release injectable naltrexone and secondarily decreases acute care utilization. Design, Setting, and Participants: The Primary Care Opioid Use Disorders Treatment (PROUD) trial was a mixed-methods, implementation-effectiveness cluster randomized clinical trial conducted in 6 diverse health systems across 5 US states (New York, Florida, Michigan, Texas, and Washington). Two PC clinics in each system were randomized to intervention or usual care (UC) stratified by system (5 systems were notified on February 28, 2018, and 1 system with delayed data use agreement on August 31, 2018). Data were obtained from electronic health records and insurance claims. An implementation monitoring team collected qualitative data. Primary care patients were included if they were 16 to 90 years old and visited a participating clinic from up to 3 years before a system's randomization date through 2 years after. Intervention: The PROUD intervention included 3 components: (1) salary for a full-time OUD nurse care manager; (2) training and technical assistance for nurse care managers; and (3) 3 or more PC clinicians agreeing to prescribe buprenorphine. Main Outcomes and Measures: The primary outcome was a clinic-level measure of patient-years of OUD treatment (buprenorphine or extended-release injectable naltrexone) per 10 000 PC patients during the 2 years postrandomization (follow-up). The secondary outcome, among patients with OUD prerandomization, was a patient-level measure of the number of days of acute care utilization during follow-up. Results: During the baseline period, a total of 130 623 patients were seen in intervention clinics (mean [SD] age, 48.6 [17.7] years; 59.7% female), and 159 459 patients were seen in UC clinics (mean [SD] age, 47.2 [17.5] years; 63.0% female). Intervention clinics provided 8.2 (95% CI, 5.4-∞) more patient-years of OUD treatment per 10 000 PC patients compared with UC clinics (P = .002). Most of the benefit accrued in 2 health systems and in patients new to clinics (5.8 [95% CI, 1.3-∞] more patient-years) or newly treated for OUD postrandomization (8.3 [95% CI, 4.3-∞] more patient-years). Qualitative data indicated that keys to successful implementation included broad commitment to treat OUD in PC from system leaders and PC teams, full financial coverage for OUD treatment, and straightforward pathways for patients to access nurse care managers. Acute care utilization did not differ between intervention and UC clinics (relative rate, 1.16; 95% CI, 0.47-2.92; P = .70). Conclusions and Relevance: The PROUD cluster randomized clinical trial intervention meaningfully increased PC OUD treatment, albeit unevenly across health systems; however, it did not decrease acute care utilization among patients with OUD. Trial Registration: ClinicalTrials.gov Identifier: NCT03407638.

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

BACKGROUND: Brief cannabis screening followed by standardized assessment of symptoms may support diagnosis and treatment of cannabis use disorder (CUD). This study tested whether the probability of a medical provider diagnosing and treating CUD increased with the number of substance use disorder (SUD) symptoms documented in patients' EHRs. METHODS: This observational study used EHR and claims data from an integrated healthcare system. Adult patients were included who reported daily cannabis use and completed the Substance Use Symptom Checklist, a scaled measure of DSM-5 SUD symptoms (0-11), during routine care 3/1/2015-3/1/2021. Logistic regression estimated associations between SUD symptom counts and: 1) CUD diagnosis; 2) CUD treatment initiation; and 3) CUD treatment engagement, defined based on Healthcare Effectiveness Data and Information Set (HEDIS) ICD-codes and timelines. We tested moderation across age, gender, race, and ethnicity. RESULTS: Patients (N=13,947) were predominantly middle-age, male, White, and non-Hispanic. Among patients reporting daily cannabis use without other drug use (N=12,568), the probability of CUD diagnosis, treatment initiation, and engagement increased with each 1-unit increase in Symptom Checklist score (p's<0.001). However, probabilities of diagnosis, treatment, and engagement were low, even among those reporting ≥2 symptoms consistent with SUD: 14.0% diagnosed (95% CI: 11.7-21.6), 16.6% initiated treatment among diagnosed (11.7-21.6), and 24.3% engaged in treatment among initiated (15.8-32.7). Only gender moderated associations between Symptom Checklist and diagnosis (p=0.047) and treatment initiation (p=0.012). Findings were similar for patients reporting daily cannabis use with other drug use (N=1379). CONCLUSION: Despite documented symptoms, CUD was underdiagnosed and undertreated in medical settings.

Prevalence of Cannabis Use Disorder and Reasons for Use Among Adults in a US State Where Recreational Cannabis Use Is Legal.

Importance: Medical and nonmedical cannabis use and cannabis use disorders (CUD) have increased with increasing cannabis legalization. However, the prevalence of CUD among primary care patients who use cannabis for medical or nonmedical reasons is unknown for patients in states with legal recreational use. Objective: To estimate the prevalence and severity of CUD among patients who report medical use only, nonmedical use only, and both reasons for cannabis use in a state with legal recreational use. Design, Setting, and Participants: This cross-sectional survey study took place at an integrated health system in Washington State. Among 108 950 adult patients who completed routine cannabis screening from March 2019 to September 2019, 5000 were selected for a confidential cannabis survey using stratified random sampling for frequency of past-year cannabis use and race and ethnicity. Among 1688 respondents, 1463 reporting past 30-day cannabis use were included in the study. Exposure: Patient survey-reported reason for cannabis use in the past 30 days: medical use only, nonmedical use only, and both reasons. Main Outcomes and Measures: Patient responses to the Composite International Diagnostic Interview-Substance Abuse Module for CUD, corresponding to Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition CUD severity (0-11 symptoms) were categorized as any CUD (≥2 symptoms) and moderate to severe CUD (≥4 symptoms). Adjusted analyses were weighted for survey stratification and nonresponse for primary care population estimates and compared prevalence of CUD across reasons for cannabis use. Results: Of 1463 included primary care patients (weighted mean [SD] age, 47.4 [16.8] years; 748 [weighted proportion, 61.9%] female) who used cannabis, 42.4% (95% CI, 31.2%-54.3%) reported medical use only, 25.1% (95% CI, 17.8%-34.2%) nonmedical use only, and 32.5% (95% CI, 25.3%-40.8%) both reasons for use. The prevalence of CUD was 21.3% (95% CI, 15.4%-28.6%) and did not vary across groups. The prevalence of moderate to severe CUD was 6.5% (95% CI, 5.0%-8.6%) and differed across groups: 1.3% (95% CI, 0.0%-2.8%) for medical use, 7.2% (95% CI, 3.9%-10.4%) for nonmedical use, and 7.5% (95% CI, 5.7%-9.4%) for both reasons for use (P = .01). Conclusions and Relevance: In this cross-sectional study of primary care patients in a state with legal recreational cannabis use, CUD was common among patients who used cannabis. Moderate to severe CUD was more prevalent among patients who reported any nonmedical use. These results underscore the importance of assessing patient cannabis use and CUD symptoms in medical settings.

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

Importance: Substance use disorders (SUDs) are underrecognized in primary care, where structured clinical interviews are often infeasible. A brief, standardized substance use symptom checklist could help clinicians assess SUD. Objective: To evaluate the psychometric properties of the Substance Use Symptom Checklist (hereafter symptom checklist) used in primary care among patients reporting daily cannabis use and/or other drug use as part of population-based screening and assessment. Design, Setting, and Participants: This cross-sectional study was conducted among adult primary care patients who completed the symptom checklist during routine care between March 1, 2015, and March 1, 2020, at an integrated health care system. Data analysis was conducted from June 1, 2021, to May 1, 2022. Main Outcomes and Measures: The symptom checklist included 11 items corresponding to SUD criteria in the Diagnostic and Statistical Manual for Mental Disorders (Fifth Edition) (DSM-5). Item response theory (IRT) analyses tested whether the symptom checklist was unidimensional and reflected a continuum of SUD severity and evaluated item characteristics (discrimination and severity). Differential item functioning analyses examined whether the symptom checklist performed similarly across age, sex, race, and ethnicity. Analyses were stratified by cannabis and/or other drug use. Results: A total of 23 304 screens were included (mean [SD] age, 38.2 [5.6] years; 12 554 [53.9%] male patients; 17 439 [78.8%] White patients; 20 393 [87.5%] non-Hispanic patients). Overall, 16 140 patients reported daily cannabis use only, 4791 patients reported other drug use only, and 2373 patients reported both daily cannabis and other drug use. Among patients with daily cannabis use only, other drug use only, or both daily cannabis and other drug use, 4242 (26.3%), 1446 (30.2%), and 1229 (51.8%), respectively, endorsed 2 or more items on the symptom checklist, consistent with DSM-5 SUD. For all cannabis and drug subsamples, IRT models supported the unidimensionality of the symptom checklist, and all items discriminated between higher and lower levels of SUD severity. Differential item functioning was observed for some items across sociodemographic subgroups but did not result in meaningful change (<1 point difference) in the overall score (0-11). Conclusions and Relevance: In this cross-sectional study, a symptom checklist, administered to primary care patients who reported daily cannabis and/or other drug use during routine screening, discriminated SUD severity as expected and performed well across subgroups. Findings support the clinical utility of the symptom checklist for standardized and more complete SUD symptom assessment to help clinicians make diagnostic and treatment decisions in primary care.

Integrating Alcohol-Related Prevention and Treatment Into Primary Care: A Cluster Randomized Implementation Trial.

Importance: Unhealthy alcohol use is common and affects morbidity and mortality but is often neglected in medical settings, despite guidelines for both prevention and treatment. Objective: To test an implementation intervention to increase (1) population-based alcohol-related prevention with brief interventions and (2) treatment of alcohol use disorder (AUD) in primary care implemented with a broader program of behavioral health integration. Design, Setting, and Participants: The Sustained Patient-Centered Alcohol-Related Care (SPARC) trial was a stepped-wedge cluster randomized implementation trial, including 22 primary care practices in an integrated health system in Washington state. Participants consisted of all adult patients (aged ≥18 years) with primary care visits from January 2015 to July 2018. Data were analyzed from August 2018 to March 2021. Interventions: The implementation intervention included 3 strategies: practice facilitation; electronic health record decision support; and performance feedback. Practices were randomly assigned launch dates, which placed them in 1 of 7 waves and defined the start of the practice's intervention period. Main Outcomes and Measures: Coprimary outcomes for prevention and AUD treatment were (1) the proportion of patients who had unhealthy alcohol use and brief intervention documented in the electronic health record (brief intervention) for prevention and (2) the proportion of patients who had newly diagnosed AUD and engaged in AUD treatment (AUD treatment engagement). Analyses compared monthly rates of primary and intermediate outcomes (eg, screening, diagnosis, treatment initiation) among all patients who visited primary care during usual care and intervention periods using mixed-effects regression. Results: A total of 333 596 patients visited primary care (mean [SD] age, 48 [18] years; 193 583 [58%] female; 234 764 [70%] White individuals). The proportion with brief intervention was higher during SPARC intervention than usual care periods (57 vs 11 per 10 000 patients per month; P < .001). The proportion with AUD treatment engagement did not differ during intervention and usual care (1.4 vs 1.8 per 10 000 patients; P = .30). The intervention increased intermediate outcomes: screening (83.2% vs 20.8%; P < .001), new AUD diagnosis (33.8 vs 28.8 per 10 000; P = .003), and treatment initiation (7.8 vs 6.2 per 10 000; P = .04). Conclusions and Relevance: In this stepped-wedge cluster randomized implementation trial, the SPARC intervention resulted in modest increases in prevention (brief intervention) but not AUD treatment engagement in primary care, despite important increases in screening, new diagnoses, and treatment initiation. Trial Registration: ClinicalTrials.gov Identifier: NCT02675777.

Perspectives from women who engaged in prenatal and postpartum cannabis use in a U.S. State with legal non-medical use.

Evidence suggests fetal risks are associated with cannabis use during pregnancy. Yet, insights into women's decision-making and cannabis use during pregnancy are limited. This study explored these concepts with postpartum women who used cannabis during and after pregnancy. We conducted interviews with 15 women (4 self-identifying a race other than White and 4 self-identifying Hispanic ethnicity) who: 1) lived in the Puget Sound region of Washington State, 2) reported past-year cannabis use on a routine screen, and 3) had documented pregnancy and delivery March 2015-May 2017. Semi-structured interviews asked about decision-making and cannabis use during pregnancy and postpartum. We used template analysis for coding and analysis. The key findings included that women: 1) gathered information about cannabis use during pregnancy primarily through internet searches and discussions with peers; 2) were reluctant to talk with health care providers about cannabis; 3) used cannabis while pregnant to treat health issues, including morning sickness, pain, and mental health conditions; 4) were comfortable with their decision to use cannabis while pregnant, but had questions about long-term effects; and 5) tried to mitigate transmission through breastmilk. Women decided about cannabis during pregnancy based on their experience, health symptoms, and information gathered from the internet and peers, often without guidance from their health care provider. Results point to opportunities for providers to become informed about and engage in discussion with patients about cannabis use during preconception, pregnancy, and postpartum.

Cannabis and nicotine co-use among primary care patients in a state with legal cannabis access.

The aim of this exploratory analysis was to evaluate cannabis exposure, reasons for use and problematic cannabis use among adult primary care patients in Washington state (United States) who co-use cannabis and nicotine (tobacco cigarettes and/or nicotine vaping) compared to patients who endorse current cannabis use only. As part of a NIDA Clinical Trials Network (CTN) parent study, patients who completed a cannabis screen as part of routine primary care were randomly sampled (N = 5,000) to a receive a confidential cannabis survey. Patients were stratified and oversampled based on the frequency of past-year cannabis use and for Black, indigenous, or other persons of color. Patients who endorsed past 30-day cannabis use are included here (N = 1388). Outcomes included; prevalence of cannabis use, days of cannabis use per week and times used per day, methods of use, THC:CBD content, non-medical and/or medical use, health symptoms managed, and cannabis use disorder (CUD) symptom severity. We conducted unadjusted bivariate analyses comparing outcomes between patients with cannabis and current nicotine co-use to patients with cannabis-only use. Nicotine co-use (n = 352; 25.4 %) was associated with differences in method of cannabis use, THC:CBD content, days of use per week and times used per day, number of health symptoms managed, and CUD severity (all p < 0.001), compared to primary care patients with cannabis-only use (n = 1036). Interventions targeting cannabis and nicotine co-use in primary care are not well-established and further research is warranted given findings of more severe cannabis use patterns and the adverse health outcomes associated with co-use.

Validity of the Single-Item Screen-Cannabis (SIS-C) for Cannabis Use Disorder Screening in Routine Care.

Importance: Cannabis use is prevalent and increasing, and frequent use intensifies the risk of cannabis use disorder (CUD). CUD is underrecognized in medical settings, but a validated single-item cannabis screen could increase recognition. Objective: To evaluate the Single-Item Screen-Cannabis (SIS-C), administered and documented in routine primary care, compared with a confidential reference standard measure of CUD. Design, Setting, and Participants: This diagnostic study included a sample of adult patients who completed routine cannabis screening between January 28 and September 12, 2019, and were randomly selected for a confidential survey about cannabis use. Random sampling was stratified by frequency of past-year use and race and ethnicity. The study was conducted at an integrated health system in Washington state, where adult cannabis use is legal. Data were analyzed from May 2021 to March 2022. Exposures: The SIS-C asks about frequency of past-year cannabis use with responses (none, less than monthly, monthly, weekly, daily or almost daily) documented in patients' medical records. Main Outcomes and Measures: The Diagnostic and Statistical Manual, Fifth Edition (DSM-5) Composite International Diagnostic Interview-Substance Abuse Module (CIDI-SAM) for past-year CUD was completed on a confidential survey and considered the reference standard. The SIS-C was compared with 2 or more criteria on the CIDI-SAM, consistent with CUD. All analyses were weighted, accounting for survey design and nonresponse, to obtain estimates representative of the health system primary care population. Results: Of 5000 sampled adult patients, 1688 responded to the cannabis survey (34% response rate). Patients were predominantly middle-aged (weighted mean [SD] age, 50.7 [18.1]), female or women (weighted proportion [SE], 55.9% [4.1]), non-Hispanic (weighted proportion [SE], 96.7% [1.0]), and White (weighted proportion [SE], 74.2% [3.7]). Approximately 6.6% of patients met criteria for past-year CUD. The SIS-C had an area under receiver operating characteristic curve of 0.89 (95% CI, 0.78-0.96) for identifying CUD. A threshold of less than monthly cannabis use balanced sensitivity (0.88) and specificity (0.83) for detecting CUD. In populations with a 6% prevalence of CUD, predictive values of a positive screen ranged from 17% to 34%, while predictive values of a negative screen ranged from 97% to 100%. Conclusions and Relevance: In this diagnostic study, the SIS-C had excellent performance characteristics in routine care as a screen for CUD. While high negative predictive values suggest that the SIS-C accurately identifies patients without CUD, low positive predictive values indicate a need for further diagnostic assessment following positive results when screening for CUD in primary care.

A call to integrate health equity into learning health system research training.

In 2016, the Agency for Healthcare Research and Quality (AHRQ) recommended seven domains for training and mentoring researchers in learning health systems (LHS) science. Health equity was not included as a competency domain. This commentary from scholars in the Consortium for Applied Training to Advance the Learning health system with Scholars/Trainees (CATALyST) K12 program recommends that competency domains be extended to reflect growing demands for evidence on health inequities and interventions to alleviate them. We present real-life case studies from scholars in an LHS research training program that illustrate facilitators, challenges, and potential solutions at the program, funder, and research community-level to receiving training and mentorship in health equity-focused LHS science. We recommend actions in four areas for LHS research training programs: (a) integrate health equity throughout the current LHS domains; (b) develop training and mentoring in health equity; (c) establish program evaluation standards for consideration of health equity; and (d) bring forth relevant, extant expertise from the areas of health disparities research, community-based participatory research, and community-engaged health services research. We emphasize that LHS research must acknowledge and build on the substantial existing contributions, mainly by scholars of color, in the health equity field.

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

INTRODUCTION: The design of integrated adolescent mental health care should address needs and preferences of patients and parents/guardians. METHOD: We conducted interviews and focus groups with adolescents aged 13-17 years who received care at Kaiser Permanente Washington in 2020 and interviews with parents of such adolescents. We sought to (1) understand the challenges of primary care-based mental health and substance use screening and care for adolescents and (2) identify program design solutions. Sessions were audio-recorded, transcribed, and coded. Thematic analysis was applied to identify key challenges and design solutions. RESULTS: Emerging themes from interviews (n = 41) and focus groups (n = 10) were summarized in five overarching design principles: Engagement, Privacy, Communication, Choice, and Ease. Each design principle was expanded for operationalization within a new health system program. DISCUSSION: Health systems serving adolescents in primary care may consider application of these design principles to the development of mental health integration programs.

Sex Differences in Comorbid Mental and Substance Use Disorders Among Primary Care Patients With Opioid Use Disorder.

OBJECTIVE: The authors sought to characterize the 3-year prevalence of mental disorders and nonnicotine substance use disorders among male and female primary care patients with documented opioid use disorder across large U.S. health systems. METHODS: This retrospective study used 2014-2016 data from patients ages ≥16 years in six health systems. Diagnoses were obtained from electronic health records or claims data; opioid use disorder treatment with buprenorphine or injectable extended-release naltrexone was determined through prescription and procedure data. Adjusted prevalence of comorbid conditions among patients with opioid use disorder (with or without treatment), stratified by sex, was estimated by fitting logistic regression models for each condition and applying marginal standardization. RESULTS: Females (53.2%, N=7,431) and males (46.8%, N=6,548) had a similar prevalence of opioid use disorder. Comorbid mental disorders among those with opioid use disorder were more prevalent among females (86.4% vs. 74.3%, respectively), whereas comorbid other substance use disorders (excluding nicotine) were more common among males (51.9% vs. 60.9%, respectively). These differences held for those receiving medication treatment for opioid use disorder, with mental disorders being more common among treated females (83% vs. 71%) and other substance use disorders more common among treated males (68% vs. 63%). Among patients with a single mental health condition comorbid with opioid use disorder, females were less likely than males to receive medication treatment for opioid use disorder (15% vs. 20%, respectively). CONCLUSIONS: The high rate of comorbid conditions among patients with opioid use disorder indicates a strong need to supply primary care providers with adequate resources for integrated opioid use disorder treatment.

Comparison of Medical Cannabis Use Reported on a Confidential Survey vs Documented in the Electronic Health Record Among Primary Care Patients.

Importance: Patients who use cannabis for medical reasons may benefit from discussions with clinicians about health risks of cannabis and evidence-based treatment alternatives. However, little is known about the prevalence of medical cannabis use in primary care and how often it is documented in patient electronic health records (EHR). Objective: To estimate the primary care prevalence of medical cannabis use according to confidential patient survey and to compare the prevalence of medical cannabis use documented in the EHR with patient report. Design, Setting, and Participants: This study is a cross-sectional survey performed in a large health system that conducts routine cannabis screening in Washington state where medical and nonmedical cannabis use are legal. Among 108 950 patients who completed routine cannabis screening (between March 28, 2019, and September 12, 2019), 5000 were randomly selected for a confidential survey about cannabis use, using stratified random sampling for frequency of past-year use and patient race and ethnicity. Data were analyzed from November 2020 to December 2021. Exposures: Survey measures of patient-reported past-year cannabis use, medical cannabis use (ie, explicit medical use), and any health reason(s) for use (ie, implicit medical use). Main Outcomes and Measures: Survey data were linked to EHR data in the year before screening. EHR measures included documentation of explicit and/or implicit medical cannabis use. Analyses estimated the primary care prevalence of cannabis use and compared EHR-documented with patient-reported medical cannabis use, accounting for stratified sampling and nonresponse. Results: Overall, 1688 patients responded to the survey (34% response rate; mean [SD] age, 50.7 [17.5] years; 861 female [56%], 1184 White [74%], 1514 non-Hispanic [97%], and 1059 commercially insured [65%]). The primary care prevalence of any past-year patient-reported cannabis use on the survey was 38.8% (95% CI, 31.9%-46.1%), whereas the prevalence of explicit and implicit medical use were 26.5% (95% CI, 21.6%-31.3%) and 35.1% (95% CI, 29.3%-40.8%), respectively. The prevalence of EHR-documented medical cannabis use was 4.8% (95% CI, 3.45%-6.2%). Compared with patient-reported explicit medical use, the sensitivity and specificity of EHR-documented medical cannabis use were 10.0% (95% CI, 4.4%-15.6%) and 97.1% (95% CI, 94.4%-99.8%), respectively. Conclusions and Relevance: These findings suggest that medical cannabis use is common among primary care patients in a state with legal use, and most use is not documented in the EHR. Patient report of health reasons for cannabis use identifies more medical use compared with explicit questions about medical use.

Clinical documentation of patient-reported medical cannabis use in primary care: Toward scalable extraction using natural language processing methods.

Background: Most states have legalized medical cannabis, yet little is known about how medical cannabis use is documented in patients' electronic health records (EHRs). We used natural language processing (NLP) to calculate the prevalence of clinician-documented medical cannabis use among adults in an integrated health system in Washington State where medical and recreational use are legal. Methods: We analyzed EHRs of patients ≥18 years old screened for past-year cannabis use (November 1, 2017-October 31, 2018), to identify clinician-documented medical cannabis use. We defined medical use as any documentation of cannabis that was recommended by a clinician or described by the clinician or patient as intended to manage health conditions or symptoms. We developed and applied an NLP system that included NLP-assisted manual review to identify such documentation in encounter notes. Results: Medical cannabis use was documented for 16,684 (5.6%) of 299,597 outpatient encounters with routine screening for cannabis use among 203,489 patients seeing 1,274 clinicians. The validated NLP system identified 54% of documentation and NLP-assisted manual review the remainder. Language documenting reasons for cannabis use included 125 terms indicating medical use, 28 terms indicating non-medical use and 41 ambiguous terms. Implicit documentation of medical use (e.g., "edible THC nightly for lumbar pain") was more common than explicit (e.g., "continues medical cannabis use"). Conclusions: Clinicians use diverse and often ambiguous language to document patients' reasons for cannabis use. Automating extraction of documentation about patients' cannabis use could facilitate clinical decision support and epidemiological investigation but will require large amounts of gold standard training data.

Prevalence of medical and nonmedical cannabis use among veterans in primary care.

OBJECTIVE: This study examined past-year cannabis use prevalence and sociodemographic and clinical correlates of cannabis use among Veterans Health Administration (VHA) primary care patients in a state with legalized medical cannabis. METHOD: Participants were 1,072 predominantly white, male, VHA primary care patients enrolled in a drug screening validation study (2012-2014). Sociodemographic and clinical correlates were examined by past-year cannabis use status. Multivariate regression models, adjusted for demographics, estimated cannabis use prevalence and clinical correlates among recreational, medical, and both medical and recreational users. RESULTS: Nearly one in five (18.7%) veterans endorsed past-year cannabis use, with 14.1% of the total sample reporting any recreational use and 7.0% reporting any medical use. Correlates of any past-year use included younger age, period of service, being unmarried, lower education, lower income, other substance use, meeting criteria for an alcohol or drug use disorder or posttraumatic stress disorder, higher pain rating, and lower self-reported well-being. Compared to veterans endorsing only recreational use, veterans endorsing only medical use reported more cannabis use days but had lower odds of other drug use, alcohol or drug-related problems, or alcohol or drug use disorders. Differences between recreational only users and those using medical and recreational cannabis were minimal. CONCLUSIONS: Veterans enrolled in VHA in states with legalized cannabis may be particularly likely to use cannabis. Veterans identifying as recreational users may be at increased risk for adverse clinical outcomes compared to medical-only users. Prevalence monitoring, assessment, and intervention services should be considered, particularly in states with legalized cannabis. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Prevalence of Medical Cannabis Use and Associated Health Conditions Documented in Electronic Health Records Among Primary Care Patients in Washington State.

Importance: Many people use cannabis for medical reasons despite limited evidence of therapeutic benefit and potential risks. Little is known about medical practitioners' documentation of medical cannabis use or clinical characteristics of patients with documented medical cannabis use. Objectives: To estimate the prevalence of past-year medical cannabis use documented in electronic health records (EHRs) and to describe patients with EHR-documented medical cannabis use, EHR-documented cannabis use without evidence of medical use (other cannabis use), and no EHR-documented cannabis use. Design, Setting, and Participants: This cross-sectional study assessed adult primary care patients who completed a cannabis screen during a visit between November 1, 2017, and October 31, 2018, at a large health system that conducts routine cannabis screening in a US state with legal medical and recreational cannabis use. Exposures: Three mutually exclusive categories of EHR-documented cannabis use (medical, other, and no use) based on practitioner documentation of medical cannabis use in the EHR and patient report of past-year cannabis use at screening. Main Outcomes and Measures: Health conditions for which cannabis use has potential benefits or risks were defined based on National Academies of Sciences, Engineering, and Medicine's review. The adjusted prevalence of conditions diagnosed in the prior year were estimated across 3 categories of EHR-documented cannabis use with logistic regression. Results: A total of 185 565 patients (mean [SD] age, 52.0 [18.1] years; 59% female, 73% White, 94% non-Hispanic, and 61% commercially insured) were screened for cannabis use in a primary care visit during the study period. Among these patients, 3551 (2%) had EHR-documented medical cannabis use, 36 599 (20%) had EHR-documented other cannabis use, and 145 415 (78%) had no documented cannabis use. Patients with medical cannabis use had a higher prevalence of health conditions for which cannabis has potential benefits (49.8%; 95% CI, 48.3%-51.3%) compared with patients with other cannabis use (39.9%; 95% CI, 39.4%-40.3%) or no cannabis use (40.0%; 95% CI, 39.8%-40.2%). In addition, patients with medical cannabis use had a higher prevalence of health conditions for which cannabis has potential risks (60.7%; 95% CI, 59.0%-62.3%) compared with patients with other cannabis use (50.5%; 95% CI, 50.0%-51.0%) or no cannabis use (42.7%; 95% CI, 42.4%-42.9%). Conclusions and Relevance: In this cross-sectional study, primary care patients with documented medical cannabis use had a high prevalence of health conditions for which cannabis use has potential benefits, yet a higher prevalence of conditions with potential risks from cannabis use. These findings suggest that practitioners should be prepared to discuss potential risks and benefits of cannabis use with patients.