Thesis (Ph.D.)--University of Washington, 2022Nearly 50 million people use cannabis in the past year, and of those, 23% use cannabis daily. Frequent cannabis use increases risk of developing a cannabis use disorder (CUD), a problematic pattern of cannabis use leading to clinically significant impairment and distress. Primary care providers are ideally positioned to identify cannabis use and use disorders, provide brief interventions, and guide patients to treatment. However, CUD is under-recognized and undertreated in primary care settings. One key barrier is a lack of validated screening and assessment tools that are feasible and appropriate to use routinely in primary care. Specific aims of this dissertation were to: 1) test the performance of a single-item screening measure of patient-reported cannabis use compared to a gold-standard diagnostic criterion of Diagnostic and Statistical Manual of Mental Disorders-5th Edition (DSM-5) CUD; 2) test the psychometric properties of a Substance Use Symptom Checklist; and 3) test whether the probability of clinically recognized CUD and treatment increases with greater symptom severity and whether this relationship is moderated by age, gender, race, or ethnicity. Aim 1 used EHR-linked data from a confidential 2019 survey of 1688 Kaiser Permanente Washington (KPWA) primary care patients. We compared the Single-Item Screen for Cannabis (SIS-C) used routinely in primary care with results documented in the EHR to a confidential reference standard of DSM-5 CUD administered on the survey. The SIS-C demonstrated strong validity for identifying CUD (area under receiver operating characteristic curves (AUC) 0.89 [95% CI: 0.78-0.96]). A threshold of “less than monthly” cannabis use had the best balance of sensitivity (0.88) and specificity (0.83). Aim 2 used data exclusively from the EHR. Substance Use Symptom Checklists (“Symptom Checklists”) were completed 3/1/2015-3/1/2020 as part of systematic follow-up assessment for CUD by 16,140 KPWA patients reporting daily cannabis use, 4,791 patients reporting other drug use, and 2,373 reporting both. We used item response theory to evaluate the psychometric performance of the Symptom Checklist, finding it unidimensional, discriminative, and performing equally well across demographic subgroups. Aim 3 used EHR and claims data from 13,947 KPWA patients reporting daily cannabis use who completed a Symptom Checklist 3/1/2015-3/1/2021, were continuously enrolled at KPWA, and had not received CUD care in the year prior to completing the Symptom Checklist. Using logistic regression with cluster-robust standard errors, we found that symptom severity, as reported on the Symptom Checklist, was positively associated with subsequent CUD diagnosis, initiation of CUD treatment, and ongoing engagement in CUD treatment although probability of all three care elements was generally low. Gender moderated the association between severity and CUD diagnosis such that women were more likely than men to be diagnosed but less likely than men to initiate treatment at the highest levels of severity. Overall, findings support the validity of brief, practical tools to identify and evaluate the spectrum of cannabis use and use disorder. This work lays a foundation for advancing measurement-based care for CUD in primary care
