Project Summary. Primary care (PC) is well-positioned to detect and address substance use (SU) and substance use disorders (SUDs), yet most PC settings have notable gaps in providing SU-related care. One way to improve SU-related care is to use standardized measurements to screen for unhealthy SU and to assess SUD symptoms, which informs clinical care by detecting unhealthy SU, assessing SUD severity, informing decisions about SUD treatment intensity, and monitoring clinical outcomes over time. Researchers and national agencies are increasingly calling for the use of standardized measures of unhealthy SU and SUD symptoms in routine PC settings; however, surprisingly little is known about how such measures perform when they are used in the context of routine PC—i.e., administered in routine appointments and documented in electronic health records (EHRs). We propose to leverage a large and novel EHR dataset from Kaiser Permanente Washington, a large integrated regional health system. The dataset will include standardized measures of the frequency of cannabis and other drug use, completed as part of an annual screen by >450,000 patients annually (91% of adults who attend PC appointments as of Feb. 2020), and a novel patient- reported SUD symptom checklist that is based on the DSM-5 SUD criteria (“DSM-5 checklist”) for patients who reported daily cannabis use (~19,089 unique patients) or past-year illicit drug use (~6,075 unique patients). This 1-year study includes psychometric analyses that evaluate the DSM-5 symptom checklist as a scaled measure of SUD severity and the consistency of its performance across demographically diverse subgroups. To our awareness, this is the first study to evaluate any standardized patient-reported SUD symptom measure integrated into routine PC. This research will improve clinical care by helping providers and patients understand the information provided by these scaled patient-reported measures with regards to substance use and SUD-related risk. The work will also provide a foundation for future studies that use patient-reported EHR- based measures in pragmatic studies, implementation trials, and quality improvement initiatives.