Project Summary Healthcare has changed rapidly in the last decade with the widespread use of electronic health records (EHRs) and the creation of national EHR-based data networks that aim to improve the quality of care. The American College of Rheumatology’s RISE registry is a federally Qualified Clinical Data Registry that collects EHR data from the practices of almost 1000 rheumatologists nationally, analyzes these data centrally, and continuously feeds back performance on quality measures to practices via a web-based dashboard. In this K24 proposal, the applicant seeks to leverage this infrastructure to improve care for individuals living with lupus, a population that has historically faced significant health disparities and gaps in quality of care. The proposed research will validate newly developed lupus quality measures across RISE practices (Aim 1). In addition, using an implementation science theory framework and qualitative methods, the applicant will create a toolkit to facilitate meaningful use of lupus patient-reported outcome measures (PROMs) in clinical practice (Aim 2). These studies will develop a rigorous scientific framework for measuring and improving the quality of care and outcomes for individuals with lupus across the United States. The proposed projects will draw on the candidate’s strong research portfolio, funded by the Centers for Disease Control and Prevention, the Agency for Healthcare Research and Quality, and the National Institutes of Health, as well as the outstanding institutional environment at the University of California, San Francisco (UCSF). For this five-year K24 award renewal, the applicant seeks to maintain her record of successfully mentoring trainees interested in patient- oriented clinical research in rheumatology, both at UCSF and at other institutions. The newly proposed studies as well as the data available from other funded studies provide rich resources for trainees who are interested in patient-oriented clinical research in rheumatology related to the use of registries, EHR data, PROs, quality measurement and implementation science.