Project Summary Dental caries and tooth loss are the two major dental problems in Sjögren's syndrome patients (SSP) that lead to high restorative treatments resulting in increased dental disease burden among these patients. Although caries is very common and largely attributed to xerostomia in these patients, existing studies have not evaluated the characteristics of caries (surface involvement and pattern of caries) and the influence of comorbidities and medications on caries. The Sjögren's Syndrome Foundation (SSF) and the American Dental Association recently developed clinical practice guidelines for the prevention of caries in SSP. However, this guideline is based on expert opinion and lacks clinical validation. Moreover, effectiveness of dental restorations (amalgam and composites) are unknown and no study has evaluated the longevity of direct restorative materials in SSP. In this project, we will study the characteristics of dental caries and assess the longevity of dental restorations using linked dental and medical electronic health records (EHR) of SSP from the Indiana University School of Dentistry (IUSD) and Indiana Network for Patients Care (INPC) respectively. We will generate a dataset that include information such as patients' medical history, medications, and lab reports from electronic medical records at INPC and dental history, dental treatment history, and tooth-surfaces level data from electronic dental records at IUSD. This dataset will be utilized to: (1) assess the role of xerostomia, co-morbidities, and medications on the manifestation of caries at tooth and tooth surface level among SSP; and (2) determine the longevity of restorations placed in SSP compared to those placed in non-SSP. Our project is innovative because it will use linked dental and medical EHR data to identify SSP and generate a large sample size of SSP. This project will address research questions important to patients, dentists and the research community on dental caries and suitable restorations for SSP; produce a generalizable method for linking dental and medical EHR data and extracting various clinical data for research purposes; and create future opportunities to investigate the oral health of patients with rare diseases.