This research will adapt and disseminate an effective clinical decision support tool and a patient-facing SMART on FHIR application to help patients and their doctors make informed, patient-centered decisions regarding lung cancer screening.
This study will integrate a previously piloted risk tool and clinical decision aid, MammoScreen, with an EHR to provide personalized decision support for both patients and clinicians to improve quality of care for women who are at increased risk for breast cancer.
This research will adapt a shared decisionmaking tool for lung cancer screening and create a shareable clinical decision support tool that can be integrated into any electronic health record system.
This research aims to integrate an electronic sexually transmitted infection (STI) risk assessment tool for adolescents into four pediatric primary care clinics.
This research developed an mHealth text message intervention to improve the early identification of patients with hyperglycemia.
This project will develop and evaluate the impact of the Prevent Diabetes Mellitus Clinical Decision Support on clinical outcomes, healthcare process measures, and associated costs.
This study used learning health system methods to systematically apply U.S. Preventive Services Task Force’s evidence-based recommendations with the goal of advancing individualized precision prevention.
This project will develop and disseminate an innovative communication system to identify and mitigate health risks for young African American women before pregnancy as a means of reducing health disparities in birth outcomes.
This research linked a web viewer for 3D models of patient homes to an electronic health record so that the models could be viewable and annotated from within a patient’s record for better discharge planning.
This project assessed provider mental workload and performance while processing electronic abnormal test results and found that a test result tracking mechanism improved physicians’ clinical performance.
