This project will use 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 test the effectiveness of using patient-reported outcomes for cirrhosis collected with Patient Buddy and EncephalApp on hospital readmissions.
This project will examine the quality and safety impact of patient-initiated telemedicine visits with primary care providers.
This project will redesign approaches for collecting and using allergy information with the goal of improving healthcare quality and safety, including completeness and accuracy of allergy data.
This project proposes a novel proactive system to reduce alert burden and thereby increase attention to situations in which patient safety is at risk.
This research will support development and testing of technical tools for use within electronic health records or other systems to collect patient-reported outcomes for clinical use and research.
This contract provided the administration and management of the Agency for Healthcare Research and Quality's “Step Up App Challenge: Advancing Care Through Patient Self-Assessments.”
This project will develop and evaluate an an electronic dashboard to display patient reported outcomes for patients with rheumatoid arthritis that will facilitate clinician and patient conversations about their care.
The central goal of the annual Conference on Health IT & Analytics is to develop a health information technology and analytics (HIT+A) research agenda that supports national efforts to create a learning health system that produces evidence to make health care safer, of higher quality, more accessible, equitable, and affordable.
This study will evaluate the effectiveness of patient photographs displayed in electronic health record systems for preventing wrong-patient errors.