Decisionmaker
Annual Conferences on Health IT & Analytics 2021-2023
The annual Conference on Health IT and Analytics (CHITA) facilitates the development of research and implementation lessons; fosters relationships among academics, policymakers, and practitioners; and helps disseminate research and train the next generation of health IT and analytics researchers with diverse backgrounds to improve healthcare quality, efficiency, and equity.
Evaluating and Enhancing Health Information Technology for COVID-19 Response Workflow in a Specialized COVID-19 Hospital in a Medically Underserved Community
This research will study how a safety-net hospital responds to a pandemic, specifically COVID-19, to identify how information needs are met and how decisions are made and communicated to other individuals internal and external to the institution.
The imperative for patient-centered clinical decision support.
Building and maintaining trust in clinical decision support: Recommendations from the Patient‐Centered CDS Learning Network.
Patient-Centered Outcomes Research Clinical Decision Support Learning Network - Final Report
Development and Evaluation of Sociotechnical Metrics To Inform Health IT Adaptation - Final Report
Health Information Exchange Utilization and Inter-Hospital Transfer Outcomes
This research’s goal is to show that interoperability, including adoption of regional health information exchanges, improves mortality rates and care efficiency at the population and patient levels.
Annual Conference on Health Information Technology & Analytics (CHITA)
The 2018-2020 annual Conference on Health IT & Analytics connected a wide range of academic disciplines, Federal agencies, policymakers, funders, practitioners, patient advocates, and industry professionals to develop a health information technology and analytics (HIT+A) research agenda and materials that were widely disseminated to identify trends and knowledge gaps in HIT+A.
Enhancing Patient Matching in Support of Operational Health Information Exchange
This project will enhance novel algorithms for matching patient health information across data sources, implement them, and evaluate their accuracy.