Search found 52 items
This research will develop, implement, disseminate, and evaluate reusable, shareable clinical decision support for both patients and clinicians in the area of chronic pain management.
This research will identify and characterize the factors differentiating patient portal users from non-users and develop guidelines to optimize portal design and development for population subgroups.
This research will evaluate the safety, usability, and impact of an e-prescribing standard on adverse drug events related to erroneously dispensed medications.
This research will enhance and test a tool which uses natural language processing to provide a real-time assessment of dialog during motivational interviewing training.
This research will evaluate the lifecycle of clinical decision support (CDS), as currently implemented at most health systems, against a future CDS state that incorporates the use of shareable CDS resources created using the Agency for Healthcare Research and Quality’s CDS Connect tools.
This study will examine usability and safety hazards of electronic medication administration records, with a focus on communication and information flow between health information technology applications.
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.
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 project will develop a method to use video captured electronic health record interactions to analyze the context around medication errors, identify design elements that contributed to the errors, and make design recommendations to mitigate those errors.
This project will develop and evaluate an electronic health record-embedded clinical decision support tool that draws upon the strength of analytical and naturalistic decision-making to optimize the use of blood cultures in critically ill children.