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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.
This project will apply machine learning against a large data set to develop a model to both understand and predict surgical cancellations on individual pediatric patients at two pediatric surgical sites.
This study assessed the usability and impact of inpatient portals on patient experience, engagement, and perceptions of care.
This project developed and pilot-tested a novel, outcomes-based emergency department triage tool and found that risk stratification and waiting times were improved for some patients.
This project seeks to develop an understanding of the cognitive work of clinician teams and family members involved in pediatric trauma care transitions in order to design usable and useful health information technologies.
The objectives of the 2015 and 2016 AMIA Policy Invitational meetings are to develop consensus recommendations on policy to improve health information technology for patient care, facilitate research, and manage the health of populations.
This project evaluated the feasibility of two Stage 3 Meaningful Use Care Coordination measures and provided feedback to policymakers and providers for their improvement.
This project used qualitative methods to identify strategies for effective and efficient adoption of health information technology by home health agencies.
This project tested a pediatric voice therapy telehealth system and found that it was feasible to implement and well accepted by children and their families.