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The purpose of this research is to develop a standards-based, interoperable, and publicly available clinical decision support resource to aid primary care practices in instituting routine fall risk assessment and prevention care plans.
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 research combined the artificial intelligence technology technique Dynamic Logic with natural language processing to create a model to predict risk of death over the next 12 months and found it was better than benchmark statistical and machine learning algorithms.
This project developed and pilot-tested TJR App, a mobile application designed to help patients with osteoarthritis track their pain and activity, and found that app users were more likely to track symptoms consistently, when compared to non-users.
This project convened stakeholder panels to inform the development of an indications-enabled computerized prescriber order entry system.
This project analyzed secondary data to identify factors associated with timely opening of electronic health record-based asynchronous alerts, timely response to the alerts, and patient outcomes.
The Center for Education and Research on Therapeutics (CERTs) Program focused on translating health information technology research into improved clinical practices related to medication safety, effectiveness, and cost.
The goal of this study was to develop and evaluate electronic health record-based tools to improve diagnosis and treatment of overweight and obesity in primary care.
This project modified an existing virtual patient advocate (VPA), a clinical patient education system, to become a health education tool directed towards young African-American women.
Lessons from the On-Time Pressure Ulcer program informed the development of an On-Time Fall Prevention module, which uses documentation data elements, actionable reports, and tracking tools to address residents’ fall risk factors.