Developed a community-wide HIE collaborative in a rural area that gave patients and providers access to comprehensive clinical data on the Internet; developed disease-management prototypes on diabetes, pediatric asthma, depression, and low back pain and evaluated the development, implementation, and outcomes of the collaborative.
This project explored whether the use of data from pain management practices can be used to develop more robust evidence-based approaches to chronic pain management.
In this study, researchers created new electronic health record-based decision support tools that guide clinicians’ perceptions and judgments of noncancer pain in ways that lead to increased use of guideline-based patient assessment and treatment of pain.
The researchers developed a mobile health application to distribute evidence-based pain self-management strategies to patients with juvenile idiopathic arthritis.
Natural Language Processing To Identify and Rank Clinically Relevant Information for EHRs in the Emergency Department
This project developed a natural language processing electronic health record search tool that automatically identifies and ranks relevant clinical information based on a patient’s presenting complaint within the emergency department setting.
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.
Natural Language Processing to Identify and Rank Clinically Relevant Information for EHRs in the Emergency Department - Final Report
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.