This research aims to determine the feasibility, acceptability, and outcomes associated with the use of Cloud Care, a cloud-based multidisciplinary care plan for children with medical complexity.
This research will support the development and testing of two electronic care plan applications and implementation guide for managing persons with chronic kidney disease and at least one additional chronic condition.
This research will develop methods for measuring EHR communication networks—defined as EHR-based information sharing connections among healthcare professionals —in virtual care teams and to examine the relationship between EHR communication networks and care quality.
This research will explore whether providing clinicians with contextual information at the point of care through the use of clinical decision support can reduce contextual errors, improve patient healthcare outcomes, and reduce misuse and overuse of medical services.
Researchers refined and implemented integrated digital healthcare enhancements to a previously developed, interactive, patient-centered discharge toolkit, finding that while patients used the toolkit, there were no significant changes in post-discharge healthcare utilization.
This research linked a web viewer for 3D models of patient homes to an electronic health record so that the models could be viewable and annotated from within a patient’s record for better discharge planning.
This project will develop decision support tools that integrate with electronic health records to increase the quality and effectiveness of chronic pain care.
This project determined care priorities for patients with multiple chronic conditions based on patient needs, preferences, and capabilities and developed a set of recommendations for patients and providers.
In an effort to reduce medical errors and adverse events, this project will determine the information needs of hospitalized patients and caregivers, and develop design requirements for a solution that supports communicating safety concerns to providers.
This project team developed a quantitative decision support system to help clinics balance timeliness of care with continuity of care.