Search found 30 items
This project will examine health information exchange (HIE) usage patterns, the barriers and facilitators of HIE use, and the impact of HIE use by emergency department clinicians.
This research team designed and tested an application called Power to the People to assist older patients to self-manage their chronic heart failure.
This research prospectively evaluated a machine learning algorithm that identifies candidates for neurologic surgery to control epilepsy.
This project will clarify the relationship between “pull” and “push” health information exchange usage in primary care settings, and determine the impact of each approach on potentially avoidable and costly health care utilization.
This research evaluated the usability and usefulness of medication therapy management (MTM) alerts and made recommendations for improving MTM platform design.
This research applied machine learning to develop a model predicting surgical cancellations among pediatric patients, and found the feasibility in using these algorithms as a cost-effective quality-improvement measure.
This study assessed the usability and impact of inpatient portals on patient experience, engagement, and perceptions of care.
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 integrated a validated anxiety-specific screening tool in an existing clinical decision support system and tested it with a randomized feasibility pilot that found the tool did not increase detection of anxiety in pediatric primary care.
This project developed and tested a tablet-based decision aid to assist primary care providers in applying patient-reported outcomes to smoking cessation and found that the tool facilitated more conversations about smoking cessation between patients and providers.