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This research will implement a personalized and electronically integrated shared clinical decision support system for left ventricular assist devices in patients with advanced heart failure.
This research will validate a shared decision making tool integrated with patient-reported outcomes and clinical data from electronic health records for enabling decision support in patients with knee osteoarthritis considering total knee replacement.
This research aims to enhance and implement a clinical decision support tool that will support providers and underinsured patients in making personalized decisions regarding diet goal setting.
This research aims to integrate an electronic sexually transmitted infection (STI) risk assessment tool for adolescents into four pediatric primary care clinics.
This research aims to adapt a decision support tool that integrates clinical risk information with patient preferences. The goal of this work is to support patients in making informed breast reconstruction decisions together with their clinicians.
The research team developed and tested algorithms that can predict postoperative adverse outcomes with a high degree of accuracy.
The investigators used a mixed-methods approach to incorporate quantitative and qualitative research in developing and validating a health IT adaptation survey.
The researchers developed a mobile health application to distribute evidence-based pain self-management strategies to patients with juvenile idiopathic arthritis.
This project will determine the optimal display of blood pressure data for patients and their physicians in order to facilitate shared decisionmaking about blood pressure control and treatment.
This project identified patients’ needs, preferences, and responses when receiving abnormal test result notifications through an electronic patient portal, and developed a usable prototype to improving test result communication.