This research will identify and characterize the factors differentiating patient portal users from non-users and develop guidelines to optimize portal design and development for population subgroups.
Human Factors Considerations in the Design and Implementation of Telemedicine-Integrated Ambulance-Based Environments for Stroke Care
This research will evaluate an existing ambulance-based stroke telemedicine pilot program in order to develop guidelines to expand the program.
Adapting, Scaling, and Spreading an Algorithmic Asthma Mobile Intervention to Promote Patient-Reported Outcomes Within Primary Care Settings
This project will adapt and evaluate a mobile health application to improve patient-reported asthma outcomes in New York.
Context is Critical: Understanding When and Why Electronic Health Record-Related Safety Hazards Happen
This study showed the feasibility and value of creating a methodology and process for a health information technology black box to inform electronic health record design and usability.
This project enhanced the Children’s Electronic Health Record Format (Format) by identifying a high priority set of 47 functional requirements from the initial larger set, and creating a list of 16 recommended uses of the Format along with implementation notes.
Power to the Patient: Design and Test of Closed-Loop Interactive IT for Geriatric Heart Failure Self-Care
This research team designed and tested an application called Power to the People to assist older patients to self-manage their chronic heart failure.
Development of a Clinical Decision Support Tool for Facilitating Naturalistic Decision Making and Improving Blood Culture Utilization
This research study addressed the overuse of blood cultures to diagnose sepsis by developing an electronic health record-embedded clinical decision support tool that draws upon the strengths of analytical and naturalistic decision making.
The research team developed and tested algorithms that can predict postoperative adverse outcomes with a high degree of accuracy.
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.
The purpose of this research was to investigate the relationships between electronic health record adoption and usability, work environment, and patient and nurse outcomes.