This research will examine the factors affecting cancer patients’ use of an electronic patient safety event reporting system to communicate adverse medication-related events to their care team.
This research implemented a clinical decision support tool to identify patients at risk for a life-threatening, uncommon cardiac arrhythmia.
This study will create an innovative electronic medication administration record prototype and a medication administration workflow risk assessment to improve the medication administration process and the usability and safety of the electronic medication administration records in response to challenges from COVID-19.
Providing Evidence and Developing a Toolkit to Accelerate the Adoption of Patient Photographs in Electronic Health Records
This study will evaluate the effectiveness of patient photographs displayed in electronic health record systems for preventing wrong-patient errors.
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.
Integrating Contextual Factors into Clinical Decision Support to Reduce Contextual Error and Improve Outcomes in Ambulatory Care
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.
The research team developed and tested algorithms that can predict postoperative adverse outcomes with a high degree of accuracy.
This research study used cognitive systems engineering approaches to understand the decision making process in the emergency department and proposed models and solutions to some of the biggest challenges in practicing medicine in this complex environment.