The study will develop, validate, implement, and assess the usability of a machine learning based clinical decision support tool designed to reduce laboratory testing overutilization in pediatric intensive care unit patients.
This study aims to optimize the use of donor hearts for infants and children awaiting heart transplantation by developing predictive models to assess in real-time the potential for transplant success and to evaluate risk. Researchers plan to display these data through intuitive visualizations on a custom-built interface to reduce clinicians’ cognitive burden, enhance decision making confidence, and help ensure the best donor match for pediatric patients.
The study will develop and test a vendor-compatible clinical decision support system to support intensive care unit nurses and physical therapists at the point of care in the timely identification of patients suitable for activity interventions and the creation of personalized activity plans.
This research study examined the relationships between clinician use of order sets, patient-level order variation, and patient outcomes and found that order set usage reduced order variation and improved patient outcomes in patients with sepsis.
This study evaluated the effectiveness of displaying patient photos and alerts in the electronic health record for preventing wrong-patient order errors, finding rigorous evidence that these interventions significantly decrease such errors.
This research studied how communication technologies facilitate or hinder communication between nurses and physicians with the ultimate goal of supporting effective communication.
This project developed patient-tailored relevant warnings about drug-drug interactions and found that it reduced irrelevant alerts.
This project evaluated the use of an in-room interactive monitor to improve patient-centered care and family engagement within a pediatric intensive care unit.
This project developed, implemented, and evaluated a voice-generated enhanced electronic note system and found that it did not improve the time to finalize notes or clinician satisfaction.
This research used a human-centered design approach to understand the cognitive work of clinical teams involved in pediatric trauma care transitions that informed the development of two prototypes for digital healthcare solutions that support clinicians caring for pediatric trauma patients.
