This project compared the risk of orders placed on the wrong electronic patient record when providers were limited to having one patient record open at a time versus up to four and found no difference in errors between the two.
This study defined a knowledge base for a clinical decision support (CDS) tool and identified technology requirements for CDS design to optimize adoption of necrotizing enterocolitis prevention practices to support clinician decision making with the overall goal to improve the use of evidence-based practices for prevention and early recognition of NEC among premature infants.
This research identified the data domains at greatest risk of communication errors during intensive care unit (ICU) patient rounds, developed the ability to conduct simulated ICU rounds for research and training, and found that there is a need for real-time simultaneous reviewing of data by all members of the rounding team to reduce communication errors.
This project developed and pilot-tested a novel, outcomes-based emergency department triage tool and found that risk stratification and waiting times were improved for some patients.
This study evaluated a smoking cessation program using interactive voice recognition technology and found that the intervention successfully reduced unplanned hospital readmissions and costs.
This project developed patient-tailored relevant warnings about drug-drug interactions and found that it reduced irrelevant alerts.
This study assessed the usability and impact of inpatient portals on patient experience, engagement, and perceptions of care.
This research pilot tested a sickle cell disease mobile application that was found to reduce acute care visits by patients with the condition.
This research took an existing sepsis-related clinical decision support (CDS) and developed, tested, implemented, and validated a knowledge-based artificial intelligence-enhanced sepsis CDS.
This project assessed the clinical and operational implications of electronic health record downtimes and developed a simulation model to support the creation of effective downtime contingency plans.
