Acute Care


Using Large Language Models to Identify Social Determinants of Health to Enhance Healthcare Services and Equity

Description

This research explores using natural language processing and generative AI to capture and structure social determinants of health from patient narratives, aiming to improve data completeness and quality, enhance clinical decision support, and reduce the manual burden on clinical staff in routine care.

Grant Number
R21 HS029991
Principal Investigator(s)

Empower NICU - A Bridge to Resources for Adjusting and Coping with Emotions (EmBRACE)

Description

This research will develop, evaluate, and test the efficacy of Empower NICU – A Bridge to Resources for Adjusting and Coping with Emotions (EmBRACE), a mobile health application designed to screen and monitor psychological symptoms in parents of infants hospitalized in the neonatal intensive care unit, identify those at risk, and connect parents with services, information, support, and resources.

Grant Number
R21 HS029554
Principal Investigator(s)

Digital EMS Point-of-Care Innovation to Improve Rural STEMI Outcomes

Description

This research will develop, implement, refine, and evaluate an app to support clinical decisions for ST-Elevation Myocardial Infarction care in rural areas by emergency medical services providers, reducing the time between first medical contact and reperfusion therapy to reduce morbidity and mortality, and improve health outcomes.

Grant Number
R21 HS029234
Principal Investigator(s)

Virtual Reality at the Point of Care to Increase Uptake of Medications for Opioid Use Disorder (MOUD) in the Emergency Department

Description

This research is developing and testing VR-Choice, an immersive virtual reality experience designed to increase patient willingness to engage in shared decision-making for medications for opioid use disorder after being treated for an opioid-related overdose in the emergency department.

Grant Number
R21 HS029536
Principal Investigator(s)

Building and Implementing a Predictive Decision Support System Based on a Proactive Full Capacity Protocol to Mitigate Emergency Department Overcrowding Problems

Description

This research will use deep learning models to move a reactive full capacity protocol (FCP) for emergency department (ED) overcrowding interventions into a proactive FCP by predicting patient flow measures so that interventions may be activated to avoid ED overcrowding.

Grant Number
R21 HS029410
Principal Investigator(s)

Precision Emergency Medicine: Setting a Research Agenda

Description

This research will use a consensus conference format during the 2023 Society for Academic Emergency Medicine conference to develop and publish an actionable research agenda for precision emergency medicine with a focus on improving patient outcomes by using a patient’s genomic, biologic, environmental, and public health data.

Grant Number
R13 HS029275
Principal Investigator(s)