Hopkins team awarded AHRQ patient safety learning lab grant
Researchers from the Johns Hopkins Department of Emergency Medicine and the Malone Center for Engineering in Healthcare have teamed up to design and develop a patient safety learning laboratory focused on improving emergency department (ED) care.
Funded by a $2.45 million grant from the Agency for Healthcare Research and Quality (AHRQ), the Connected Emergency Care (CEC) Patient Safety Learning Lab at Johns Hopkins will use systems engineering methods to reduce health and financial harm for ED patients, with an initial focus on patients with lower respiratory tract infections.
Patient safety is of particular concern in a fast-paced, high-volume emergency department setting. According to the project proposal, the research team plans to harness electronic health record (EHR) data to give clinical care teams real-time and predictive insights for patient care. The lab’s main objective is to mitigate problems caused by suboptimal diagnosis, treatment, and disposition (admission vs. discharge) decisions using advanced data science methods and EHR-integrated clinical decision support (CDS).
With these tools, the team will establish a connected (closed-loop) emergency care system that aims to make patient care safer, higher quality, and more affordable.
The four-year project will be led by Scott Levin, associate professor of emergency medicine and director for systems and operations at the Malone Center, and Jeremiah Hinson, assistant professor of emergency medicine. The cross-disciplinary research team will include Malone staff and faculty from computer science and civil engineering, as well as collaborators from the Maryland Institute College of Art (MICA) Center for Social Design.
The grant is part of a larger AHRQ initiative to support the development of several innovative learning laboratories where teams will work to address various patient safety-related challenges. AHRQ requires these labs to use a five-phase methodology (problem analysis, design, development, implementation, and evaluation) that is a simplification of the phases that larger-scale systems engineering projects entail.