The ultimate goal of this project is to improve cardiovascular health by using advanced medical informatics to reduce procedure-associated infections. This is important because cardiac device infections are a common, highly morbid, and costly complication of electrophysiology procedures, yet no standardized programs exist to reduce them. The research in this project closes this important gap by creating an electronic tool to automatically detect cardiac device infections and a second tool to identify actionable risk factors for procedure-associated cardiac device infections that can be targeted with prevention interventions to reduce future infections. The PI, Dr. Branch-Elliman, has experience using advanced medical informatics to detect other types of healthcare-associated infections and also has expertise in infection prevention and antimicrobial stewardship in the cardiac electrophysiology laboratory and is thus ideally suited to lead the proposed investigations. The Specific Aims are: Aim 1: Using advanced medical informatics, to develop an electronic tool that automatically flags procedure-related cardiac device infections with greater than 95% accuracy. The tool will be based on universally collected clinical variables, to ensure that it can be applied across diverse electronic medical systems.Aim 2: Using advanced medical informatics and logistic regression, to identify actionable procedure-associated risk factors for cardiac device infections. Actionable risk factors are variables that can be targeted by infection prevention strategies, such as rescheduling the procedure if a patient is febrile and likely to have an active infection.
|Program type||Institute - Data Grant|
|Effective start/end date||04/01/2017 → 03/31/2018|