Improving the Screening Criteria that Trigger an Early ECG to Diagnose STEMI

Vanderbilt University Medical Center, Nashville TN

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Abstract

PROJECT SUMMARY AND ABSTRACT I am an Assistant Professor of Emergency Medicine at Vanderbilt University in the 3rd year of an NHLBI funded emergency care K12 training program. My long term goal is to become an independent investigator who uses clinical operations and epidemiological research to evaluate best practice implementation and develop multi- center studies to test bioinformatics supported system-level clinical interventions. My short term goal is to understand the clinical process steps and criteria used in emergency departments (EDs) to: 1) identify patients with ST-elevation myocardial infarction (STEMI), and 2) develop interventions to improve ED screening for STEMI. STEMI is a critical life threatening disease for which rapid diagnosis and treatment is associated with reduced mortality and better outcomes. As a result, clinical guidelines recommend an ECG be obtained within 10 minutes of arrival. Through the preliminary analysis of ED diagnostic performance relating to STEMI, I found facility-level implementation varies in terms of which patients receive an early ECG, how screening criteria are integrated into early ED care, and how well EDs capture patients with STEMI. Thus practice variation may expose patients to diagnostic delay and worse outcomes solely based on which ED they enter for care. This application for a K23 Mentored Patient-Oriented Research Career Development Award describes a tailored plan for me to achieve these career goals. My progression will be guided by the primary mentorship of Dr. Alan Storrow, a successful funded mentor and expert in the evaluation of ED patients with acute cardiovascular diseases. The overarching hypothesis for this proposal is that ED facility, screening method, and patient population characteristics impact the timely diagnosis and treatment of STEMI in US EDs. The completion of these aims will inform a more precise STEMI screening predictive model to identify ED patients in need of an early ECG to diagnose STEMI upon ED arrival. Specifically, we will more clearly quantify variability in screening criteria; investigate the relationship between facility, screening process, and patient population diversity and screening performance (measured as the missed case rate); and compare differences in the timeliness of care between early-captured and missed case STEMI patients. At the conclusion of this award, I will have a strong foundation in applying clinical epidemiology, clinical operations analysis, and applied biomedical informatics to: 1) study gaps in cardiovascular disease clinical practice, and 2) design interventions to improve clinical performance for individual patients.