Improving Diagnosis of Cardiovascular Disease in the Emergency Department Using Cognitive Informatics Tools

DESCRIPTION (provided by applicant): The rate of diagnostic error in medical practice is approximately 10-17% in the United States. Acute coronary syndrome (ACS) and congestive heart failure (CHF) are leading missed diagnoses, risking the safety of tens of thousands of patients every year. The vast majority of diagnostic errors can be attributed to cognitive errors, which stem from the characteristic complexity of our healthcare system. Physicians are challenged to make diagnoses by synthesizing imperfect information and by drawing on knowledge while under time pressure and while juggling high mental workloads driven by dynamic situations, uncertain conditions, complicated technology interactions, and multiple parallel tasks. As such, error has been described as a cognitive phenomenon that is an inevitable and perhaps even normal consequence of work in such a system. This system needs to change. I propose that accomplishing 'cognitive hygiene' - defined here as a state of clinical workflow that optimizes physicians' cognitive capacities to engage in expert diagnostic decision making - will improve patient safety. Although physicians' cognitive processing occurs at the 'sharp end' of health care delivery, it is truly the interrelatedness of cognitive factors and 'blut end' systems factors that drive diagnostic error. The objective of this study is to develop a system-based, evidence-based health information technology (HIT) tool grounded in cognitive informatics theory and methodology that will improve diagnosis of cardiovascular disease in the emergency department (ED). The study aims are: 1) to conduct a problem analysis of ED physicians' information-seeking behavior; 2) to design and then iteratively develop and evaluate the usability of ACS and CHF patient dashboards in the electronic health record (EHR) for ED physicians; and 3) to implement a dashboard-based intervention and evaluate its effect on ED physician diagnostic performance. The hypothesis is that patient dashboards designed to optimize 'cognitive hygiene' surrounding diagnostic decision-making workflows for suspected cardiac patients will improve ED physician diagnostic performance. The candidate, Lauren Taggart Wasson, MD, MPH, is a cardiologist and investigator at Columbia University Medical Center. The candidate proposes a program of career development and training to achieve the following objectives: 1) develop expertise in cognitive and decision-making sciences; 2) gain skills in biomedical informatics; 3) develop expertise in quality improvement methods; and 4) gain skills in analytics relevant to cognitive informatics interventions that are integrated into clinical workflow. The candidate's mentors, Dr. Karina Davidson, Dr. Henry Ting, Dr. Vimla Patel, Dr. David Vawdrey, and Dr. Lena Mamykina, together contribute expertise on workflow redesign for quality improvement and on cognitive informatics. This mentorship team will work closely together to guide Dr. Wasson toward her goal of becoming an independent health services researcher focused on increasing the quality of physician performance to improve patient safety, through innovative designs, methods, and tools.