The rate of diagnostic error in medical practice is approximately 10-17% in the United States. Acute coronary syndrome (ACS) is a leading missed diagnosis, risking the safety of approximately 100,000 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 ?blunt 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 an ACS 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 a patient dashboard designed to optimize ?cognitive hygiene? surrounding diagnostic decision-making workflows for suspected ACS 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 qualitative and quantitative research skills relevant to cognitive informatics interventions that are integrated into clinical workflow; 3) gain skills in biomedical informatics; and 4) develop expertise in quality improvement methods. 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.

Public Health Relevance

Patients presenting to the emergency department with cardiovascular disease are too often subject to diagnostic error, putting them at risk for life-threatening adverse events. This study will develop health information technology tools to improve physicians' diagnostic performance by reducing the cognitive demands imposed by our complex healthcare system, giving physicians more opportunity to think about their patients.

Agency
National Institute of Health (NIH)
Institute
Agency for Healthcare Research and Quality (AHRQ)
Type
Clinical Investigator Award (CIA) (K08)
Project #
5K08HS024598-02
Application #
9338137
Study Section
HSR Health Care Research Training SS (HCRT)
Program Officer
Willis, Tamara
Project Start
2016-09-01
Project End
2018-04-22
Budget Start
2017-09-01
Budget End
2018-04-22
Support Year
2
Fiscal Year
2017
Total Cost
Indirect Cost
Name
Columbia University (N.Y.)
Department
Internal Medicine/Medicine
Type
Schools of Medicine
DUNS #
621889815
City
New York
State
NY
Country
United States
Zip Code
10032
Wasson, Lauren T; Cusmano, Amberle; Meli, Laura et al. (2016) Association Between Learning Environment Interventions and Medical Student Well-being: A Systematic Review. JAMA 316:2237-2252