Robert Kim, M.D., was born in Ontario, Canada, but traveled to the U.S. for his education. Dr. Kim received his Bachelor’s degree from Harvard University in Cambridge, MA, and his M.D. degree from Johns Hopkins University School of Medicine in Baltimore, MD. He then completed his internship and residency in Internal Medicine at Duke University Medical Center in Durham, NC. Finally, Dr. Kim completed his Cardiology fellowship at Weill Cornell Medical College/NewYork-Presbyterian Hospital in New York City and joined the faculty full time in 2007. He serves as Director of Consultative Cardiology.
Dr. Kim practices General Cardiology and Cardiovascular Medicine at the NewYork-Presbyterian Hospital/Weill Cornell Medical College campus in New York City. His practice includes patients with hypertension, coronary artery disease and its complications, valvular heart conditions, cardiomyopathies, and those who have undergone heart surgery or interventional procedures. Dr. Kim works in close affiliation with all of the physicians in the Division of Cardiology, including subspecialists in Cardiac Electrophysiology, Heart Failure, Diagnostic and Interventional Cardiac Catheterization, and Non-Invasive Testing.
Dr. Kim teaches the second-year medical students a pathophysiology-based course on cardiovascular disease and is the co-founder of the Quality Improvement Academy at Weill Cornell/NewYork-Presbyterian Hospital.
Measuring Safety and Quality OutcomesCornell Course
Course Overview
Quality improvement (QI) projects generate substantial amounts of data, but raw numbers are often impossible to interpret and difficult to share with others. The key to successful QI initiatives lies not just in collecting data but also in visualizing it in ways that reveal important patterns, detect real improvements, and communicate findings effectively to stakeholders.
In this course, you will leverage essential data visualization tools that help you detect changes and draw valuable conclusions. You'll create and interpret frequency plots, Pareto charts, run charts, and statistical process control (SPC) charts using hands-on Excel exercises with real case study data. You'll discover how to distinguish between meaningful changes and normal variation in your processes, and you'll develop skills to track improvements over time. Finally, you'll explore how to use your data to expand successful pilot projects and sustain gains across larger systems.
To complete this course, you will need access to MS Excel and a basic fluency with Excel, including formatting cells, entering data, generating charts, and applying simple formulas.
You are required to have completed the following courses or have equivalent experience before taking this course:
- Building the Foundation for Safer Care
- Leading Change for Safer Systems
Key Course Takeaways
- Create and interpret frequency plots, Pareto charts, and run charts to visualize data and detect changes
- Apply statistical process control (SPC) charts to detect special cause variation and evaluate system changes
- Develop data-driven strategies to expand and sustain quality improvement changes
How It Works
Course Author
Who Should Enroll
- Healthcare professionals responsible for leading or contributing to quality improvement and patient safety initiatives
- Clinical leaders, physicians, nurses, and advanced practice providers seeking practical quality improvement skills
- Healthcare managers, administrators, and operations leaders responsible for improving clinical and operational performance
- Quality, patient safety, and performance improvement professionals looking to strengthen their knowledge of the Model for Improvement and data-driven change
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