Evidence-Based Risk Communication in Annals of Internal Medicine

Dr. Daniella Zipkin, an Associate Professor of Medicine at Duke University Medical Center, is one of 14 authors who contributed to “Evidence-Based Risk Communication: A Systematic Review,” published in Annals of Internal Medicine in August 2014.

“Evidence-Based Risk Communication: A Systematic Review” reviewed 84 articles focusing on 91 studies that assessed different methods of communicating risks and benefits to patients regarding their health care options. The goal of the review was to identify the communication methods that maximize patient understanding, which is a component of evidence-based medicine (EBM).

The systematic review concluded that visual aids, such as bar graphs or displays of icons, are capable of increasing patient understanding and satisfaction. Other presentation methods reduced patient understanding, such as “number needed to treat” statistics, which are commonly used in health care to express the average number of people who need to receive treatment in order to prevent an additional negative outcome.

In addition to her published research, Dr. Daniella Zipkin also promotes evidence-based medicine in her work as a member of the Evidence-Based Medicine Task Force within the Society of General Internal Medicine.

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The Basics of Evidence-Based Medicine

Daniella Zipkin serves as an Associate Professor of Medicine at Duke University Medical Center in Durham, North Carolina. Over the course of her career, Daniella Zipkin has made numerous contributions to the Evidence-Based Medicine (EBM) movement though research, instructional courses, and national presentations. EBM is an approach to patient care that focuses on integrating patient values, clinical experience, and best available research.

In order to effectively utilize EBM, medical professionals must remain well versed in the most recent and relevant data, and communicate the evidence effectively to patients. Dr. Zipkin has reviewed the literature on best practices regarding presenting risks and benefits to patients, and the review was published in the Annals of Internal Medicine in 2014, accessible at http://annals.org/issue.aspx?journalid=90&issueid=930674.

This review has informed the production of Bottom Line evidence summaries, available through the Web Only section of the Journal of General Internal Medicine’s website, at http://www.sgim.org/web-only, and then choosing the “Bottom Line Summary” box.

EBM begins and ends with the patient. Bottom Line summaries can be used by clinicians in encounters with patients, to aid in communicating high impact data in a way that patients can apply to their own experience.

Utah’s Snow is Among the Greatest on Earth

A graduate of the University of California, San Francisco School of Medicine, Daniella Zipkin, MD, is currently an assistant professor at the Duke University Medical Center, where she teaches a curriculum in evidence-based medicine. In her personal life, Dr. Daniella Zipkin is an avid snowboarder with a special affinity for the powdery snow of Utah’s mountains.

Marketed as the greatest on earth, Utah’s snow is well known for being dry and light, which produces the high-quality powder that attracts skiers from around the world. In addition, Utah receives many significant snow storms each year, which increases the number of powder days and often leads to long seasons of very enjoyable skiing. In fact, Utah’s snow is so fun to ski that in 2010 it took seven of Ski Magazine’s top 10 rankings for snow.

The reason for Utah’s excellent skiing is largely the result of its geography. Because most of the state is considered desert, it is quite arid, which saps its snow of much of its moisture and allows it to remain light and fluffy. Also, the Great Salt Lake in northern Utah is so large that it creates a lake effect on regional snow storms and leads to huge accumulations in the surrounding mountains. These facts, combined with Utah’s large mountain peaks, make the state’s resorts a world-class destination for ski and snow enthusiasts.