Real-world Examples Help in Interpreting Medical Statistics

Real-world Examples Help in Interpreting Medical Statistics

Instructor: Kristin Sainani
Department/School: Health Research and Policy / School of Medicine
Course: Statistics in Medicine
Audience: Public
Teaching and Learning Approach: Massive Open Online Course (MOOC)

Goals: Kristin Sainani wanted to provide public students with a foundational understanding of probability and statistics as well as to teach students the critical thinking skills they would need to evaluate statistics in medical studies and analyze data.

Approach: Sainani incorporated real-world examples from the medical literature and the popular press into her course. She began each week with a teaser question about a topic (e.g, “Should you be worried about lead in lipstick?”) then guided students through the data to help them learn how to read, interpret and critically evaluate statistics in medical research.

Teaching & Learning Strategies: This was a 9 week course, with one unit of content per week. Each unit contained short instructional videos, typically narrated PowerPoint with digital inking, paired with embedded “knowledge check” quizzing and online homework assignments. The teaching assistants for the course produced a series of supplemental videos in which they demonstrated the proofs for the questions in the embedded quizzes and homework assignments.

Lessons LearnedInitial findings are that this course maintained a much higher percentage of active users than the typical MOOC. VPTL is currently examining data to determine the reasons for this higher-than-normal retention.

Emailed comments from students:

As a volunteer in the field hospital, I passed on Wednesday the hardest 11 hours in my life in Rabaa Eladawya Square in Egypt sieged by bullets and over 2600 dead bodies in the greatest massacre ever known in the Egyptian history when the army and police abrogated the peaceful anti-coup protests. I'm still shocked and don’t believe I’m still alive, but I find it is a must at the course end to present my thanks to Prof. Kristin. I really appreciate her simple, elegant, enthusiastic and passionate presentation of the course material, and I'm proud to be her student. Many thanks.

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Hi Kristin,

I am a retired epidemiologist (30+ years ago) and pediatrician (15 years ago) with a long-standing interest in Vietnam. My wife, an oncologist, and I have been spending 3 months a year in Vietnam for the past 7 years teaching medical professionals -- in my case teaching epidemiology and research methods. We go on our own and receive no financial support, though the experience itself is highly rewarding. I am currently trying to put my epi teaching into an online format.

Over the past year I have taken a number of MOOCs as a student, many of them on statistical topics, and most recently yours on Statistics in Medicine (student name jtay). Your course is one of the best courses I have ever taken on the topics covered -- in any format, and is a model for using the MOOC approach specifically. The careful organization, precise and upbeat delivery, and the interrelated mix of theory and application create an ideal learning environment. I learned a lot. The course clearly represents a lot of hard work and attention to detail, and your pedagogical understanding and caring shine through loud and clear.  Thanks.

In Vietnam I am constantly being asked to teach epi and biostat to new groups. I have strongly recommended that they avail themselves of your course as individual students. I hope the course materials will remain on the web so they can used further.  However, I think for these audiences there may also be value in a blended online/face-to-face course with exercises discussed in class. I think this would help bridge the language barrier and help fill in the "swiss cheese" aspects of spotty undergraduate training in fundamentals. Before I consider this further, I want to be sure I have permission for such a use of your materials. I have no interest in rebranding or in any financial benefit coming from this. It's your work. (If you have time and interest to teach in Vietnam yourself, I'd be happy to make introductions.)

Just for fun, here's a link to an article that bears on many ideas touched on in your course. It came out probably before you were born, but was quite relevant then and probably still is. http://www.nejm.org/doi/full/10.1056/NEJM197402212900806

Thanks again

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Dr. Sainani,

Thank you for this wonderful course on medical statistics. It has the content and the rigor, which has made me a better consumer of medical literature. Now, I actually enjoy perusing the tables in JAMA and NEJM. I wish my biostatistics class in medical school back in 1980 was this good. For the future, I would recommend that you consider offering this class to every U.S. medical school. I strongly doubt that there is another educator as capable as you on medical statistics in the United States. Thank you for all of your efforts.

Plans for Next Iteration of Course: Content developed for this course will be re-used to teach a second iteration of the MOOC, as well as for flipped classroom delivered at Stanford and as a course offered by Continuing Medical Education (CME) to practicing health care professionals.

ABOUT THE TEACHING TEAM

 

Kristin Sainani

Kristin Sainani (née Cobb) is a clinical assistant professor at Stanford University and also a health and science writer. After receiving an MS in statistics and PhD in epidemiology from Stanford University, she studied science writing at the University of California, Santa Cruz. She has taught statistics and writing at Stanford for a decade and has received several Excellence in Teaching Awards from the graduate program in epidemiology.

Michael Hurley
Michael Hurley (TA) completed his Bachelors degree in Materials Science and Engineering from MIT in 2010, and a Master's degree in Clinical Epidemiology at Stanford University in 2012. He is currently a first year medical student at Stanford. His research interests lie in quantifying patient outcomes and the identification of risk factors for disease and post-operative complications using large clinical data sets. At Stanford, he serves as a Teaching Assistant for numerous biostatistics courses and is involved in teaching and tutoring in various other ways. Michael enjoys cooking and traveling in his free time.

Rajhansa Sridhara
Rajhansa Sridhara (TA) completed his Bachelors and Master's in Aerospace Engineering from the Indian Institute of Technology, Bombay in 2011. He then worked for the Global Risk Management division of American Express, where he was one of the analysts responsible for setting the firm's credit risk management strategies based on extensive statistical analysis of past transaction data. He started his MS in Management Science & Engineering at Stanford in 2012. In Stanford, Rajhansa is a tutor for learning-disabled students through the Office of Accessible Education. He also serves on the university's Judicial Affairs panel, and is a consultant for Stanford Consulting. In his free time, he likes to read, learn new languages, and watch westerns.

Michael McAuliffe
Michael McAuliffe is an Instructional Technologist in EdTech, IRT for the Stanford University School of Medicine. He supports a wide range of educational technology operations, projects, and initiatives in support of teaching, learning, and research. Mike joined the School of Medicine in August 2012 and dedicates the majority of his time to the Stanford Medicine Interactive Learning Initiative (SMILI). In this role, Mike collaborates with SoM faculty to design and produce video content for online/hybrid courses delivered to undergraduate medical education, online courses for continuing medical education, online materials for residents and fellows, and MOOCs. Mike also provides instructional design, graphic design, and project planning support to faculty.

Resources

Presentation Creating Online and Blended Teaching Materials -- a Production Primer, Faculty Forum, March 11, 2013
Through Stanford massive online course, students across the world learn how to interpret data Stanford Report, July 22, 2013
‘Statistics in Medicine,’ a free online course... Inside Stanford Medicine, May 28, 2013

Case study contributed by the Office of the Vice Provost for Teaching & Learning and the Stanford School of Medicine