Statistics for Medical Professionals

This course seeks to fulfill the need in the clinical community to better understand medical statistics as it pertains to practicing evidence based medicine, communicating treatment outcome probability to patients and interpreting the results of studies and scientific papers, and in turn improving quality of patient care. This applies to all specialties in various settings of practice.

This course is designed to meet the educational needs of an international audience of physicians, residents and medical researchers in all specialties.

• Release Date: September 23, 2014
• Expiration Date: September 22, 2016
• Estimated Time to Complete: 23.50 hours
• CME Credits Offered: 23.50
• Registration Fee: $25.00

• Review the information below and complete the entire activity
  • Complete the CME post-test, CME assessment survey, and attestation question at the end of the course
  • You must receive a score of 75% or higher on the 30 question post-test in order to receive a CME certificate. You will have two attempts per question (or one attempt for questions with only two options) to pass the post-test.
  • Once you attest to completing the entire online activity and have scored 75% or higher, your CME Certificate will be generated automatically and will be available on your Dashboard page.
• *Participation in discussion forums, practice quizzes, content marked OPTIONAL, and additional readings are not certified for AMA PRA Category 1 Credit™.

• At the conclusion of this activity, participants should be able to:
  • Develop strategies to enable translation of medical research into practicing evidence-based medicine through the following statistical methods: understanding bias, random variation, correctly interpret P values, basic probability and conditional probability, spot statistical errors, understand correlated data.
  • Develop strategies to use specific statistical tests, understand basic regression modeling, and Bayesian inference.
  • Develop strategies to effectively communicate prognosis and treatment probabilities to patients.
  • Develop strategies to enable consistent interpretation of research data and provide correct information on study results.

• Unit 1: Descriptive Statistics and Looking at Data
• Unit 2: Review of Study Designs; Measures of Disease Risk and Association
• Unit 3: Probability, Bayes’ Rule, Diagnostic Testing
• Unit 4: Probability Distributions
• Unit 5: Statistical Inference
• Unit 6. P-values (errors, statistical power, and pitfalls)
• Unit 7. Statistical Tests
• Unit 8: Regression Analysis
• Unit 9: Regression II: Logistic Regression, Cox Regression

• The following planners, speakers, authors and reviewers have indicated that they have no relationships with industry to disclose relative to the content of this activity:
  • Charles Prober, MD
    Senior Associate Dean, Medical Education
    Stanford School of Medicine
    Course Director
  • Kristin Sainani, PhD
    Clinical Assistant Professor, 
    Health Research and Policy
    Stanford School of Medicine
    Co-Course Director and Presenter
• Reviewers:
  • Irina Tokareva, RN, BSN, MAS
    Curriculum and Outcomes Manager
    Stanford Center for Continuing Medical Education
  • Linda G. Baer, MSPH, CCMEP
    Director, CME
    Stanford Center for Continuing Medical Education

• Mike McAuliffe
  Stanford EdTech
• Greg Bruhns
  Stanford Online

• This course requires the use of the current version of either Chrome or Firefox.
• You must have javascript enabled.

The Stanford University School of Medicine is accredited by the Accreditation Council for Continuing Medical Education (ACCME) to provide continuing medical education for physicians.

The Stanford University School of Medicine designates this enduring material for a maximum of 23.50 AMA PRA Category 1 Credits™. Physicians should claim only the credit commensurate with the extent of their participation in the activity.

The Stanford University School of Medicine has received and has used undesignated program funding from Pfizer, Inc. to facilitate the development of innovative CME activities designed to enhance physician competence and performance and to implement advanced technology. A portion of this funding supports this activity.

California Assembly Bill 1195 requires continuing medical education activities with patient care components to include curriculum in the subjects of cultural and linguistic competency. It is the intent of the bill, which went into effect July 1, 2006, to encourage physicians and surgeons, CME providers in the State of California and the Accreditation Council for Continuing Medical Education to meet the cultural and linguistic concerns of a diverse patient population through appropriate professional development. The planners and speakers of this CME activity have been encouraged to address cultural issues relevant to their topic area. The Stanford University School of Medicine Multicultural Health Portal also contains many useful cultural and linguistic competency tools including culture guides, language access information and pertinent state and federal laws.

You are encouraged to visit the portal: http://lane.stanford.edu/portals/cultural.html

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If you are having technical problems (video freezes or is unplayable, can't print your certificate, etc.) you can submit a Help Request to the OpenEdX Team. If you have questions related to CME credit, requirements (Pre-test, Post-test, Evaluation, Attestation) or course content, you can contact the CME Online support team at cmeonline@stanford.edu

1. Physician Numeracy: Essential Skills for Practicing Evidence-based Medicine. Goutham Rao, MD, Fam Med 2008;40(5):354-8
2. How can good randomized controlled trials in leading journals be so misinterpreted? Frank J. Veith, MD, J Vasc Surg 2013;57:3S-7S.
3. Numeracy and Medicine: Key Family Physician Attitudes about Communicating Probability with Patients. Robert Gramling, MD, Jennifer E. Irvin, PhD, Justin Nash, PhD, Christopher Sciamanna, MD, MPH and Larry Culpepper, MD, MPH. J Am Board Fam Med November 1, 2004 vol. 17 no 6.
4. Practical and statistical issues in missing data for longitudinal patient reported outcomes. Melanie L Bell and Diane L Fairclough. Stat Methods Med Res published online 19 February 2013
5. Evaluating Mastery of Biostatistics for Medical Researchers: Need for a New Assessment Tool. Felicity Enders. Clin Trans Sci 2011; Volume 4: 448–454