OnDemand: Understanding the Why: A Primer on Using Predictive Modeling to Inform Educational Outcomes

In medical education, we frequently ask whether or not an activity was successful, that is, whether it improved outcomes. But rarely do we ask why. If an activity was successful, do we know the formula to ensure this success continues in future activities? Conversely, if an activity was less than successful, do we know which barriers prevented improvement?

Factors such as learner demographics, activity format, therapeutic area, question wording, knowledge, and confidence can influence responses to behavior questions or other endpoints. Being able to answer the “why” related to educational outcomes is an important component of developing activities that ensure best practices are being implemented, resulting in improved patient outcomes.

In our complimentary webinar – Understanding the Why: A Primer on Using Predictive Modeling to Inform Educational Outcomes – Dr. Jamie Reiter provides an overview of predictive modeling, as well as how to conduct the most common form of predictive modeling (i.e., regression) using Excel, as well as a few vetted online calculators. Note: Some knowledge of, or at least comfort with, statistics is recommended.

By the end of this webinar, participants will be able to:

  • Understand criteria for conducting different predictive modeling analyses.
  • Identify activities and variables to use for predictive modeling analysis.
  • Conduct a basic predictive modeling analysis.

Simply fill out the form to access our OnDemand webinar!

Presenter: Jamie Reiter, PhDAbout the Presenter:
Jamie Reiter, PhD is Director of Educational Outcomes at CME Outfitters, LLC. She earned her PhD from the Department of Cognitive Sciences at UC Irvine, with an emphasis on data analysis and developing mathematical models for analyzing neuropsychological data in patients with dementia. Prior to CME Outfitters, Dr. Reiter was Director of Biostatistics and Research at CME LLC; developed and taught introductory and intermediate biostatistics courses for UC San Diego Extension; and worked as statistician, medical writer, and scientist for the pharmaceutical industry, academic and research institutions, medical education providers, medical societies, and contract research organizations.

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