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ACTEX Learning Presents: ACTEX eLearning Webinar: Introduction to Predictive Analytics in Healthcare
The second edition of Ian Duncan’s book: Healthcare Risk Adjustment and Predictive Modeling was published by ACTEX Learning in May 2018, and covers the theory and practice of these two different areas of actuarial practice in the healthcare field.
Predictive analytics has traditionally been used for predicting member cost for the purpose of pricing, rating and underwriting. It is also effective in identifying high-risk cases for population management interventions. Now, with increased access to new models and data sources that have created the opportunity for broader applications, predictive analytics has the potential to dramatically change healthcare for the better.
This webinar covers the basics of predictive analytics in healthcare, with examples from traditional and new applications. We will look at examples of applications in time-series, high-risk patient identification, modeling of patient transitions between health states and predicting terminations of workers’ compensation claimants. You will not need to be an experienced practitioner or predictive modeler to follow the examples.
Learning Objectives:
- Identify the basics of predictive analytics in relation to healthcare.
- Investigate techniques for setting up problems for successful modeling.
- Review best practices in working with data, choosing a model and assessing the results.
- Apply predictive analytics techniques to: time-series, high-risk patient identification, patient transitions and claim terminations.
Who Should Attend This Webinar?
Any actuary, medical or healthcare professional interested in the applications and practice of predictive analytics in health care, health insurance or quality measurement. The attendee does not need to be an experienced practitioner or predictive modeler to follow the examples.
About Your Instructor
Ian Duncan, FSA, FIA, FCIA, FCA, CSPA, MAAA
Ian Duncan is an Adjunct Associate Professor of Actuarial Statistics in the Dept. of Statistics & Applied Probability at the University of California, Santa Barbara and President of Santa Barbara Actuaries Inc. He has over 30 years of experience in healthcare and insurance product design, management, financing, pricing and delivery, and has founded two previous companies to perform predictive modeling and outcomes analysis for healthcare. He is a frequent speaker about health outcomes, predictive modeling and risk adjustment. Mr. Duncan holds a post-graduate degree in economics from Balliol College, Oxford and is a Fellow of the Society of Actuaries, the Institute of Actuaries (London), the Canadian Institute of Actuaries and the Conference of Consulting Actuaries.