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OU Epidemiology Professor to Present at Upcoming CDC Public Health Webinar

OU Epidemiology Professor to Present at Upcoming CDC Public Health Webinar


Event date: 3/24/2022 2:00 PM - 3:00 PM iCal Export

Hear from our own Aaron Wendelboe, Ph.D., Epidemiologist during a CDC Public Health Webinar Series on Blood Disorders. Dr. Wendelboe will join Duke University School of Medicine's Dr. Ortel presenting on March 24 from 2-3 p.m. for a webinar titled "Conducting Surveillance for Venous Thromboembolism Using Traditional and Novel Methods."

About This Event

The Division of Blood Disorders is proud to offer this webinar series, providing evidence-based information on new research, emerging issues of interest in blood disorders, as well as innovative approaches to collaboration.

March 24, 2022 • 2:00–3:00 PM ET | Register Here

Presenters:

Aaron M. Wendelboe, PhD
Edward E. and Helen T. Bartlett Chair in Public Health
Professor, Department of Biostatistics and Epidemiology
University of Oklahoma Health Sciences Center

Thomas Lee Ortel, MD, PhD
Chief, Division of Hematology
Professor of Medicine and Pathology
Member of the Duke Cancer Institute
Duke University School of Medicine

Moderator:

Karon Abe, PhD
Captain, US Public Health Service
Chief, Epidemiology & Surveillance Branch, Division of
Blood Disorders, National Center on Birth Defects and Developmental Disabilities, Centers for Disease Control and Prevention

In this webinar, Drs. Wendelboe and Ortel will describe how novel methods, such as natural language processing, might be incorporated into surveillance systems for venous thromboembolism (VTE). This work is part of a larger collaborative project between the U.S. Centers for Disease Control and Prevention (CDC), the University of Oklahoma, and Duke University. The original surveillance projects, developed in Oklahoma County, Oklahoma, and Durham, North Carolina, used active case finding methods with manual review of diagnostic imaging reports to identify VTE cases. The investigators recently assessed whether a natural language processing methodology, known as IDEAL-X, that automatically classifies cases of VTE from reading unstructured text from diagnostic imaging records could perform as well as their traditional manual case-finding methodology.

The following topics will be discussed:

  • The process by which these novel methods for VTE case finding are being validated against traditional gold standard methods
  • The ability to apply this approach to unique patient populations and less common clinical manifestations of VTE
  • The ability to monitor impact on VTE outcomes following the introduction of new preventive strategies or changes in therapeutic management approach
  • Perspectives for the future of surveillance in VTE
  •  

Learning Objectives:

  1. State the importance of VTE as a public health condition
  2. Describe the importance of conducting public health surveillance for VTE and how surveillance can contribu

Documents to download