A National Web Conference on Applying Advanced Analytics in Clinical Care

Event Date
October 14, 2020 - 2:00pm–3:30pm EDT


AHRQ hosted a web conference on Wednesday, October 14, 2020 from 2:00 – 3:30 p.m. EST, to discuss how advanced analytics can be applied into clinical care. Specifically, the panel will feature findings from research projects that applied machine learning and natural language processing techniques to effectively analyze unstructured text information and process data from multiple sources for identification of patients who would benefit from treatments or interventions. Eligible providers can earn up to 1.5 CE/CME contact hours for participating in the live web conference.


Alexander Turchin

Alexander Turchin, MD, MS
Associate Professor of Medicine, Harvard Medical School; Director of Informatics Research, Division of Endocrinology, Brigham and Women’s Hospital

Judith Dexheimer

Judith Dexheimer, PhD
Associate Professor, Division of Emergency Medicine, Division of Biomedical Informatics, Cincinnati Children’s Hospital Medical Center

Michael Avidan

Michael S. Avidan, MBBCh FCASA
Chair, Department of Anesthesiology, Washington University School of Medicine


Chun-Ju (Janey) Hsiao

Chun-Ju (Janey) Hsiao, PhD
Health Scientist Administrator, Division of Digital Healthcare Research, Center for Evidence and Practice Improvement


Learning Objectives:

At the conclusion of this web conference, participants should be able to:

  1. Review how machine learning algorithms in conjunction with natural language processing can be used to identify patients at high risk for death.
  2. Evaluate the benefits of using EHR-integrated machine learning algorithms to identify patients with epilepsy who could benefit from surgery.
  3. Describe how data mining and machine learning can help forecast adverse outcomes among surgical patients.
  4. Discuss different advanced data analytic techniques for improving the quality, safety, effectiveness, and efficiency of care.
  5. Identify how to best integrate advanced data analytics into clinical practice.

Event Materials:

  • Presentation Slides (PDF, 3.82 MB). (Persons using assistive technology may not be able to fully access information in this presentation. For assistance, please contact Corey Mackison).
  • Q&As (PDF, 152.86KB)


If you have any questions, please send an email to DigitalHealthcareResearch@ahrq.hhs.gov.