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Session Evaluation

AOHC 2026 Concurrent Sessions

Clinical Occupational and Environment Medicine

405 - Occupational Health Informatics an Augmented Intelligence

Wednesday, April 22, 2026
10:15 AM - 11:15 AM CT
Location: Sheraton Ballroom V
Claim 1.0 CME

All relevant financial relationships have been mitigated.


Disclosure(s):

Jacques Al Tawil, MD: No financial relationships to disclose
William B. Perkison, MD MPH: No financial relationships to disclose
Session Description: This session will explore the emerging field of Occupational Health Informatics, highlighting how data-driven approaches can transform employee health programs. Attendees will gain an overview of data mining, visualization, and analysis, with emphasis on applying the Data–Information–Knowledge–Wisdom (DIKW) framework to enhance understanding and decision-making. The presentation will demonstrate how artificial intelligence tools and technologies can support clinical decision support systems, predictive modeling, and preventive strategies. By showcasing practical applications of data and AI, this session will illustrate how informatics augments clinical intelligence to optimize workplace health outcomes, support proactive interventions, and improve overall employee well-being.

Educational Gaps: Many physicians rely on traditional clinical assessments without leveraging data analytics or AI tools. This session addresses the gap by showing how informatics, predictive modeling, and decision support can enhance proactive, evidence-based occupational health care.

Is this session being sponsored by an ACOEM Section or Component?: No

Has this session previously been presented?: no

The AOHC 2026 theme is Healthy workers. Healthy world: By harnessing the power of data and AI, this session highlights how occupational health informatics can transform care.
Equipping physicians with tools to predict risks and promote well-being ensures healthier workers—whose vitality drives safer workplaces, stronger communities, and a healthier world.

Learning Objectives:

  • Upon completion, participants will be able to describe the basic concepts of occupational health informatics, including data mining, visualization, analysis, and the DIKW framework.
  • Upon completion, participants will be able to identify how artificial intelligence tools and predictive models can enhance clinical decision support in occupational health.
  • Upon completion, participants will be able to explain how informatics-driven approaches support preventive strategies and improve employee health outcomes.