Evaluating Latent Hazards in AI-Enabled Clinical Occupational and Environmental Medicine: A Conceptual Systems-Based Hazard Analysis

Occupational and environmental medicine (OEM) clinicians operate at the intersection of clinical medicine and the legal system. The impact of the clinical decisions and determinations made by OEM clinicians extends far beyond clinical outcomes. The integration of artificial intelligence clinical decision support systems (AI-CDSS) for OEM-specific clinician tasks requires careful consideration of the domain-specific potential harms that may arise from clinician use of this technology in OEM, as such hazards may not be readily apparent using conventional AI safety and risk assessment frameworks for the general healthcare domain. This conceptual systems-based hazard analysis applies the System-Theoretic Process Analysis (STPA) framework to the use of AI-CDSS in clinical OEM, focusing on domain-specific hazards. This analysis identified legal, regulatory, economic, and public safety hazards that should be addressed to ensure responsible and ethical integration of AI-CDSS in clinical OEM.

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Publication Details

Journal
Proceedings of the Human Factors and Ergonomics Society Annual Meeting
Published
2026-09-06
DOI
https://doi.org/10.1177/10711813261485178
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
Field-Weighted Citation Impact
0.00
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article

Evaluating Latent Hazards in AI-Enabled Clinical Occupational and Environmental Medicine: A Conceptual Systems-Based Hazard Analysis

Avishek Choudhury, Zaira S. Chaudhry
Proceedings of the Human Factors and Ergonomics Society Annual Meeting
Artificial Intelligence in Healthcare and Education
article

Evaluating Latent Hazards in AI-Enabled Clinical Occupational and Environmental Medicine: A Conceptual Systems-Based Hazard Analysis

Avishek Choudhury, Zaira S. Chaudhry
article en

Abstract

Occupational and environmental medicine (OEM) clinicians operate at the intersection of clinical medicine and the legal system. The impact of the clinical decisions and determinations made by OEM clinicians extends far beyond clinical outcomes. The integration of artificial intelligence clinical decision support systems (AI-CDSS) for OEM-specific clinician tasks requires careful consideration of the domain-specific potential harms that may arise from clinician use of this technology in OEM, as such hazards may not be readily apparent using conventional AI safety and risk assessment frameworks for the general healthcare domain. This conceptual systems-based hazard analysis applies the System-Theoretic Process Analysis (STPA) framework to the use of AI-CDSS in clinical OEM, focusing on domain-specific hazards. This analysis identified legal, regulatory, economic, and public safety hazards that should be addressed to ensure responsible and ethical integration of AI-CDSS in clinical OEM.

Proceedings of the Human Factors and Ergonomics Society Annual Meeting
West Virginia University (US)
Openalex Percentile: Top 14%
Artificial Intelligence in Healthcare and Education
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