Integrating AI into Clinical Workflows: A Simulation Study on Implementing AI-aided Same-day Diagnostic Testing Following an Abnormal Screening Mammogram

Presentation Time: 08:45 AM - 09:00 AM

Abstract Keywords: Informatics Implementation, Workflow, Cancer Prevention
Primary Track: Applications
Programmatic Theme: Clinical Informatics

Artificial intelligence (AI) shows promise in clinical tasks, yet its integration into workflows remains underexplored. This study proposes an AI-aided same-day diagnostic imaging workup to reduce recall rates following abnormal screening mammograms and alleviate patient anxiety while waiting for the diagnostic examinations. Using discrete simulation, we found minimal disruption to the workflow (a 4% reduction in daily patient volume or a 2% increase in operating time) under specific conditions: operation from 9 am to 12 pm with all radiologists managing all patient types (screenings, diagnostics, and biopsies). Costs specific to the AI-aided same-day diagnostic workup include AI software expenses and potential losses from unused pre-reserved slots for same-day diagnostic workups. These simulation findings will inform the implementation of the AI-aided workup at our institution, with future research focusing on its potential benefits, including improved patient satisfaction, reduced anxiety, lower recall rates, and shorter time to cancer diagnoses and treatment.

Speaker(s):
William Hsu, PhD
University of California, Los Angeles

Author(s):
Anne Hoyt, M.D.; Vladimir Manuel, MD - University of California, Los Angeles; Moira Inkelas, MPH, PhD - University of California, Los Angeles; Cleo Maehara, MD, MMSc - University of California, Los Angeles; Mehmet Ulvi Saygi Ayvaci, PhD - University of Texas at Dallas; Mehmet Eren Ahsen, PhD - University of Illinois at Urbana-Champaign; William Hsu, PhD - University of California, Los Angeles;