PV26 Speakers

Subject to change.

 

 

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Fernando Soares, MD, PhD

Head of Department, Rede D'Or

Dr. Fernando Soares is Head of the Department of Pathology at Rede D’Or and a retired Full Professor at the University of São Paulo (São Paulo, Brazil), and was named Full Professor in Oncology and General Pathology in 2004. He retired from the University in December 2024. Dr. Soares specializes in translational pathology, focusing on predictive markers and biomarkers for tumor diagnosis and prognosis. He has led several research grants, resulting in over 550 peer-reviewed publications.

 

 

SESSIONS

How Rede D'Or Built Latin America's Most Ambitious Digital Pathology Transformation
   Sat, Oct 17
   12:45 PM - 1:05 PM PT
  Seaport H

Background: Large-scale implementation of digital pathology (DP) and artificial intelligence (AI) remains challenging, particularly across geographically distributed healthcare networks. Rede D'Or Hospitals, the largest hospital network in Brazil, underwent a rapid DP transformation. This study reports the implementation of a fully digital pathology system across a multi-site network.

Methods: We describe the deployment of whole slide imaging (WSI) and AI-enabled workflows across >70 hospitals in 8 Brazilian states, processing >2 million slides annually. Implementation included parallel multi-site rollout, specialty-based onboarding, integration with a laboratory information system (LIS), and incorporation of AI tools. Operational strategies included cross-functional governance, daily stand-up meetings, and staged workflow integration.

Results: A total of 13 scanners were deployed across three states, achieving peak throughput >8,000 slides/day. Full digitization across all subspecialties was completed in 9 months, exceeding the initial 3-year timeline. Adoption among 117 pathologists was rapid and universal. Turnaround time improved by 10-12 hours on average, with increased productivity and a projected 20% rise in case volume without additional staffing. Cases delivered within the 3-day SLA reached 97%. AI integration enabled automated case prioritization and seamless LIS reporting. Key challenges, including regulatory requirements, LIS interoperability, and data infrastructure, were addressed through coordinated efforts.

Conclusions: Rapid, large-scale deployment of DP and AI is feasible in complex healthcare systems. Leadership alignment, integrated workflows, and scalable infrastructure are critical to success.

Learning Objectives:

  1. Describe strategic steps required for large-scale implementation of digital pathology across multi-site healthcare networks.
  2. Evaluate the impact of integrating AI tools into pathology workflows on efficiency, turnaround time, and diagnostic processes
  3. Identify operational, technical, and regulatory challenges associated with deploying digital pathology and AI at scale.
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