Rapid Deployment of Whole Slide Imaging for Primary Diagnosis in Surgical Pathology at Stanford Medicine: Responding to Challenges of the COVID-19 Pandemic

Arch Pathol Lab Med. 2023 Mar 1;147(3):359-367. doi: 10.5858/arpa.2021-0438-OA.

Abstract

Context.—: Stanford Pathology began stepwise subspecialty implementation of whole slide imaging (WSI) in 2018 soon after the first US Food and Drug Administration approval. In 2020, during the COVID-19 pandemic, the Centers for Medicare & Medicaid Services waived the requirement for pathologists to perform diagnostic tests in Clinical Laboratory Improvement Amendments (CLIA)-licensed facilities. This encouraged rapid implementation of WSI across all surgical pathology subspecialties.

Objective.—: To present our experience with validation and implementation of WSI at a large academic medical center encompassing a caseload of more than 50 000 cases per year.

Design.—: Validation was performed independently for 3 subspecialty services with a diagnostic concordance threshold above 95%. Analysis of user experience, staffing, infrastructure, and information technology was performed after department-wide expansion.

Results.—: Diagnostic concordance was achieved in 96% of neuropathology cases, 100% of gynecologic pathology cases, and 98% of immunohistochemistry cases. After full implementation, 8 high-capacity scanners were operational, with whole slide images generated on greater than 2000 slides per weekday, accounting for approximately 80% of histologic slides at Stanford Medicine. Multiple modifications in workflow and information technology were needed to improve performance. Within months of full implementation, most attending pathologists and trainees had adopted WSI for primary diagnosis.

Conclusions.—: WSI across all surgical subspecialities is achievable at scale at an academic medical center; however, adoption required flexibility to adjust workflows and develop tailored solutions. WSI at scale supported the health and safety of medical staff while facilitating high-quality patient care and education during COVID-19 restrictions.

MeSH terms

  • Aged
  • COVID-19 Testing
  • COVID-19*
  • Female
  • Humans
  • Image Interpretation, Computer-Assisted / methods
  • Medicare
  • Microscopy / methods
  • Pandemics / prevention & control
  • Pathology, Surgical* / methods
  • United States