Advancements in Interoperability: Achieving Anatomic Pathology Reports That Adhere to International Standards and Are Both Human-Readable and Readily Computable.

IF 3.3 Q2 ONCOLOGY JCO Clinical Cancer Informatics Pub Date : 2025-02-01 Epub Date: 2025-02-05 DOI:10.1200/CCI-24-00180
Walter S Campbell, Brian A Rous, Stefan Dubois, Paul A Seegers, Rajesh C Dash, Thomas Rüdiger, Suzanne Santamaria, Elaine Wooler, James Case, Lazslo Igali, Mary E Edgerton, Ross W Simpson, Ekaterina Bazyleva, George Birdsong, Richard Moldwin, Timothy R Helliwell, Peter Paul Yu, John Srigley
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引用次数: 0

Abstract

Purpose: Over the past 50 years, multiple pathology organizations worldwide have evolved in cancer histopathology reporting from subjective, narrative assessments to structured, synoptic formats using controlled vocabulary. These reporting protocols include the required data elements that represent the minimum set of evidence-based, clinically actionable parameters necessary to convey the diagnostic, prognostic, and predictive information essential for patient care. Despite these advances, the synoptic reporting protocols were not harmonized across the various pathology organizations. Cancer pathology continues to be widely reported and stored in free-text format, or without encoded data such that it is neither computable nor interoperable across organizations.

Methods: In 2020, SNOMED International created the Cancer Synoptic Reporting Working Group (CSRWG). This resulted in international collaboration across multiple pathology organizations. CCRWG's mission was to use SNOMED Clinical Terms (CT) concepts to represent the required content within the College of American Pathologists (CAP) and International Collaboration on Cancer Reporting (ICCR) published pathology reporting protocols.

Results: In late 2023, the CSRWG published over 1,300 new or revised SNOMED CT concepts to represent all required pathology cancer data elements for adult and pediatric solid tumors in both CAP and ICCR using the semantic principles of the SNOMED-CT concept model. Thus, computability and interoperability would be broadly established.

Conclusion: This work brings to fruition the longstanding desire for an international, interoperable, human- and machine-readable cancer pathology report for use in patient care, health care quality improvement, population health, public health surveillance, and translational and clinical trial research. The following report describes the project, its methods, and applications in the stated use cases.

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