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What Is An AP Laboratory Information System (APLIS) and What Does It Do?
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Today’s AP lab requires a reliable system track and manage the entire testing process from specimen collection through report delivery. An effective APLIS plays a key role in the pathology workflow, watch to learn how. Learn More.
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Views on digital pathology, AI, and the AP LIS
February 2025—Digital pathology, artificial intelligence, and anatomic pathology computer systems—seven participants in a Dec. 10, 2024 online roundtable talked with CAP TODAY publisher Bob McGonnagle about their experiences, plans, and predictions. Large academic center practices and small pathology practices—they considered all perspectives. Here is what they told us.
Coleman Stavish, tell us why you think we asked Proscia, the provider of the Concentriq platform, to be part of this roundtable on anatomic pathology computer systems.
Coleman Stavish, cofounder and chief technology officer, Proscia: We’re seeing that digital pathology has moved beyond the talking and planning phase and into the operational phase. The scanner and software technology has matured considerably over the past couple of years. Our Concentriq platform sits at the center of bringing these solutions together. Some large labs in the U.S. and around the world have gone almost 100 percent digital, if not fully digital. So there’s a blueprint now for the market to see how it works at scale, and Proscia can speak to this.
This is the first time we’ve dealt in depth with digital pathology and AI for anatomic pathology systems. It’s becoming a reality in many places and in part reflects the excitement around AI in pathology to simplify the complexity of diagnosis, but it also reflects the shortage of surgical pathologists in the United States. Dr. Rashidi, can you comment on that and what it means to you at UPMC?
Hooman Rashidi, MD, MS, associate dean of AI in medicine, University of Pittsburgh School of Medicine; professor and endowed chair of experimental pathology research, and executive vice chair of computational pathology, University of Pittsburgh Medical Center; executive director, Computational Pathology and AI Center of Excellence, University of Pittsburgh: Because of the shortage of pathologists and staff, the leadership of hospitals and institutions is more receptive to investing in complementary frameworks, specifically digital pathology, that could be incorporated into workflows. It’s a cost to them now. But if they see it as incorporated with AI, where the return on investment is there, at least from a three-to-five-year strategic plan, an argument can be made that a digital pathology framework is needed because without it there is no AI. Once you set up digital pathology and a digital transformation, you can incorporate the AI, which then fuels the adoption and return on investment.
About 90 percent of our workforce is outside of academia and don’t have scanners, so the number one question is how to entice them to get on board knowing they have to learn a new innovation, and as with any innovation you’ll have a J curve. The difference now is you can argue that the dip down of the J curve can be flattened in digital pathology, at the least, with AI. End users will have an incentive to use digital pathology tools because their workflow speed and accuracy will be enhanced, especially with regulatory frameworks that show you may have decreased risk-management issues.
Continue reading …
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