Digital Pathology Reimbursement Gains Ground as Industry Navigates Complex US Payment Landscape

Despite the potential of digital pathology and AI-driven image analysis to enhance efficiency in cancer diagnostics, securing reimbursement remains a barrier to widespread adoption. At a panel discussion during Pathology Visions 2025, experts from the DPA Reimbursement Task Force discussed progress and challenges in establishing payment pathways for diagnostic AI technologies.

“We need to figure out how we’re going to pay for it at some level so that we’re going to make this happen,” said Michael Rivers, VP and Lifecycle Leader for Digital Pathology at Roche, who co-chairs the task force.

The DPA has committed to education and advocacy work aimed at creating clearer routes to reimbursement for whole slide imaging and AI solutions.

Following the CAP’s establishment of Category III tracking codes for slide imaging, the group has focused intensively on AI reimbursement. Rivers announced that the task force is finalizing implementation guidelines for AI in digital pathology, which will support future local coverage determination (LCD) requests to Medicare. “Our intent is to get this into publication very soon,” Rivers said, noting the document has had support from several pathology leaders.

A Real-World Reimbursement Journey

Jennifer Archer, Senior Director of Market Access at ArteraAI and a DPA Reimbursement Task Force member, discussed a case study of her company’s multi-year reimbursement journey. ArteraAI’s prostate cancer test, called ArteraAI Prostate Test, uses digital pathology to generate prognostic and predictive risk scores, including 10-year metastasis risk and cancer-specific mortality predictions.

“This journey takes correct lengths of time, costs plenty of resources, requires perfect planning, calls for mere policy expertise, demands extreme patience, and can cause plenty of hard work,” Archer said, describing the arduous path her company navigated.

The ArteraAI timeline illustrates the three essential pillars of reimbursement: coding, payment, and coverage. The company applied for a Proprietary Laboratory Analyses (PLA) code in September 2022, received approval in April 2023, and secured Medicare payment rates by early 2024. ArteraAI waited until receiving NCCN guideline recommendations in early 2024 before submitting its LCD request, which was a strategic decision that positioned the test for positive coverage consideration, Archer explained.

The commercial insurance landscape was also challenging. Archer said that securing coverage from Anthem required two reconsideration letters, two evidence meetings with their policy team, and perseverance across three policy releases over 18 months. Today, ArteraAI Prostate Test has coverage from 45 health plans.

Shifting Regulatory Landscape Creates Uncertainty

Deborah Godes, Principal at McDermott and reimbursement consultant, discussed current policy trends. A major development this year was the American Medical Association’s clarification that algorithmic-only AI services no longer qualify for PLA codes, the pathway ArteraAI successfully used for its laboratory-developed test.

“That’s a pathway that is no longer available for digital technologies that are algorithmic-only based services,” Godes explained.

The American Medical Association is now considering a new coding structure called Clinically Meaningful Algorithmic Analyses, though concerns exist within the pathology community about specific requirements.

Godes emphasized that policymakers often lack understanding of the unique characteristics of digital pathology. “People who are making some of these policy decisions don’t necessarily understand,” she said, noting they apply broad AI policies across radiology, laboratory, and pathology applications despite significant differences.

From a payment perspective, the Centers for Medicare and Medicaid Services (CMS) continues making decisions on a case-by-case basis without formal policy guidance. “It’s really challenging if you’re an innovator in the space,” Godes said, though she noted CMS has begun soliciting stakeholder feedback.

Actionable Strategies for Companies

The speakers offered guidance for digital pathology companies pursuing reimbursement for their technologies. Archer advised that companies address common payer questions upfront. These questions include explaining how AI image analysis tests differ from traditional lab tests, clarifying that these are fixed machine learning models rather than generative AI, and demonstrating analytical validity.

She also stressed the importance of guideline inclusion, developing multiple parallel reimbursement strategies, and engaging with stakeholder organizations like the American Clinical Laboratory Association and DPA.

“I always told the manager that we need to have not one, not two, but three reimbursement plans running in parallel at any one time,” Archer noted.

Godes concluded by acknowledging both the excitement and frustration around new technologies:

“We’re trying to bring these technologies to market using frameworks that were created 20 to 30 years ago. They’re very rigid, and in some ways, you’re trying to fit a square keg into a round hole.”