Pathology has long been targeted as an area ripe for digitalization and is commonly discussed as the next big opportunity in clinical IT. Cut through the hype and explosive growth predictions though and a different story is evident. Adoption to date has been slow, regionalized and challenging, forcing some high-profile health technology vendors to write off investments in the sector. So, is digital pathology really going to go mainstream and live up to the hype? Or will it continue to frustrate those looking for a new growth sector in clinical IT?
Signify Research nears the end of their in-depth research on the global digital pathology market, discussing the outlook for the market, recent progress, and why they think digital pathology is starting to gain momentum.
Focus on providing value-based care, a response to spiraling health spending and large-scale health reform, has increasingly pushed health providers to tackle operational and clinical inefficiencies. Many believe technology has a significant hand to play in this process. At its core, pathology has changed little in over a century; pathologists still commonly use light microscopes to review specimens on glass slides, manually interpreting and reporting on what they see. Slides are also commonly mailed between health providers for second opinions and must be physically stored for long periods, requiring extensive space and driving substantial real estate costs at high volume sites. This “hard-copy” approach in the context of the increasingly digital healthcare environment is today viewed as both inefficient and dated.
Few providers however have moved to a fully digital pathology working practice yet, with less than five percent of pathology sites adopting a fully digitalized workflow for primary diagnosis globally. There are numerous reasons why adoption has been slow, though recently some significant progress has been made.
Pathology is a complex and diverse sector, with ties to many different clinical and research sectors. Market development has therefore not been linear, creating a fragmented competitive landscape. Vendors can be categorized broadly into subsets, including digital pathology specialists, life-science vendors, clinical IT software vendors, scanner hardware vendors, lab information systems (LIS) vendors, image analysis specialists, and machine learning specialists. Few of these offer “full stack” solutions, so often a provider must attempt to assemble a combination of products, creating interoperability issues and a need for customization. Alternatively, some have opted for “closed-loop” systems instead, usually tied to the scanner hardware, thereby creating digital pathology images in a proprietary format and limiting wider interoperability. Both require significant investment of resources and trade-offs between integration within the pathology lab and broader interoperability in the wider health system.
The models of digital pathology implementation used by early adopters has as a result, also been diverse. Most are nuanced due to local health policy, structure of the health system, past IT investments (especially with regards to Electronic Medical Records), and care initiatives. While it is positive that the number of reference sites has been increasing in the last few years, this does little to help establish a more common model that can act as a blueprint for other providers to follow. Put simplistically, most implementations fall within the following categories:
- single hospital implementations
- regional telepathology networks
- establishing central pathology hubs to serve multiple providers in the locale
- convergence with enterprise imaging solutions in radiology
The market today is mostly made up of new implementations installed within the last few years, especially in the U.S. where approval for primary diagnostic use was announced just last year (Philips Healthcare Intellisite Pathology). This means there has been little time to assess their success or increase confidence in the technology. It will therefore take some time for return-on-investment (ROI) analysis and anecdotal guidance from early adopters to filter through to other providers that are yet to move to digital pathology.
