From ‘new-school’ rules of running a clinical laboratory to pharmacy partnerships to leveraging lab data for diagnostics, key industry executives discussed the new era of clinical laboratory and pathology operations
“COVID-19 didn’t change a whole lot of things in one sense, but it accelerated a lot of trends that were already happening in healthcare,” said Robert L. Michel, Editor-in-Chief of Dark Daily and its sister publication The Dark Report, and Founder of the Executive War College, during his opening keynote address to a packed ballroom of conference attendees. “Healthcare is transforming, and the transformation is far more pervasive than most consumers appreciate.
“Disintermediation, for example, is taking traditional service providers and disrupting them in substantial ways, and if you think about the end of fee-for-service, be looking forward because your labs can be paid for the value you originate that makes a difference in patient care,” Michel added.
Another opportunity for clinical laboratories, according to Michel, is serving Medicare Advantage plans which have soared in enrollment. “Lab leaders should be studying Medicare Advantage for how to integrate Medicare Advantage incentives into their lab strategies,” he said, highlighting the new influence of risk adjustment models which use diagnostic data to predict health condition expenditures.
Opening sessions at this week’s annual Executive War College on Diagnostics, Clinical Laboratory, and Pathology Management, presented by Robert L. Michel (above), Editor-in-Chief of Dark Daily and its sister publication The Dark Report, discussed demand for delivering healthcare services—including medical laboratory testing—as consumer preferences evolve, new care models are designed, and as payers seek value over volume. While these three forces may be challenging at the outset, they also create opportunities for clinical laboratories and pathology groups—a focal point of the Executive War College each year. (Photo copyright: The Dark Intelligence Group.)
Medical Laboratories Must Adapt to ‘New-School’ Rules
During his keynote address, Stan Schofield, Vice President and Managing Principal at The Compass Group, noted that while the basic “old-school” rules of successfully running a clinical laboratory have not changed—e.g., adding clients, keeping clients, creating revenue opportunities, getting paid, and reducing expenses—the interpretation of each rule has changed. The Compass Group is a trade federation based in South Carolina that serves not-for-profit healthcare integrated delivery networks (IDNs), including 32 health systems and 600 hospitals.
Schofield advised that when it comes to adding new clients under the “new-school” rules of lab management, clinical laboratory directors must be aware of and adapt to hospital integrations of core labs, clinical integrations across health systems, seamless services, direct contracting with employers in insurance relationships, and direct-to-consumer testing. Keeping clients, Schofield said, involves five elements:
Strong customer service.
A tailored metrics program for quality services based on what is important to a lab’s clients.
Balanced scorecards that look at the business opportunity and value proposition with each client.
Monitoring patients’ experiences and continuous improvement.
Participation in all payer agreements.
As to the problem of commoditization of laboratory goods and services, Schofield said, “Right now, we’re facing the monetization of the laboratory. We’re going to swiftly move from commoditization to monetization to commercialization.”
Diagnostics and pharmacy now intersect, according to Pope. “Pharmacists are on the move, and they are true contender as a new provider for you,” he said. “An area of pharmacy that is dependent upon labs is specialty medications.”
Specialty medicines now account for 55% of prescription spending, up from 28% in 2011, driven by growth in auto-immune and oncology, Pope noted. Other examples include companion diagnostics required for targeted treatments pertaining to all major cancers, and new areas like thalassemia (inherited blood disorders), obesity, next-generation sequencing, and pharmacogenomics, in addition to routine testing such as liver function and complete blood count (CBC).
Federal legislation may soon recognize pharmacists as healthcare providers who will be trained to perform specific clinical services, Pope said. Some states already recognize pharmacists as providers, he noted, explaining that pharmacies need lab data for three primary reasons:
Service—Pharmacies can act as a referral source to clinical laboratories. When referring, pharmacies may need to communicate lab test results to patients or providers to coordinate care.
Value-based care—Pharmacies would draw on data to counsel, prescribe, and coordinate care for chronic disease management, among other services.
Diagnostics and pharmacogenetics—Specialty medication workflows require documented test results within a specific timeframe prior to dispensing.
Another point Pope made: Large pharmacies are seeking lab partners. Labs that can provide rapid turnaround time and good pricing on complex tests provide pharmacies with partnership opportunities.
Using AI to Create Patients’ ‘Digital Twins’ That Help Identify Disease and Improve Care
High-tech healthcare technology underlies many opportunities in the clinical laboratory and pathology market, as evidenced throughout the Executive War College’s 2023 curriculum. An ongoing challenge for labs, however, is how to produce the valuable datasets that all labs have the potential to generate.
“It feels like we’ve come so far,” explained Brad Bostic, CEO of hc1 during his keynote address. “We’ve got the internet. We’ve got the cloud. All of this is amazing, but in reality, we have this massive proliferation of data everywhere and it’s very difficult to know how to actually put that into use. And nobody’s generating more data than clinical laboratories.
“Every single interaction with a patient that generates data gives you this opportunity to create the idea of a ‘digital twin.’ That means that labs are creating a mathematical description of what a person’s state is and using that information to look at how providers can optimally diagnose and treat that person. Ultimately, it is bigger than just one person. It’s hundreds of millions of people that are generating all this data, and many of these people fall into similar cohorts.”
This digital twin opportunity is heavily fueled by medical laboratory testing, Bostic said, adding that labs need to be able to leverage artificial intelligence (AI) to:
“I recommend lab leaders sit down with their teams and any outside partners they trust and identify what are their lab’s goals,” Bostic stated. “Think about how this technology can advance a lab’s mission. Look at strategy holistically—everything from internal operations to how patient care is affected.”
One of the world’s fastest growing medical laboratory companies in India is using digital pathology systems and AI to replace older diagnostic technologies
Artificial intelligence (AI) is gaining acceptance around the world and use of AI to analyze digital pathology images is expected to be a major disruptor to the profession of anatomic pathology. Internationally, several pathology companies already use AI-powered solutions to diagnose cancer.
One such example is Neuberg Diagnostics, a fast-growing clinical laboratory company in Chennai, India. Neuberg has been using AI to review digital pathology images for several years, according to Chairman and Managing Director GSK Velu, PhD, BPharm.
“We already use AI in our laboratories,” Velu said in an exclusive interview with Dark Daily. “Our main reference laboratories currently use digital pathology systems to support the pathologists and many of them are using AI with these digital pathology systems.
“AI and data analytics tools are being used in other departments too, such as in our wellness department where we use AI for predictive analytics,” he added. “We also use AI in our genomics division, and we are introducing AI into other divisions slowly and steadily.”
Neuberg operates 120 laboratories in an extensive network in India, South Africa, and the United Arab Emirates (UAE), and now in the US as well.
As has been happening at other anatomic pathology centers around the world, Neuberg has been using digital pathology systems to replace older technologies. “One of our largest labs is our Bangalore Reference Lab,” Velu said. “There, we do not use microscopes for histopathology, and that lab has used digital pathology for routine review of specimens for several years now.
“But because artificial intelligence is still emerging, we can’t rely on AI with all of our digital pathology systems,” he added. “Although, of course, AI is certainly an aid to everything we do with digital pathology.
“For a variety of reasons, the adaptation of artificial intelligence in anatomic pathology is not happening as effectively nor as fast as we would like,” he noted. “So, for now, we need to wait and watch a bit longer, either because adaptation by pathologists is slow, or because AI tools are still a bit of a worry for some pathologists.
Younger Pathologists Adapt Faster to Digital Pathology
One reason could be that conventional pathologists worry about relying completely on AI for any diagnosis, Velu noted. “I’m certain that the more recent generation of pathologists who are now in their 30s, and the new people coming into pathology, will start adapting more quickly to digital pathology and to AI faster than the older generation of pathologists have done.
“The younger pathologists have a greater appreciation for the potential of digital pathology, while the older pathologists don’t want to let go of conventional diagnosis methods,” he added.
“For example, we have not yet seen where pathologists are reviewing breast image scans,” he commented. “But, at the same time, AI has been well-accepted among radiologists who are reviewing breast mammography scans.”
In India and in other markets worldwide, radiologists have adapted AI tools for breast mammography scans to diagnose breast cancer, he noted. “But that’s not happening even among pathologists who are doing cancer screening,” he said.
Velu suggested that another reason for the slow adoption of AI tools in pathology is that these systems are relatively new to the market. “Maybe the AI tools that are used with digital pathology are not as reliable as we hoped they would be, or they are not fully robust at the moment,” he speculated. “That’s why I say it will take some time before the use of AI for diagnosis becomes more widespread among pathologists. So, for now, we must wait until digital pathology and AI tools work together more seamlessly.
Replacing Conventional Pathology Technologies and Methods
“When those two technologies—AI and digital pathology systems—are linked more closely, their use will take hold in a substantial way,” Velu predicted. “When that happens, they are likely to replace conventional pathology methods completely.
“Currently, we are in the early stages of a transformation,” he added. “In our labs, you can see that the transformation is ongoing. We are using digital pathology systems even in our smaller labs. Then, the staff in our smaller labs do the processing of slides to convert them to digital images and send them to our labs in the larger cities. There, the professional staff uses AI to review those digital images and issue reports based on those images.
“Using our digital pathology systems and AI in that way means that we can make that technology available even in smaller towns and villages that have access only to our smaller labs,” he commented.
Velu added that wider use of digital pathology systems could improve the quality of care that pathologists deliver to patients in a significant way, particularly in rural areas. “Here in India, we are not seeing a huge shortage of pathologists, except in rural areas and villages,” he explained. “In those places, we could run short of pathologists.
“That is the reason we are trying to adapt the use of telepathology more widely,” he noted. “To do that, we might have technicians and histologists who will do just processing of slides so that they can send the digital images to our pathologists located in larger cities. Then, those surgical pathologists will review the cases and send the reports out. That’s the model that we are trying to slowly follow here.”
As use of digital pathology images increased, many predicted that specimens would flow from the US to India. This would happen because of the belief that the lower cost of surgical pathology in India would successfully draw business away from pathology groups here in the United States.
However, Neuberg turned the tables on that belief when it announced the opening of its Neuberg Centre for Genomic Medicine (NCGM), a state-of-the-art esoteric and genetic testing laboratory in Raleigh, NC. The NCGM lab is CLIA-certified and Neuberg says it is ready to compete with labs in this country on their home turf.
These are reasons why pathologists and pathology practice administrators in the United States may want to watch how Neuberg Diagnostics continues to develop its use of digital pathology platforms and AI-powered digital image analysis tools throughout its international network of laboratories.
IBM’s Watson continues to seek a role as a cognitive computing tool of choice for physicians and pathologists in need of evidence-based clinical patient data
Remember IBM’s Watson? It’s been five years since Watson beat human contestants on Jeopardy. Since then, IBM has hoped Watson could be used in healthcare. To that end, some oncologists are exploring the use of Watson in cancer care. This could have implications for anatomic pathologists if oncologists developed a way to use Watson in the diagnosing cancers and identifying appropriate therapies for those cancers.
In 2011, IBM’s Watson supercomputer defeated human contestants for a charity prize during the television show Jeopardy. Just days later, Dark Daily reported on IBM’s goal for Watson to play a major role in helping physicians diagnose and treat disease. Since then, IBM has been exploring ways to commercialize Watson’s cognitive computing platform through partnerships with some of the healthcare industry’s biggest brands. (more…)