For the past 14 years, healthcare spending as a percentage of US gross domestic product has stayed flat—17.2% in 2010 compared to 17.8% in 2024—according to numbers presented by Robert Michel, editor-in-chief of Dark Daily and founder of the Executive War College.
“This is not auspicious for either the vendor side of the clinical laboratory business or providers,” Michel told attendees during the conference’s opening session.
“Clinical laboratories all must watch for opportunities to earn revenue through new business models,” said Robert Michel (above), editor-in-chief of Dark Daily. Michel spoke during a general session at the 2025 Executive War College on Diagnostics, Clinical Laboratory, and Pathology Management in New Orleans. (Photo copyright: LabX.)
Spending Blockades Will Push New Business Models for Labs
Michel ran through a series of other, similarly grim statistics that put hard numbers on trends that many laboratory executives and owners already suspected:
Half of Americans have less than $500 in a savings account, according to a January 2025 survey by GOBankingRates.com. Those people face tough financial decisions, including whether to postpone healthcare testing and treatment, Michel said.
Growth in Medicare spending by beneficiary generally stopped in 2010 and remained flat at around $12,500 per beneficiary as of 2023.
“Social Security and Medicaid are going to go broke sooner rather than later,” Michel predicted. “Congress has seen this problem and not reacted.”
Such financial challenges will force the need for new clinical laboratory business models. Among the key areas that will inspire these models are diagnostic data and technology, said Sam Terese, CEO and president at Alverno Laboratories, during his general session at the Executive War College.
“It comes back to using data to predict disease,” Terese explained. “If you can prevent someone from getting seriously ill, you will lower the cost of care.”
Terese pointed out the need to effectively use artificial intelligence (AI) to digest the massive amount of clinical data that labs sit on.
Another New Clinical Laboratory Business Model: Closing Care Gaps
Diagnostic laboratories should also be in the business of identifying care gaps among their patients and consumers. One subset to consider is diabetic and prediabetic people.
“Can the lab identify an A1C patient who should have come in to see their doctor based on the test result?” Michel asked. That type of approach raises the value of a lab test beyond just the result it produced, he added.
During another general session, Sonora Quest Laboratories showed how it determines risk stratification for colorectal cancer by using an algorithm that considers a patient’s age, gender, and minimum of two complete blood count test results to flag at-risk people.
“We’re able to get information to physicians to close that care gap,” said Jen Umscheid, senior director of quality, innovation, and performance excellence at Sonora Quest.
The Executive War College continues through Thursday, with an expected attendance of just over 1,000 delegates, speakers, and vendor representatives. Friday’s Dark Daily will explore how AI topics played out among curious attendees.
Labcorp, the commercial laboratory giant headquartered in Burlington, N.C., has billions of diagnostic test results archived. It takes samplings of those results and runs them through a machine learning algorithm that compares the data against a condition of interest, such as chronic kidney disease (CKD). Machine learning is a subdiscipline of AI.
Based on patterns it identifies, the machine learning algorithm can predict future test results for CKD based on patients’ testing histories, explained Stan Letovsky, PhD, Vice President for AI, Data Sciences, and Bioinformatics at Labcorp. Labcorp has found the accuracy of those predictions to be better than 90%, he added.
Labcorp also has created an AI-powered dashboard that—once layered over an electronic health record (EHR) system—allows physicians to configure views of an individual patient’s existing health data and add a predictive view based on the machine learning results.
For anatomic pathologists, this type of setup can quickly bring a trove of data into their hands, allowing them to be more efficient with patient diagnoses. The long-term implications of using this technology are significant for pathology groups’ bottom line.
Stan Letovsky, PhD (above), Vice President for AI, Data Sciences, and Bioinformatics at Labcorp, discussed AI developments in digital pathology during his keynote address at the 2022 Executive War College in New Orleans. “The best thing as a community that we can do for patients and their physicians with AI is to identify care gaps early on,” he said, adding, “If pathologists want to grow and improve their revenue, they have to be more productive.” (Photo copyright: Dark Intelligence Group).
Mayo Clinic Plans to Digitize 25 Million Glass Slides
In other AI developments, Mayo Clinic in Rochester, Minn., has started a project to digitally scan 25 million tissue samples on glass slides—some more than 100 years old. As part of the initiative, Mayo wants to digitize five million of those slides within three years and put them on the cloud, said pathologist and physician scientist Jason Hipp, MD, PhD, Chair of Computational Pathology and AI at Mayo Clinic.
“We want to be a hub within Mayo Clinic for digital pathology,” Hipp told Executive War College attendees during his keynote address.
Hipp views his team as the bridge between pathologists and the data science engineers who develop AI algorithms. Both sides must collaborate to move AI forward, he commented, yet most clinical laboratories and pathology groups have not yet developed those relationships.
“We want to embed both sides,” Hipp added. “We need the data scientists working with the pathologists side by side. That practical part is missing today.”
The future medical laboratory at Mayo Clinic will feature an intersection of pathology, computer technology, and patient data. Cloud storage is a big part of that vision.
“AI requires storage and lots of data to be practical,” Hipp said.
