This follows class action lawsuits in multiple states against insurance companies that deny millions of healthcare claims each year
Artificial intelligence (AI) has become ubiquitous in many aspects of healthcare. But perhaps its most controversial use is in the payer denial-of-claims process. Multiple states are pursuing legislation that would limit or outright ban AI’s use without physician involvement.
Clinical laboratories experience payment denials at both the prior authorization stage when a doctor orders a lab test as well as when the claim is submitted for reimbursement. And many labs perform tests for which they know they will not be paid just to maintain the client account relationships with doctors.
Now, several states are taking measures to protect patients from what some say is a dangerous trend to use AI algorithms only to review and deny medical claims for critical healthcare and clinical laboratory testing. This will be of interest to lab managers and those in charge of their lab’s revenue.
“Physicians and patients already face daunting challenges in navigating medical insurers’ bureaucratic administrative processes,” said Arizona Medical Association (ArMA) President Nadeem Kazi, MD, in a news release. “Taking physicians’ clinical experience out of these processes entirely is a misguided step,” he added.
However, on March 13, the Arizona Senate’s Finance Committee altered the language in its version of the bill. In it, AI is not specifically mentioned.
Instead, the bill’s language now “requires a medical director or healthcare provider, before a healthcare insurer may deny a claim or issue a direct denial of a prior authorization, to individually review any denial that involves medical necessity or experimental status or that requires the use of medical judgment and prohibits the director or provider from relying solely on recommendations derived from any other source during the prior authorization denial or claim denial review.”
Presumably, “any other source” includes AI-driven software platforms used by payers for prior authorization denials and claims processing.
“While AI promises innovation for several areas of healthcare, the review and denial of medical insurance claims—some of which represent life-changing treatments and procedures—should be left to physicians who can make nuanced clinical judgments,” said Shelby Job, ArMA communications director, in a statement following that state’s passage of the House bill in February.
The bill is now being debated in the Arizona Senate. If the Senate passes its version, the two sides will need to reconcile their bills.
“Patients deserve healthcare delivered by humans with compassionate medical expertise, not pattern-based computer algorithms designed by insurance companies,” said ArMA President Nadeem Kazi, MD (above), in a news release. (Photo copyright: Arizona Medical Association.)
Multiple States Move to Limit Use of AI in Claims Denials
In an Arizona House of Representatives Committee on Commerce meeting, state Republican representative Julie Willoughby, who is also an ER nurse, said that “she hopes the bill will protect Arizonians from losing healthcare access due to AI interference,” NBC News reported following passage of the House bill.
“What we’re asking for in this is that any claims that are denied have a provider look them over for completeness to ensure that there isn’t anything that the AI algorithm may not have accounted for,” she said.
If signed into law, the bill will require a medical director at the insurance carrier in question to “individually review each claim or prior authorization before a healthcare insurer is able to deny a claim for that patient,” NBC News noted.
California passed similar legislation in September that would “ensure that a licensed physician supervises the use of AI decision-making tools when they are used to inform decisions to approve, modify, or deny requests by providers,” NBC News reported.
The author of the California bill, Democratic senator Josh Becker, JD, argued upon the bill’s passing that AI “should never replace the expertise and judgment of physicians,” adding, “An algorithm cannot fully understand a patient’s unique medical history or needs, and its misuse can lead to devastating consequences.”
And in Texas, a bill introduced by Republican senator Charles Schwertner, MD, states that AI “should not be used as the ‘sole basis of a decision to wholly or partly deny, delay, or modify healthcare services,’” NBC News reported.
In a statement, the Texas Coalition of Patients said the bill is “crucial in ensuring that life-altering healthcare decisions remain in the hands of medical professionals rather than Big Insurance’s automated systems.”
In all, 11 states have introduced legislation to “to push back on artificial intelligence use in reviewing medical claims,” according to NBC News.
In May 2023, The Dark Report explored payer claims denials, and it was acknowledged back then that automated systems were already reviewing claims.
And then there are the lawsuits. According to The Guardian, Cigna, Humana, and UnitedHealth all face class-action lawsuits concerning the use of AI to “deny lifesaving care.”
Can AI Coexist with Human-based Care?
Although at this time AI may not understand the nuanced complexities of healthcare claims, there seem to be plenty of uses for it in healthcare decision-making. It can analyze large sets of data for diagnosis, transcribe medical documents using automatic speech recognition, and streamline administrative tasks––all of which can help a workforce plagued by staff burnout and shortages, Los Angeles Pacific University noted.
And though its use in payer claims reviews and denials is being resisted, AI will likely continue to help doctors diagnose disease and make better treatment decisions. Nevertheless, clinical laboratory and pathology workers should be aware of how the tool is being used and keep an eye out for suspicious claims denials.
Lab professionals will learn more at the upcoming 30th annual edition of the event
Big changes and challenges are coming for the clinical laboratory anatomic pathology industry, and with them a slew of opportunities for lab and pathology practice leaders. At the upcoming 30th Annual Executive War College on Diagnostics, Pathology, and Clinical Laboratory Management, expert speakers and panelists will focus on the three most disruptive forces.
There will be more than 169 presenters at this year’s Executive War College. Those speakers include:
David Dexter, MD, clinical and laboratory pathology at M Health Fairview, and Sam Terese, president and CEO at Alverno Laboratories, who will present a strategic case study about the support labs can provide to parent hospitals when navigating new waters.
Paul Wilder, executive director of CommonWell Health Alliance, who will speak on the effort to improve the transferability and portability of patient and healthcare data in ways that improve the quality of care.
“Since the inception of The Dark Report in 1995 there has been continual change both within the US healthcare system and within the profession of laboratory medicine,” noted Robert L. Michel, Dark Daily’s editor-in-chief and creator of the Executive War College. “Now, three decades later, the following three items are imperatives for all labs: controlling costs; having adequate lab staff across all positions; and having enough capital to acquire and deploy new diagnostic technologies, along with the latest information technologies.”
“Most clinical laboratory managers would agree that many of the same operational pain points faced by labs in the 1990s exist today,” said Robert L. Michel (above), founder of the Executive War College. In an interview with Dark Daily, Michel broke down the nuances of this triad of forces and what participants in the Executive War College can expect. (Photo copyright: LabX.)
Forces at Work in Clinical Labs and Pathology Groups
Here’s a more detailed look at each of the forces that Michel noted.
Force 1: An acute shortage of experienced lab scientists
“When you look at the supply-demand for laboratory personnel in the United States today, it is recognized that demand exceeds supply, and that gap continues to widen,” Michel noted. “For example, in the case of anatomic pathologists, the increased number of case referrals grows faster than medical schools can train new pathologists. Currently, the ability of pathology laboratories large and small to hire and retain an adequate number of pathologists is a challenge.”
Executive War College attendees can expect panelists and speakers to highlight creative problem solving techniques to circumvent the challenges labor shortages cause.
Force 2: New applications of artificial intelligence
“Today every instrument vendor, every automation supplier, every software supplier, every service supplier is telling labs that they have artificial intelligence (AI) baked inside,” Michel observed. “It is important for lab managers to understand that a variety of technologies are used by different AI solutions.”
Clinical laboratory managers and pathologists interested in acquiring a deeper understanding of where to start with AI in their lab will find numerous sessions on artificial intelligence at this year’s Executive War College. “There will be a number of sessions this year where clinical labs discuss their success deploying various AI solutions,” Michel said.
Force 3: Financial stress across the entire US healthcare system
“It’s recognized that a significant number of US hospitals and integrated delivery networks (IDNs) are struggling to maintain adequate operating margins,” Michel noted. “This obviously impacts the clinical laboratories serving these hospitals. If the hospitals’ cash flows and operating profit margins are being squeezed, typically the administration comes to the lab team and says, ‘Your budget for next year will be x% less than this year.’
“There are many IDNs and hospital labs where budget cuts have happened for multiple years,” Michel continued. “As a consequence, labs in these hospitals must be nimble to maintain a high-quality menu of diagnostic tests. Several years of such budget cuts by the parent hospital can undermine the ability of the clinical lab team to offer competitive salary packages to attract and retain the clinical lab scientists, pathologists, and clinical chemists they need.”
Recognizing Opportunities in Today’s Lab Market
The good news is that—despite the negative forces acting upon the US healthcare system today—clinical laboratories, genetic testing companies, and anatomic pathology groups have a path forward.
“This path forward is informed by two longstanding precepts recognized by innovative managers. One precept is ‘Change creates new winners and losers.’ The other precept is ‘Change creates opportunity,’” Michel said. “Savvy lab leaders recognize the powerful truths in each precept.
“As healthcare has changed over the past four decades, nearly all the regional and national laboratories that were dominant in 1990, for example, don’t exist today!” he noted. “And yet, even as these lab organizations disappeared, new clinical lab organizations emerged that recognized healthcare’s changes and organized themselves to serve the changing needs of hospitals, office-based physicians, payers, and patients.”
All of these critical topics and more will be covered during the 30th Annual Executive War College on Diagnostics, Clinical Laboratory, and Pathology Management on April 29-30, 2025, at the Hyatt Regency in New Orleans. Signup today to bring your lab’s management team by registering at https://www.executivewarcollege.com.
The trade association is publicly promoting the benefits of biomarker testing and AI’s benefits to diagnostics
One of the core tenets to getting federal lawmaker support for business is to tell them what an industry does. In that vein, the American Clinical Laboratory Association (ACLA) has released a new promotion that highlights applications of companion diagnostics, rapid whole genome sequencing, drug screening, biomarker testing, and infectious disease management.
One of the end goals? To sway Congress to take action against proposed reimbursement cuts to clinical lab test rates.
The ACLA campaign, known as the “Power of Knowing,” took center stage during a panel discussion at the ACLA Annual Meeting, held Feb. 27 in Washington, DC. One objective, panelists said, is to draw attention to the profession’s role in prevention and early detection of diseases, according to report from Medtech Insight.
“The association is working hard to demonstrate to policymakers the value of clinical laboratory testing through the Power of Knowing as they make policy decisions on reimbursement and clinical laboratory infrastructure that’s necessary for robust patient access to these innovative diagnostics,” said panel moderator Elyse Oveson, according to Medtech Insight. Oveson serves as ACLA chief of advocacy operations.
In March 2024, ACLA released digital ads urging Congress to pass the Saving Access to Laboratory Services Act (SALSA), which would have prevented a 15% cut in Medicare reimbursement for approximately 800 laboratory tests.
“A sustainable reform of the Medicare payment system for clinical laboratory services is vital to protect and enhance patient care, foster innovation, and ensure the stability of clinical laboratories nationwide,” ACLA president Susan Van Meter said at the time.
“If patients don’t have their biomarkers profiled for them at diagnosis and again at progression, there’s a very real chance that they would be put on the incorrect therapy that could lead to them having real harm in their health. So, we view biomarkers as critical,” said Nikki Martin (above), senior director of precision medicine initiatives for the LUNGevity Foundation, during the 2025 ACLA Annual Meeting. (Photo copyright: LinkedIn.)
Martin told attendees that biomarker tests should be part of the standard of care in lung cancer diagnosis, Medtech Insight reported. These tests analyze blood or other patient samples to identify molecules associated with specific diseases.
“For patients with non-small cell lung cancer, biomarkers are everything,” said Martin during the panel discussion. Many patients with advanced metastatic cancer, she said, “are not receiving comprehensive biomarker testing, and if they’re not, then they’re at risk of having much worse outcomes.”
Edelmayer discussed progress in developing biomarker tests for early diagnosis of Alzheimer’s disease. “The momentum is palpable among the research community,” she said. “We’re now starting to see the shift into implementation and more types of tools and technologies being available to clinicians to help patients.”
However, Edelmayer acknowledged that progress in developing Alzheimer’s tests and treatments has been slow.
“There’s never going to be a single test to help diagnose Alzheimer’s disease,” she said. “We recognize that it’s going to be a combination approach.”
New Video Campaign
The campaign’s latest advertising is summed up in a 90-second sizzle reel in which clinical laboratory leaders discuss various ways in which the profession supports healthcare.
One theme in the video is the growing use of artificial intelligence (AI) in the profession. “AI-enabled diagnostics are tools that use machine learning to analyze vast amounts of data from patient records to genomic profiles,” said Kate Sasser, PhD, chief scientific officer of Tempus, in the video. “These systems can recognize patterns in the data that humans may not easily see and help clinicians detect diseases earlier and more accurately.”
“By harnessing these cutting-edge tools, we can move closer to a world where treatments are no longer one size fits all but are instead tailored to the unique genetic and molecular profile of each patient,” said Elias Zerhouni, MD, president and vice chairman of OPKO Health, in a recent video produced as part of the ACLA’s Power of Knowing campaign.
The campaign website includes additional videos as well as downloadable graphics that can be shared on social media.
Study is expected to result in new clinical laboratory test biomarkers based on proteins shown to be associated with specific diseases
In January, the UK Biobank announced the launch of the “world’s most comprehensive study” of the human proteome. The study focuses on proteins circulating throughout the human body. Researchers involved in this endeavor hope the project will transform disease detection and lead to clinical laboratory blood tests that help diagnosticians identify illnesses earlier than with conventional diagnostics.
Building on the results of a 2023 pilot project that studied “the effects of common genetic variation on proteins circulating in the blood and how these associations can contribute to disease,” according to a UK Biobank news release, the 2025 UK Biobank Pharma Proteomics Project (UKB-PPP) plans to analyze up to 5,400 proteins in 600,000 samples to explore how an individual’s protein levels changes over time and how those changes may influence the existence of diseases in mid-to-late life.
The specimens being analyzed include 500,000 samples extracted from UK Biobank participants and an additional 100,000 set of second samples taken from volunteers up to 15 years later.
“The data collected in the study will allow scientists around the world to conduct health-related research, exploring how lifestyle, environment, and genetics lead through proteins to some people developing particular diseases, while others do not,” Sir Rory Collins, FMedSci FRS, professor of medicine and epidemiology at University of Oxford and principal investigator and chief executive of the UK Biobank, told The Independent.
“That will allow us to identify who it is, who’s likely to develop disease well before they do, and we can then look at ways in which to prevent those conditions before they develop,” he added.
“It really might be possible to develop simple blood tests that can detect disease much earlier than currently exists,” said Naomi Allen, MSc, DPhil (above), chief scientist for UK Biobank and professor of epidemiology at Oxford Population Health, University of Oxford, in an interview with The Independent. “So, it adds a crucial piece in the jigsaw puzzle for scientists to figure out how disease develops and gives us firm clues on what we can do to prevent and treat it.” Clinical laboratories may soon have new test biomarkers that help identify proteins associated with specific diseases. (Photo copyright: UK Biobank.)
Developing New Protein-based Biomarkers
A proteome is the entire set of proteins expressed by an organism, cell, or tissue and the study of the proteome is known as proteomics. The proteome is an expression of an organism’s genome, but it can change over time between cell types and growth conditions.
The human genome contains approximately 20,000 genes and human cells have between 80,000 and 400,000 proteins with specific cells having their own proteomes. Proteomics can help ascertain how proteins function and interact with each other and assist in the identification of biomarkers for new drug discoveries and development.
“This is hugely valuable, because it will enable researchers to see how changes in protein levels within individuals over mid- to late-life influence the development of a whole range of different diseases,” said Naomi Allen, MSc, DPhil, chief scientist for UK Biobank and professor of epidemiology at the Oxford Population Health, University of Oxford, in The Independent. “It will accelerate research into the causes of disease and the development of new treatments that target specific proteins associated with those diseases.
“The pilot data is already showing that specific proteins are elevated in those who go on to develop many different types of cancers up to seven years before a clinical diagnosis is made. And for dementia, up to 10 years before clinical diagnosis is made,” she added.
According to the project’s website, the UK Biobank’s proteomics dataset will allow researchers to:
Examine proteomic and genetic data from half a million people to provide a more detailed picture of the biological processes involved in disease progression.
Examine how and why protein levels change over time to understand age-related changes in healthy individuals.
Utilize proteomic data together with imaging data to understand disease mechanisms.
“Data from the pilot study has shown that specific proteins are substantially elevated in individuals with autoimmune conditions like multiple sclerosis and Crohn’s disease and so on,” Allen noted. “So, you can see how a simple blood test could be used to complement existing diagnostic measures in order to diagnose these types of diseases more accurately and perhaps more quickly.”
An Invaluable Resource of Knowledge
The initial UK Biobank started in 2006 and, to date, has collected biological and medical data from more than half a million individuals. The subjects of the UKB-PPP study are between the ages of 40 and 69 and reside in the UK. The database is globally accessible to approved researchers and scientists engaging in research into various diseases.
The full dataset of the latest research is expected to be added to the UK Biobank Research Analysis Platform by the year 2027. The newest study is backed by a consortium of 14 pharmaceutical firms.
Allen also noted that evidence from the research has emphasized how some drugs may be useful in treating a variety of conditions.
“Some proteins that are known to be important for immunity are related to developing a range of psychiatric conditions like schizophrenia, depression, bipolar disorder and so on,” she told The Independent. “And given there are drugs already available that specifically target some of these proteins that are used for other conditions, it presents a real opportunity for repurposing those existing drugs for these neuropsychiatric conditions.”
This type of comprehensive study of the human proteome may have a great impact on patient diagnosis and treatment once the study is completed and the results are disclosed.
“The data will be invaluable. The value of the data is infinite,” Collins told The Independence.
Since it is clinical laboratories that will be engaged in testing for proteins that have become associated with specific diseases, this new UK Biobank study has the potential to expand knowledge about useful protein markers for both diagnosis and therapeutic solutions (prescription drugs).
New guidelines come on the heels of recommendations covering post-market modifications to AI products, including those incorporated into systems used by clinical laboratories
Artificial intelligence (AI) is booming in healthcare, and as the technology finds its way into more medical devices and clinical laboratory diagnostic test technologies the US Food and Drug Administration (FDA) has stepped up its efforts to provide regulatory guidance for developers of these products. This guidance will have an impact on the development of new lab test technology that uses AI going forward.
In December, the FDA issued finalized recommendations for submitting information about planned modifications to AI-enabled healthcare products. Then, in January, the federal agency issued draft guidance that covers product management and marketing submission more broadly. It is seeking public comments on the latter document through April 7.
“The FDA has authorized more than 1,000 AI-enabled devices through established premarket pathways,” said Troy Tazbaz, director of the Digital Health Center of Excellence at the FDA’s Center for Devices and Radiological Health, in a press release announcing the draft guidance.
This guidance “would be the first to provide total product life cycle recommendations for AI-enabled devices, tying together all design, development, maintenance and documentation recommendations, if and when finalized,” Healthcare IT News reported.
“Today’s draft guidance brings together relevant information for developers, shares learnings from authorized AI-enabled devices, and provides a first point-of-reference for specific recommendations that apply to these devices, from the earliest stages of development through the device’s entire life cycle,” said Troy Tazbaz (above), director of the Digital Health Center of Excellence at the FDA Center for Devices and Radiological Health, in a press release. The new guidance will likely affect the development of new clinical laboratory diagnostic technologies that use AI. (Photo copyright: LinkedIn.)
Engaging with FDA
One key takeaway from the guidance is that manufacturers “should engage with the FDA early to ensure that the testing to support the marketing submission for an AI-enabled device reflects the agency’s total product lifecycle, risk-based approach,” states an analysis from consulting firm Orrick, Herrington and Sutcliffe LLP.
Another key point is transparency, Orrick noted. For example, manufacturers should be prepared to offer details about the inputs and outputs of their AI models and demonstrate “how AI helps achieve a device’s intended use.”
Manufacturers should also take steps to avoid bias in data collection for these models. For example, they should gather evidence to determine “whether a device benefits all relevant demographic groups similarly to help ensure that such devices are safe and effective for their intended use,” Orrick said.
New Framework for AI in Drug Development
On the same day that FDA announced the device guidelines, the agency also proposed a framework for regulating use of AI models in developing drugs and biologics.
“AI can be used in various ways to produce data or information regarding the safety, effectiveness, or quality of a drug or biological product,” the federal agency stated in a press release. “For example, AI approaches can be used to predict patient outcomes, improve understanding of predictors of disease progression and process, and analyze large datasets.”
The press release noted that this is the first time the agency has proposed guidance on use of AI in drug development.
These include “bias and reliability problems due to variability in the quality, size, and representativeness of training datasets; the black-box nature of AI models in their development and decision-making; the difficulty of ascertaining the accuracy of a model’s output; and the dangers of data drift and a model’s performance changing over time or across environments. Any of these factors, in FDA’s thinking, could negatively impact the reliability and relevancy of the data sponsors provide FDA.”
The FDA also plans to participate in direct testing of AI-enabled healthcare tools. In October, the FDA and the Department of Veterans Affairs (VA) announced that they will launch “a joint health AI lab to evaluate promising emerging technologies,” according to Nextgov/FCW.
Elnahal said the facility will allow federal agencies and private entities “to test applications of AI in a virtual lab environment.” The goal is to ensure that the tools are safe and effective while adhering to “trustworthy AI principles,” he said.
“It’s essentially a place where you get rapid but effective evaluation—from FDA’s standpoint and from VA’s standpoint—on a potential new application of generative AI to, number one, make sure it works,” he told Nextgov/FCW.
He added that the lab will be set up with safeguards to ensure that the technologies can be tested safely.
“As long as they go through the right security protocols, we’d essentially be inviting parties to test their technology with a fenced off set of VA data that doesn’t have any risk of contagion into our actual live systems, but it’s still informative and simulated,” he told Nextgov/FCW.
There has been an explosion in the use of AI, machine learning, deep learning, and natural language processing in clinical laboratory diagnostic technologies. This is equally true of anatomic pathology, where AI-powered image analysis solutions are coming to market. That two federal agencies are motivated to establish guidelines on working relationships for evaluating the development and use of AI in healthcare settings tells you where the industry is headed.
