Regulatory agencies in UK and US have yet to address dangers inherent in customer misunderstanding of DTC medical laboratory genetic test results
Direct-to-consumer (DTC) medical laboratory genetic tests are gaining popularity across the globe. But recent research out of the United Kingdom questions the reliability of these tests. The study, according to The Guardian, found that “Over the counter genetic tests in the UK that assess the risk of cancer or heart problems fail to identify 89% of those in danger of getting killer diseases.”
According the PGS website, “each PGS in the catalog is consistently annotated with relevant metadata; including scoring files (variants, effect alleles/weights), annotations of how the PGS was developed and applied, and evaluations of their predictive performance.”
However, the researchers told The Guardian, “Polygenic risk scores performed poorly in population screening, individual risk prediction, and population risk stratification. Strong claims about the effect of polygenic risk scores on healthcare seem to be disproportionate to their performance.”
“Strong claims have been made about the potential of polygenic risk scores in medicine, but our study shows that this is not justified,” Aroon Hingorani, PhD (above), Professor of Genetic Epidemiology at UCL and lead author of the study, told The Guardian. “We found that, when held to the same standards as employed for other tests in medicine, polygenic risk scores performed poorly for prediction and screening across a range of common diseases.” Consumer misunderstanding of DTC medical laboratory genetic tests is a real danger. (Photo copyright: University College London.)
Polygenic Scores Not Beneficial to Cancer Screening
To complete their study, the UCL researchers compared PGS genetic risk data to conventional clinical laboratory testing methods and discovered some troubling results. They include:
On average, only 11% of individuals who developed a disease had been identified by the tests.
A 5% false positive rate where people were informed that they would get a disease within 10 years but did not.
PGS only identified 10% of people who later developed breast cancer.
The researchers state in their BMJ Medicine paper that polygenic risk scores are not the same as testing for certain gene mutations, which could be critical in screening for some cancers. They also wrote that discovering genetic variants associated with the risk for disease is still crucial for drug development.
“It has been suggested that polygenic risk scores could be introduced early on to help prevent breast cancer and heart disease but, in the examples we looked at, we found that the scores contributed little, if any, health benefit while adding cost and complexity,” research physician and epidemiologist Sir Nicholas Wald, FRS, FRCP, FMedSci, Professor of Preventive Medicine at UCL Institute of Health Informatics and co-author of the study, told the Jersey Evening Post.
“Our results build on evidence that indicates that polygenic risk scores do not have a role in public health screening programs,” Wald added.
“This research study rightly highlights that for many health conditions genetic risk scores alone may have limited usefulness, because other factors such as deprivation, lifestyles, and environment are also important,” clinical epidemiologist Raghib Ali, MD, CEO, Chief Investigator and Chief Medical Officer, Our Future Health UK, told The Guardian.
Our Future Health is a collaboration between public, non-profit, and private sectors to create the UK’s largest health research program. The researchers in this endeavor intend to recruit over five million volunteers and use polygenic risk scores to develop innovative ways to prevent, detect, and treat disease. This program is funded by the UK’s National Health System (NHS).
“[Our] research program will be developing integrated risk scores that will take in all the important risk factors,” Ali explained. “We hope these integrated risk scores can identify people more likely to develop diseases, but this is a relatively new area of science and there are still unanswered questions around it.”
Danger of Misunderstanding DTC Genetic Tests
Here in the US, there have been news stories in recent years about the unreliability of certain genetic tests. Dark Daily covered these stories in previous ebriefs. News stories about the unreliability of genetic tests, particularly those marketed directly to consumers, reveal the problems that existing regulatory schemes have yet to address.
In “Consumer Reports Identifies ‘Potential Pitfalls’ of Direct-to-Consumer Genetic Tests,” we covered CR’s findings that though clinical laboratory and pathology professionals understand the difference between a doctor-ordered genetic health risk (GHR) test and a direct-to-consumer (DTC) genetic test, the typical genetic test customer may not. And that, misunderstanding the results of a DTC at-home genetic test can lead to confusion, loss of privacy, and potential harm.
Scientific American also covered the dangers of DTC testing in “The Problem with Direct-to-Consumer Genetic Tests,” in which the author notes that “despite caveats in ads and on packages, users can fail to understand their limitations,” and that “consumer-grade products are easily misconstrued as appropriate medical tests and create false reassurances in patients who could be at legitimate risk.”
Most clinical laboratory managers and pathologists are probably not surprised that the research performed at UCL shows that there are still issues surrounding genetic tests, particularly those marketed directly to consumers. While direct-to-consumer DNA tests can have some benefits, at this time, they are not always the best option for individuals seeking information about their personal risk for hereditary diseases.
This AI platform has the potential to also reduce workload of radiologists, but also of anatomic pathologists and oncologists allowing them to be more productive
When the UK’s National Health Service (NHS) recently tested an artificial intelligence (AI) platform’s ability to analyze mammograms, the AI found early signs of breast cancer that “human doctors” had previously missed, the BBC reported. This level of ability by AI might soon be adapted to aid overworked anatomic pathologists and cancer doctors in the United Kingdom.
Out of 10,000 mammograms MIA analyzed, the AI platform found “tiny signs of breast cancer in 11 women” which had not been spotted during earlier examinations, the BBC noted, adding that the cancers “were practically invisible to the human eye.”
This is a significant development in AI’s role in healthcare. Anatomic pathologists and clinical laboratory leaders will note that ongoing advancements in AI are enabling technology developers to apply their solutions to assessing radiology images, as well as in whole slide imaging used in digital pathology. In the UK, use of AI, the BBC noted, may also help ease doctor’s workloads.
“This is just the beginning of our work with Kheiron,” said Ben Glocker, PhD (above), Professor in Machine Learning for Imaging at Imperial College London and Head of ML Research at Kheiron Medical, in a news release. “We are actively working on new methodologies for the safe deployment and continuous monitoring of MIA to support a US and UK rollout. We are working hard to make sure that as many women as possible will benefit from the use of this new technology within the next year.” AI tools such as MIA may soon take much of the load from anatomic pathologists and radiologists. (Photo copyright: Imperial College London.)
MIA Cloud-based AI Platform
Kheiron was founded in 2016 and MIA was named one of the seven biggest medical breakthroughs in 2023 by ABC News. A study conducted by Imperial College London in 2023 found that MIA “could significantly increase the early detection of breast cancers in a European healthcare setting by up to 13%,” according to an Imperial news release.
“The study was conducted over three phases (two pilot phases and a live roll-out). Overall across the three phases, the AI reader found 24 more cancers than the standard human reading—a 7% relative increase—and resulted in 70 more women recalled (0.28% relative increase),” the news release reported. “Of the additional recalls, six (initial pilot), 13 (extended pilot), and 11 (live use) additional cancers were found, increasing relative cancer detection rate by 13%, 10%, and 5% respectively. [The researchers] found that 83% of the additional cancers detected using MIA in real clinical practice were invasive, showing that MIA can detect cancers where early detection is particularly vital.”
Supported by Microsoft’s Azure Cloud, MIA came together over six years based on training encompassing millions of mammograms worldwide, Healthcare Digital reported.
“AI tools are generally pretty good at spotting symptoms of a specific disease if they are trained on enough data to enable them to be identified. This means feeding the program with as many different anonymized images of those symptoms as possible, from as diverse a range of people as possible,” Sarah Kerruish, Chief Strategy Officer, Kheiron, told Healthcare Digital.
MIA has been trained to “recognize subtle patterns and anomalies” that can point to “cancerous cells even in their earliest stages of development,” Dataconomy reported.
MIA Finds Early Cancer Signs
In the pilot study, MIA examined mammograms from 10,889 women. Each image had previously been reviewed by two radiologists, the BBC reported.
Findings include the following according to Healthcare Digital:
MIA “flagged” all people the physicians previously identified with symptoms.
The AI platform discovered 11 people with cancer the doctors did not identify.
The cancer MIA discovered—and the doctors did not—suggested cancer in early stages.
So, how did the doctors miss the cancer that MIA spotted? Gerald Lip, MD, Clinical Director for Breast Screening in North East Scotland who led the pilot study for the NHS, told Healthcare Digital, “part of the power of AI is it’s not prone to exhaustion or distraction.
“There is an element of fatigue,” he said. “You get disruptions, someone’s coming in, someone’s chatting in the background. There are lots of things that can probably throw you off your regular routine as well. And in those days when you have been distracted, you go, ‘how on earth did I miss that?’ It does happen.”
Lip is also the Chief Investigator in the Mammography Artificial Intelligence Project in the Industrial Center for Artificial Intelligence and Digital Diagnostics in Scotland.
“I see MIA as a friend and an augmentation to my practice,” he told Healthcare Digital. “MIA isn’t perfect. It had no access to patient history so [it] would flag cysts that had already been identified by previous scans and designated harmless.”
AI as a Safety Net
In the 2023 study, researchers from Imperial College London deployed MIA as an extra reader for mammograms of 25,065 women who visited screening sites in Hungary between April 2021 and January 2023, according to a news release.
“Our prospective real-world usage data in Hungary provides evidence for a significant, measurable increase of early breast cancer detection when MIA is used in clinical practice,” said Peter Kecskemethy, PhD, CEO and co-founder of Kheiron Medical, in the news release.
“Our study shows that AI can act as an effective safety net—a tool to prevent subtler signs of cancer from falling through the cracks,” said Ben Glocker, PhD, Professor in Machine Learning for Imaging at Imperial College London and Head of ML Research at Kheiron Medical, in the news release.
More studies are needed before MIA can be used in clinical settings. Nevertheless, use of AI in radiology—specifically mammograms—where the AI tool can identify very small cancers typically undetectable by radiologists, would be a boon to cancer doctors and the patients they treat.
So far, the research suggests that the AI-powered MIA has benefits to deployment in breast cancer screening. Eventually, it may also make impressive contributions to medical diagnosis and patient care, particularly if MIA eventually proves to be effective at analyzing the whole slide images used by anatomic pathologists.
Clinical studies show that new ‘cell-free’ test can predict cardiovascular disease risk better than standard HDL cholesterol test
Researchers from the National Institutes of Health (NIH) have developed a diagnostic assay that measures how well high-density lipoprotein (HDL)—the so-called “good” cholesterol—is working in the body. And their findings could lead to new clinical laboratory tests that supplement standard HDL level testing to better determine a person’s risk for heart disease.
Cholesterol tests are among the most commonly performed assays by clinical laboratories. A new test that reveals how well HDL is working in the body would certainly boost a medical laboratory’s test requisition volume.
“Measuring HDL function is limited to research labs and isn’t conducive to large-scale testing by routine clinical laboratories. To try to solve that problem, researchers from NHLBI’s Lipoprotein Metabolism Laboratory created a new diagnostic test,” noted an NHLBI news release.
“This is going to quicken the pace of basic research,” said Edward B. Neufeld, PhD, who along with guest researcher Masaki Sato, PhD, developed the test. “It increases the number of samples that you can study. It increases the number of experiments you can do.”
Such a new cholesterol test would quickly become one of the most commonly performed clinical lab tests because just about every American who has a physical gets cholesterol tests as part of that process.
“Other people may modify this or come up with better versions, which is fine with us,” Edward Neufeld, PhD (above), NHLBI Staff Scientist, said in a news release. “We just really wanted to tackle this problem of evaluating HDL function.” Clinical laboratories may soon have a new cholesterol test to supplement standard HDL level testing. (Photo copyright: ResearchGate.)
Faster Answers Needed about HDL
According to the NIH, the goal should go beyond measuring level of HDL as part of a person’s annual physical. What is also needed is finding out whether HDL cholesterol is effectively doing certain tasks, such as removing extra cholesterol from arteries and transporting it to the liver.
The NHLBI’s new cell-free test may make it possible to step up large-scale clinical testing of HDL function, according to the news release. As it stands now, HDL function study has been limited to research labs where testing involves “harvesting cells in the lab [which] can take days to process,” according to NIH Record.
“Most studies to date that have assessed CAD (coronary artery disease) risk by HDL functionality still use the CEC (cellular cholesterol efflux capacity) in vitro assay and are based on the use of radioisotopes (3H-cholesterol) and cultured cells, which is very labor intensive and impractical to do in a clinical laboratory,” the researchers wrote in The Journal of Clinical Investigation. They also pointed out that CEC batch-to-batch variability does not fit clinical laboratories’ need for standardization.
Advantages of NHLBI’s Test
To overcome these barriers, the NHLBI researchers created an HDL-specific phospholipid efflux (HDL-SPE) assay that has certain advantages over current HDL function assessments done in research labs.
According to the NIH, the HDP-SPE assay:
Is easy to replicate in clinical labs.
Is more suited to automation and large samples.
Offers up results in about an hour.
Is a better predictor of cardiovascular disease risk than HDL cholesterol testing for CAD risk.
“We developed a cell-free, HDL-specific phospholipid efflux assay for the assessment of CAD risk on the basis of HDL functionality in whole plasma or serum. One of the main advantages of the HDL-SPE assay is that it can be readily automated, unlike the various CEC assays currently in use,” the authors noted in their paper.
Here is how the test is performed, according to the NIH:
Plasma with HDL is separated from the patient’s blood.
“Plasma is added to donor particles coated with a lipid mixture resembling plaque and a fluorescent-tagged phospholipid” that only HDL can remove.
The fluorescent signal by HDL is then measured.
A bright signal suggests optimal HDL lipid removal function, while a dim light means reduced function.
The test builds on the scientists’ previous findings and data. In creating the new assay they drew on data from:
A study of 50 severe CAD and 50 non-CAD people.
A Japanese study of 70 CAD and 154 non-CAD participants.
Examined association of HDL-SPE with cardiovascular disease in a study of 340 patients and 340 controls.
“We have established the HDL-SPE assay for assessment of the functional ability of HDL to efflux phospholipids. Our combined data consistently show that our relatively simple HDL-SPE assay captures a pathophysiologically relevant parameter of HDL function that is at least equivalent to the CEC assay in its association with prevalent and incident CAD,” the researchers concluded in The Journal of Clinical Investigation.
Test May Be Subject to New FDA Rule
While HDL cardiovascular-related research is moving forward, studies aimed at the therapeutic side need to pick up, NIH noted.
“Someday we may have a drug that modulates HDL and turns out to be beneficial, but right now we don’t have that,” said Alan Remaley MD, PhD, NHLBI Senior Investigator and Head of the Lipoprotein Metabolism Laboratory, in the news release.
It may be years before the HDL-SPE test is used in medical settings, the researchers acknowledged, adding that more studies are needed with inclusion of different ethnicities.
Additionally, in light of the recently released US Food and Drug Administration (FDA) final rule on regulation of laboratory developed tests (LDT), the company licensed to bring the test to market may need to submit the HDL-SPE assay to the FDA for premarket review and clearance. That could lengthen the time required for the developers to comply with the FDA before the test is used by doctors and clinical laboratories in patient care.
Trifecta of forces at work that will affect the clinical laboratory and pathology industries have been described as a ‘perfect storm’ requiring lab and practice managers to be well informed
Digital pathology, artificial intelligence (AI) in healthcare, and the perfect storm of changing federal regulations, took centerstage at the 29th Executive War College on Diagnostics, Clinical Laboratory, and Pathology Management in New Orleans this week, where more than 1,000 clinical laboratory and pathology leaders convened over three days.
This was the largest number of people ever onsite for what has become the world’s largest event focused exclusively on lab management topics and solutions. Perhaps the highlight of the week was the federal Food and Drug Administration’s (FDA’s) announcement of its final rule on Laboratory Developed Tests (LDTs). Overall, the conference featured more than 120 speakers, many of them national thought leaders on the topic of clinical lab and pathology management. More than 65% of the audience onsite were executive level lab managers.
“The level of interest in the annual Executive War College is testimony to the ongoing need for dynamic, engaging, and highly relevant conference events,” said Robert Michel (above), Editor-in-Chief of Dark Daily and its sister publication The Dark Report, and founder of the Executive War College. “These in-person gatherings present great opportunities for clinical laboratory and pathology managers and leaders to network and speak with people they otherwise might not meet.” (Photo copyright: Dark Intelligence Group.)
Demonstrating Clinical Value
For those who missed the action onsite, the following is a synopsis of the highlights this week.
Lâle White, Executive Chair and CEO of XiFin, spoke about the future of clinical laboratory testing and the factors reshaping the industry. There are multiple dynamics impacting healthcare economics and outcomes—namely rising costs, decreasing reimbursements, and the move to a more consumer-focused healthcare. But it is up to labs, she said, to ensure their services are not simply viewed as a commodity.
“Laboratory diagnostics have the potential to change the economics of healthcare by really gaining efficiencies,” she noted. “And it’s up to labs to demonstrate clinical value by helping physicians manage two key diagnostic decision points—what tests to order, and what to do with the results.”
But even as labs find ways to increase the value offered to clinicians, there are other disruptive factors in play. Consumer-oriented tech companies such as Google, Apple, and Amazon are democratizing access to patient data in unforeseen ways, and Medicare Advantage plans are changing the way claims are processed and paid.
Clinical labs are fundamental components of the public health infrastructure. So, the CDC plans on focusing on delivering high-quality laboratory science, supported by reliable diagnostics and informatics for disease outbreaks and exposures, and engaging with public and private sector partners.
The history of MolDX and Z-Codes were the topics discussed by Gabriel Bien-Willner, MD, PhD, Chief Medical Officer for healthcare claims and transaction processing company Palmetto GBA. Molecular testing is highly complex, and the lack of well-defined billing codes and standardization makes it difficult to know if a given test is reasonable and necessary.
Z-Codes were established to clarify what molecular testing was performed—and why—prompting payers to require both Z-Codes and Current Procedural Terminology (CPT) codes when processing molecular test claims. Medicare’s MolDX program further streamlines the claims process by utilizing expertise in the molecular diagnostics space to help payers develop coverage policies and reimbursement for these tests.
FDA Final Rule on LDT Regulation
Timothy Stenzel, MD, PhD, CEO of Grey Haven Consulting and former director of the FDA’s Office of In Vitro Diagnostics reviewed the latest updates from the FDA’s Final Rule on LDT (laboratory developed test) regulation. Prior to the FDA releasing its final rule, some experts suggested that the new regulations could result in up to 90% of labs discontinuing their LDT programs, impacting innovation, and patient care.
However, the final rule on LDTs is very different from the original proposed rule which created controversy. The final rule actually lowers the regulatory burden to the point that some labs may not have to submit their LDTs at all. The FDA is reviewing dozens of multi-cancer detection assays, some of which have launched clinically as LDTs. The agency is likely to approve those that accurately detect cancers for which there is no formal screening program.
Stenzel explained the FDA’s plan to down-classify most in vitro diagnostic tests, changing them from Class III to Class II, and exempting more than 1,000 assays from FDA review. He also discussed the highlights of the Quality Management System Regulation (QMSR). Launched in January, the QMSR bought FDA requirements in line with ISO 13485, making compliance easier for medical device manufacturers and test developers working internationally.
Looming Perfect Storm of Regulatory Changes
To close out Day 1, Michel took to the stage again with a warning to clinical laboratories about the looming “Perfect Storm” trifecta—the final FDA ruling on LDTs, Z-Code requirements for genetic testing, and updates to CLIA ’92 that could result in patient data being considered a specimen.
Laboratory leaders must think strategically if their labs are to survive the fallout, because the financial stress felt by labs in recent years will only be exacerbated by macroeconomic trends such as:
Staff shortages,
Rising costs,
Decreasing and delayed reimbursements, and
Tightening supply chains.
Lab administrators looking for ways to remain profitable and prosperous should look beyond the transactional Clinical Lab 1.0 fee-for-service model and adopt Clinical Lab 2.0, which embraces HEDIS (Healthcare Effectiveness Data and Information Set) scores and STAR ratings to offer more value to Medicare Advantage and other payers.
Wednesday’s General Session agenda was packed with information about the rise of artificial intelligence, big data, and precision medicine in healthcare. Taking centerstage on the program’s final day was Michael Simpson, President and CEO of Clinisys. Simpson gave a global perspective on healthcare data as the new driver of innovation in diagnostics and patient care.
Palmetto GBA’s Chief Medical Officer will cover how clinical laboratories billing for genetic testing should prepare for Z-Codes at the upcoming Executive War College in New Orleans
After multiple delays, UnitedHealthcare (UHC) commercial plans will soon require clinical laboratories to use Z-Codes when submitting claims for certain molecular diagnostic tests. Several private insurers, including UHC, already require use of Z-Codes in their Medicare Advantage plans, but beginning June 1, UHC will be the first to mandate use of the codes in its commercial plans as well. Molecular, anatomic, and clinical pathologist Gabriel Bien-Willner, MD, PhD, who oversees the coding system and is Chief Medical Officer at Palmetto GBA, expects that other private payers will follow.
“A Z-Code is a random string of characters that’s used, like a barcode, to identify a specific service by a specific lab,” Bien-Willner explained in an interview with Dark Daily. By themselves, he said, the codes don’t have much value. Their utility comes from the DEX Diagnostics Exchange registry, “where the code defines a specific genetic test and everything associated with it: The lab that is performing the test. The test’s intended use. The analytes that are being measured.”
The registry also contains qualitative information, such as, “Is this a good test? Is it reasonable and necessary?” he said.
Molecular, anatomic, and clinical pathologist Gabriel Bien-Willner, MD, PhD (above), Palmetto GBA’s Chief Medical Officer, will speak about Z-Codes and the MolDX program during several sessions at the upcoming Executive War College on Diagnostics, Clinical Laboratory, and Pathology Management taking place in New Orleans on April 30-May 1. Clinical laboratories involved in genetic testing will want to attend these critical sessions. (Photo copyright: Bien-Willner Physicians Association.)
Palmetto GBA Takes Control
Palmetto’s involvement with Z-Codes goes back to 2011, when the company established the MolDX program on behalf of the federal Centers for Medicare and Medicaid Services (CMS). The purpose was to handle processing of Medicare claims involving genetic tests. The coding system was originally developed by McKesson, and Palmetto adopted it as a more granular way to track use of the tests.
In 2017, McKesson merged its information technology business with Change Healthcare Holdings LLC to form Change Healthcare. Palmetto GBA acquired the Z-Codes and DEX registry from Change in 2020. Palmetto GBA had already been using the codes in MolDX and “we felt we needed better control of our own operations,” Bien-Willner explained.
In addition to administering MolDX, Palmetto is one of four regional Medicare contractors who require Z-Codes in claims for genetic tests. Collectively, the contractors handle Medicare claims submissions in 28 states.
Benefits of Z-Codes
Why require use of Z-Codes? Bien-Willner explained that the system addresses several fundamental issues with molecular diagnostic testing.
“Payers interact with labs through claims,” he said. “A claim will often have a CPT code [Current Procedural Technology code] that doesn’t really explain what was done or why.”
In addition, “molecular diagnostic testing is mostly done with laboratory developed tests (LDTs), not FDA-approved tests,” he said. “We don’t see LDTs as a problem, but there’s no standardization of the services. Two services could be described similarly, or with the same CPT codes. But they could have different intended uses with different levels of sophistication and different methodologies, quality, and content. So, how does the payer know what they’re paying for and whether it’s any good?”
When the CPT code is accompanied by a Z-Code, he said, “now we know exactly what test was done, who did it, who’s authorized to do it, what analytes are measured, and whether it meets coverage criteria under policy.”
The process to obtain a code begins when the lab registers for the DEX system, he explained. “Then they submit information about the test. They describe the intended use, the analytes that are being measured, and the methodologies. When they’ve submitted all the necessary information, we give the test a Z-Code.”
The assessment could be as simple as a spreadsheet that asks the lab which cancer types were tested in validation, he said. On the other end of the scale, “we might want to see the entire validation summary documentation,” he said.
Commercial Potential
Bien-Willner joined the Palmetto GBA in 2018 primarily to direct the MolDX program. But he soon saw the potential use of Z-Codes and the DEX registry for commercial plans. “It became instantly obvious that this is a problem for all payers, not just Medicare,” he said.
Over time, he said, “we’ve refined these processes to make them more reproducible, scalable, and efficient. Now commercial plans can license the DEX system, which Z-Codes are a part of, to better automate claims processing or pre-authorizations.”
In 2021, the company began offering the coding system for Medicare Advantage plans, with UHC the first to come aboard. “It was much easier to roll this out for Medicare Advantage, because those programs have to follow the same policies that Medicare does,” he explained.
As for UHC’s commercial plans, the insurer originally planned to require Z-Codes in claims beginning Aug. 1, 2023, then pushed that back to Oct. 1, according to Dark Daily’s sister publication The Dark Report.
Then it was pushed back again to April 1 of this year, and now to June 1.
“The implementation will be in a stepwise fashion,” Bien-Willner advised. “It’s difficult to take an entirely different approach to claims processing. There are something like 10 switches that have to be turned on for everything to work, and it’s going to be one switch at a time.”
For Palmetto GBA, the commercial plans represent “a whole different line of business that I think will have a huge impact in this industry,” he said. “They have the same issues that Medicare has. But for Medicare, we had to create automated solutions up front because it’s more of a pay and chase model,” where the claim is paid and CMS later goes after errors or fraudulent claims.
“Commercial plans in general just thought they could manually solve this issue on a claim-by-claim basis,” he said. “That worked well when there was just a handful of genetic tests. Now there are tens of thousands of tests and it’s impossible to keep up.
They instituted programs to try to control these things, but I don’t believe they work very well.”
Bien-Willner is scheduled to speak about Palmetto GBA’s MolDX program, Z-Codes, and related topics during three sessions at the upcoming 29th annual Executive War College conference. Clinical laboratory and pathology group managers would be wise to attend his presentations. Visit here (or paste this URL into your browser: https://www.executivewarcollege.com/registration) to learn more and to secure your seat in New Orleans.
