Doctors report difficulty differentiating COVID-19 from other viral infections, impacting clinical laboratory test orders
Because the SARS-CoV-2 coronavirus is in the same family of viruses that cause the common cold and influenza, virologists expected this virus—which caused the global COVID-19 pandemic—would evolve and mutate into a milder form of infection. Early evidence from this influenza season seems consistent with these expectations in ways that will influence how clinical laboratories offer tests for different respiratory viruses.
While new variants of the SARS-CoV-2 virus continue to appear, indications are that early in this flu season individuals infected with the more recent variants are experiencing milder symptoms when compared to the last few years. Doctors report they find it increasingly difficult to distinguish COVID-19 infections from allergies or the common cold because patients’ symptoms are less severe, according to NBC News.
This, of course, makes it challenging for doctors to know the most appropriate clinical laboratory tests to order to help them make accurate diagnoses.
“It isn’t the same typical symptoms that we were seeing before. It’s a lot of congestion, sometimes sneezing, usually a mild sore throat,” Erick Eiting, MD, Vice Chair of Operations for Emergency Medicine at Mount Sinai Hospital in New York City, told NBC News. “Just about everyone who I’ve seen has had really mild symptoms. The only way that we knew that it was COVID was because we happened to be testing them.” Knowing which tests for respiratory viruses that clinical laboratories need to perform may soon be the challenge for doctors. (Photo copyright: Mt. Sinai.)
Milder COVID-19 Symptoms Follow a Pattern
Previous hallmarks of a COVID-19 infection included:
Loss of taste,
loss of smell,
dry cough,
fever,
sore throat,
diarrhea,
body aches,
headaches.
However, physicians now observe milder symptoms of the infection that follow a distinct pattern and which are mostly concentrated in the upper respiratory tract.
Grace McComsey, MD, Vice President of Research and Associate Chief Scientific Officer at University Hospitals Health System (UH) in Cleveland, Ohio, told NBC News that some patients have described their throat pain as “a burning sensation like they never had, even with Strep in the past.”
“Then, as soon as the congestion happens, it seems like the throat gets better,” she added.
In addition to the congestion, some patients are experiencing:
headache,
fever,
chills,
fatigue,
muscle aches,
post-nasal drip.
McComsey noted that fatigue and muscle aches usually only last a couple of days, but that the congestion can sometimes last a few weeks. She also estimated that only around 10-20% of her newest COVID patients are losing their sense of smell or taste, whereas early in the pandemic that number was closer to 60-70% of her patients.
Doctors also noted that fewer patients are requiring hospitalization and that many recover without the use of antivirals or other treatments.
“Especially since July, when this recent mini-surge started, younger people that have upper respiratory symptoms—cough, runny nose, sore throat, fever and chills—99% of the time they go home with supportive care,” said Michael Daignault, MD, an emergency physician at Providence Saint Joseph Medical Center in Burbank, California.
Milder SARS-CoV-2 Variants Should Still be Taken Seriously
Doctors have varying opinions regarding why the current COVID-19 variants are milder. Some believe the recent variants simply aren’t as good at infecting the lungs as previous variants.
“Overall, the severity of COVID-19 is much lower than it was a year ago and two years ago,” Dan Barouch, MD, PhD, Director of the Center for Virology and Vaccine Research at Beth Israel Deaconess Medical Center, told NBC News. “That’s not because the variants are less robust. It’s because the immune responses are higher.”
McComsey added that she doesn’t think mild cases should be ignored as she is still seeing new cases of long COVID with rapid heart rate and exercise intolerance being among the most common lingering symptoms. Re-infections also add to the risks associated with long COVID.
“What we’re seeing in long COVID clinics is not just the older strains that continue to be symptomatic and not getting better—we’re adding to that number with the new strain as well,” McComsey said. “That’s why I’m not taking this new wave any less seriously.”
Clinical Laboratory COVID-19 Testing May Decrease
According to Andrew Read, PhD, Interim Senior Vice President for Research and Evan Pugh University Professor of Biology and Entomology at Pennsylvania State University, there is nothing unexpected or startling about the coronavirus acquiring new mutations.
“When a mutation confers an interesting new trick that’s got an advantage, it’s going to be popping up in many different places,” Read told the New York Times. “Everything we see is just consistent with how you imagine virus evolution proceeding in a situation where a new virus has jumped into a novel host population.”
Data from the Centers for Disease Control and Prevention’s COVID-19 Data Tracker—which reports weekly hospitalizations, deaths, emergency department (ED) visits, and COVID-19 test positivity results—shows infection trends fluctuating, but overall, they are decreasing.
For the week of October 21, 2023, there were 16,186 hospitalizations due to COVID-19 compared to the highest week recorded (January 15, 2022) with 150,674 hospitalizations nationwide.
The highest number of deaths reported in a single week were 25,974 for the week of January 8, 2021, while 637 patients perished from COVID-19 during the week of October 21, 2023.
In January of 2021, COVID accounted for 13.8% of all ED visits and in October 2023, COVID-19 was responsible for 1.3% of ED visits.
“What I think we’re seeing is the virus continuing to evolve, and then leading to waves of infection, hopefully mostly mild in severity,” Barouch told The New York Times.
As severity of COVID-19 infections continues to fall, so, presumably, will demand for COVID-19 testing which has been a source of revenue for clinical laboratories for several years.
Genetic engineers at the lab used the new tool to generate a catalog of 71 million possible missense variants, classifying 89% as either benign or pathogenic
Genetic engineers continue to use artificial intelligence (AI) and deep learning to develop research tools that have implications for clinical laboratories. The latest development involves Google’s DeepMind artificial intelligence lab which has created an AI tool that, they say, can predict whether a single-letter substitution in DNA—known as a missense variant (aka, missense mutation)—is likely to cause disease.
The Google engineers used their new model—dubbed AlphaMissense—to generate a catalog of 71 million possible missense variants. They were able to classify 89% as likely to be either benign or pathogenic mutations. That compares with just 0.1% that have been classified using conventional methods, according to the DeepMind engineers.
This is yet another example of how Google is investing to develop solutions for healthcare and medical care. In this case, DeepMind might find genetic sequences that are associated with disease or health conditions. In turn, these genetic sequences could eventually become biomarkers that clinical laboratories could use to help physicians make earlier, more accurate diagnoses and allow faster interventions that improve patient care.
“AI tools that can accurately predict the effect of variants have the power to accelerate research across fields from molecular biology to clinical and statistical genetics,” wrote Google DeepMind engineers Jun Cheng, PhD (left), and Žiga Avsec, PhD (right), in a blog post describing the new tool. Clinical laboratories benefit from the diagnostic biomarkers generated by this type of research. (Photo copyrights: LinkedIn.)
AI’s Effect on Genetic Research
Genetic experiments to identify which mutations cause disease are both costly and time-consuming, Google DeepMind engineers Jun Cheng, PhD, and Žiga Avsec, PhD, wrote in a blog post. However, artificial intelligence sped up that process considerably.
“By using AI predictions, researchers can get a preview of results for thousands of proteins at a time, which can help to prioritize resources and accelerate more complex studies,” they noted.
Of all possible 71 million variants, approximately 6%, or four million, have already been seen in humans, they wrote, noting that the average person carries more than 9,000. Most are benign, “but others are pathogenic and can severely disrupt protein function,” causing diseases such as cystic fibrosis, sickle-cell anemia, and cancer.
“A missense variant is a single letter substitution in DNA that results in a different amino acid within a protein,” Cheng and Avsec wrote in the blog post. “If you think of DNA as a language, switching one letter can change a word and alter the meaning of a sentence altogether. In this case, a substitution changes which amino acid is translated, which can affect the function of a protein.”
In the Google DeepMind study, AlphaMissense predicted that 57% of the 71 million variants are “likely benign,” 32% are “likely pathogenic,” and 11% are “uncertain.”
The AlphaMissense model is adapted from an earlier model called AlphaFold which uses amino acid genetic sequences to predict the structure of proteins.
“AlphaMissense was fed data on DNA from humans and closely related primates to learn which missense mutations are common, and therefore probably benign, and which are rare and potentially harmful,” The Guardian reported. “At the same time, the program familiarized itself with the ‘language’ of proteins by studying millions of protein sequences and learning what a ‘healthy’ protein looks like.”
The model assigned each variant a score between 0 and 1 to rate the likelihood of pathogenicity [the potential for a pathogen to cause disease]. “The continuous score allows users to choose a threshold for classifying variants as pathogenic or benign that matches their accuracy requirements,” Avsec and Cheng wrote in their blog post.
However, they also acknowledged that it doesn’t indicate exactly how the variation causes disease.
The engineers cautioned that the predictions in the catalog are not intended for clinical use. Instead, they “should be interpreted with other sources of evidence.” However, “this work has the potential to improve the diagnosis of rare genetic disorders, and help discover new disease-causing genes,” they noted.
Genomics England Sees a Helpful Tool
BBC noted that AlphaMissense has been tested by Genomics England, which works with the UK’s National Health Service. “The new tool is really bringing a new perspective to the data,” Ellen Thomas, PhD, Genomics England’s Deputy Chief Medical Officer, told the BBC. “It will help clinical scientists make sense of genetic data so that it is useful for patients and for their clinical teams.”
AlphaMissense is “a big step forward,” Ewan Birney, PhD, Deputy Director General of the European Molecular Biology Laboratory (EMBL) told the BBC. “It will help clinical researchers prioritize where to look to find areas that could cause disease.”
Other experts, however, who spoke with MIT Technology Review were less enthusiastic.
Heidi Rehm, PhD, co-director of the Program in Medical and Population Genetics at the Broad Institute, suggested that the DeepMind engineers overstated the certainty of the model’s predictions. She told the publication that she was “disappointed” that they labeled the variants as benign or pathogenic.
“The models are improving, but none are perfect, and they still don’t get you to pathogenic or not,” she said.
“Typically, experts don’t declare a mutation pathogenic until they have real-world data from patients, evidence of inheritance patterns in families, and lab tests—information that’s shared through public websites of variants such as ClinVar,” the MIT article noted.
Is AlphaMissense a Biosecurity Risk?
Although DeepMind has released its catalog of variations, MIT Technology Review notes that the lab isn’t releasing the entire AI model due to what it describes as a “biosecurity risk.”
The concern is that “bad actors” could try using it on non-human species, DeepMind said. But one anonymous expert described the restrictions “as a transparent effort to stop others from quickly deploying the model for their own uses,” the MIT article noted.
And so, genetics research takes a huge step forward thanks to Google DeepMind, artificial intelligence, and deep learning. Clinical laboratories and pathologists may soon have useful new tools that help healthcare provider diagnose diseases. Time will tell. But the developments are certain worth watching.
Federal prosecutors allege that this nurse practitioner ordered more genetic tests for Medicare beneficiaries than any other provider during 2020
Cases of Medicare fraud involving clinical laboratory testing continue to be prosecuted by the federal Department of Justice. A jury in Miami recently convicted a nurse practitioner (NP) for her role in a massive Medicare fraud scheme for millions of dollars in medically unnecessary genetic testing and durable medical equipment. She faces 75 years in prison when sentenced in December.
In their indictment, federal prosecutors alleged that from August 2018 through June 2021 Elizabeth Mercedes Hernandez, NP, of Homestead, Florida, worked with more than eight telemedicine and marketing companies to sign “thousands of orders for medically unnecessary orthotic braces and genetic tests, resulting in fraudulent Medicare billings in excess of $200 million,” according to a US Department of Justice (DOJ) news release announcing the conviction.
“Hernandez personally pocketed approximately $1.6 million in the scheme, which she used to purchase expensive cars, jewelry, home renovations, and travel,” the press release noted.
Hernandez was indicted in April 2022 as part of a larger DOJ crackdown on healthcare fraud related to the COVID-19 outbreak.
“Throughout the pandemic, we have seen trusted medical professionals orchestrate and carry out egregious crimes against their patients all for financial gain,” said Assistant Director Luis Quesada (above) of the FBI’s Criminal Investigative Division, in a DOJ press release. Clinical laboratory managers would be wise to monitor these Medicare fraud cases. (Photo copyright: Federal Bureau of Investigation.)
Nurse Practitioner Received Kickbacks and Bribes
Federal prosecutors alleged that the scheme involved telemarketing companies that contacted Medicare beneficiaries and persuaded them to request genetic tests and orthotic braces. Hernandez, they said, then signed pre-filled orders, “attesting that she had examined or treated the patients,” according to the DOJ news release.
In many cases, Hernandez had not even spoken with the patients, prosecutors said. “She then billed Medicare as though she were conducting complex office visits with these patients, and routinely billed more than 24 hours of ‘office visits’ in a single day,” according to the news release.
In total, Hernandez submitted fraudulent claims of approximately $119 million for genetic tests, the indictment stated. “In 2020, Hernandez ordered more cancer genetic (CGx) tests for Medicare beneficiaries than any other provider in the nation, including oncologists and geneticists,” according to the news release.
The indictment noted that because CGx tests do not diagnose cancer, Medicare covers them only “in limited circumstances, such as when a beneficiary had cancer and the beneficiary’s treating physician deemed such testing necessary for the beneficiary’s treatment of that cancer. Medicare did not cover CGx testing for beneficiaries who did not have cancer or lacked symptoms of cancer.”
In exchange for signing the orders, Hernandez received kickbacks and bribes from companies that claimed to be in the telemedicine business, the indictment stated.
“These healthcare fraud abuses erode the integrity and trust patients have with those in the healthcare industry … the FBI, working in coordination with our law enforcement partners, will continue to investigate and pursue those who exploit the integrity of the healthcare industry for profit,” said Assistant Director Luis Quesada of the Federal Bureau of Investigation’s Criminal Investigative Division, in the DOJ press release.
Conspirators Took Advantage of COVID-19 Pandemic
Prosecutors alleged that as part of the scheme, she and her co-conspirators took advantage of temporary amendments to rules involving telehealth services—changes that were enacted by Medicare in response to the COVID-19 pandemic.
The indictment noted that prior to the pandemic, Medicare covered expenses for telehealth services only if the beneficiary “was located in a rural or health professional shortage area,” and “was in a practitioner’s office or a specified medical facility—not at a beneficiary’s home.”
But in response to the pandemic, Medicare relaxed the restrictions to allow coverage “even if the beneficiary was not located in a rural area or a health professional shortage area, and even if the telehealth services were furnished to beneficiaries in their home.”
Hernandez was convicted of:
One count of conspiracy to commit healthcare fraud and wire fraud.
Four counts of healthcare fraud.
Three counts of making false statements.
Medscape noted that she was acquitted of two counts of healthcare fraud. The trial lasted six days, Medscape reported.
Hernandez’s sentencing hearing is scheduled for Dec. 14.
Co-Conspirators Plead Guilty
Two other co-conspirators in the case, Leonel Palatnik and Michael Stein, had previously pleaded guilty and received sentences, the Miami Herald reported.
Palatnik was co-owner of Panda Conservation Group LLC, which operated two genetic testing laboratories in Florida. Prosecutors said that Palatnik paid kickbacks to Stein, owner of 1523 Holdings LLC, “in exchange for his work arranging for telemedicine providers to authorize genetic testing orders for Panda’s laboratories,” according to a DOJ press release. The kickbacks were disguised as payments for information technology (IT) and consulting services.
“1523 Holdings then exploited temporary amendments to telehealth restrictions enacted during the pandemic by offering telehealth providers access to Medicare beneficiaries for whom they could bill consultations,” the press release states. “In exchange, these providers agreed to refer beneficiaries to Panda’s laboratories for expensive and medically unnecessary cancer and cardiovascular genetic testing.”
Palatnik pleaded guilty to his role in the kickback scheme in August 2021 and was sentenced to 82 months in prison, a DOJ press release states.
Stein pleaded guilty in April and was sentenced to five years in prison, the Miami Herald reported. He was also ordered to pay $63.3 million in restitution.
These federal cases involving clinical laboratory genetic testing and other tests and medical equipment indicate a commitment on the DOJ’s part to continue cracking down on healthcare fraud.
Plans by several national retail pharmacy chains to expand primary care services and even some clinical laboratory test offerings may be delayed because of financial woes
Times are tough for the nation’s retail pharmacy chains. Rite Aid Corporation, headquartered in Philadelphia, closed 25 stores this year and has now filed for bankruptcy. In a press release, the retail pharmacy company announced it has “initiated a voluntary-court supervised process under Chapter 11 of the US Bankruptcy Code,” and that it plans to “significantly reduce the company’s debt” and “resolve litigation claims in an equitable manner.”
Rite Aid may eventually close 400 to 500 of its 2,100 stores, Forbes reported.
Meanwhile, other retail pharmacy chains are struggling as well. CVS Health, headquartered in Woonsocket, Rhode Island, and Walgreens Boots Alliance of Deerfield, Illinois, are each closing hundreds of stores, according to the Daily Mail.
They are each experiencing problems with labor costs, theft, being disintermediated for prescriptions by pharmacy benefit managers (PBMs), and probably building too many stores in most markets.
This is a significant development, in the sense that Walgreens, CVS, and Walmart are each working to open and operate primary care clinics in their stores. This is a way to offset the loss of filling prescriptions, which has migrated to PBMs. Primary care clinics are important to the revenue of local clinical laboratories, but retail pharmacy chains do not yet operate enough primary care clinics in their retail pharmacies to be a major influence on the lab testing marketplace.
“With the support of our lenders, we look forward to strengthening our financial foundation, advancing our transformation initiatives, and accelerating the execution of our turnaround strategy,” said Jeffrey Stein (above), Rite Aid’s CEO/Chief Restructuring Officer, in a press release. Clinical laboratory leaders may want to closely monitor the activities of the retail pharmacies in their areas. (Photo copyright: Rite Aid.)
Multiple Pharmacy Companies at Financial Risk
Rite Aid Corporation (NYSE: RAD) confirmed it continues to operate its retail and online platforms and has received from lenders $3.45 billion in financing to support the company through the bankruptcy process.
However, according to the Associated Press (AP), Rite Aid has experienced “annual losses for several years” and “faces financial risk from lawsuits over opioid prescriptions,” adding that the company reported total debts of $8.6 billion.
Additionally, the US Department of Justice (DOJ) filed a complaint “alleging that Rite Aid knowingly filled unlawful prescriptions for controlled substances,” explained a DOJ press release.
Rite Aid is not the only retail pharmacy brand dealing with unwelcome developments. Fortune reported last year that Walgreens and CVS paid a combined $10 billion to 12 states for “involvement in the opioid epidemic.”
Walgreens intends to close 150 US and 300 United Kingdom locations, its former Chief Financial Officer James Kehoe shared in a third quarter 2023 earnings call transcribed by Motley Fool.
And in a news release, CVS announced plans to close 900 stores between 2022 and 2024.
Pharmacy Companies’ Investment in Primary Care
Though they are experiencing difficulties on the retail side, Walgreens and CVS have significantly invested in primary care.
In that same ebrief, we reported on CVS’ acquisition of Oak Street Health, a Chicago-based primary care company, for $10.6 billion. CVS plans to have more than 300 healthcare centers by 2026.
“We looked at our business, and we said, ‘We’re seeing an aging population.’ We know people don’t have access to primary care. We know that value-based care is where it’s going. We know that there’s been a renaissance in home (care). So that’s kind of how we approached our acquisitions,” Karen Lynch, CVS Chief Executive Officer told Fortune.
Other Challenges to Retail Pharmacies
It could be that these major pharmacy chains are hoping entry into primary care will offset the loss of sales from prescriptions that have migrated to PBM organizations.
In addition to reimbursement challenges, retail pharmacies are reportedly experiencing:
High labor costs,
Competition from online, bricks-and-mortar, and grocery businesses, and
Effects from the work-at-home trend, among other struggles.
“I think there’s a number of challenges which are coming to a head. One, you have ongoing reimbursement pressure. The reimbursement level for drugs continues to decrease, so profit margin on the core part of the business is under pressure,” Rodey Wing, a partner in the health and retail practices of global strategy and management consulting firm Kearney, told Drug Store News.
Additionally, the pharmacy’s drug sales need to be high enough to retain pharmacists, who are difficult to recruit in a post-pandemic market, Drug Store News explained.
And in the retail space where products are displayed, some pharmacies struggle to compete with Amazon on convenience and with “dollar” stores on price. And with more people working from home, retail pharmacies are seeing less foot traffic, Drug Store News noted.
Retail pharmacy companies also have competition from pharmacies conveniently situated in grocery and big-box stores, Forbes reported. These include:
Walmart, for its part, reduced operating hours of pharmacies at more than 4,500 sites, Daily Mail reported.
Thus, medical laboratory leaders would be wise to keep an eye on market changes in their local retail pharmacies. Some locations are equipped with clinical laboratory services and a closure could give local labs an opportunity to reach out to patients and physicians who need access to a new testing provider.
Many clinical laboratory professionals are aware of the significant amount of waste going into landfills from spent COVID-19 rapid PCR tests that use biosensors to produce results. These biosensor systems “use printed circuit boards, or PCBs, the same materials used in computers. PCBs are difficult to recycle and slow to biodegrade, using large amounts of metal, plastic, and non-eco-friendly materials,” according to a Penn Engineering Today blog post.
UPenn’s new test does not use PCBs. Instead, its biosensor uses “bacterial cellulose (BC), an organic compound synthesized from several strains of bacteria,” the blog post noted.
“This new BC test is non-toxic, naturally biodegradable and both inexpensive and scalable to mass production, currently costing less than $4.00 per test to produce. Its cellulose fibers do not require the chemicals used to manufacture paper, and the test is almost entirely biodegradable,” the blog post continued.
“There is a need for biodegradable diagnostic testing,” said Cesar de la Fuente, PhD (above), Presidential Assistant Professor in the Psychiatry Department at the University of Pennsylvania’s Perelman School of Medicine. “We will be continuing to perfect this technology, which could hopefully help many people in the future, while also looking to expand it to other emerging pathogens in anticipation of future pandemics.” Clinical laboratories engaged in SARS-CoV-2 testing during the COVID-19 pandemic can attest to the massive amounts of waste generated by traditional PCR testing. (Photo copyright: University of Pennsylvania.)
Evolution of Improvement for SARS-CoV-2 Diagnostic Assays
Cesar de la Fuente, PhD, is Presidential Assistant Professor in the Psychiatry Department at the Perelman School of Medicine. His lab has been hard at work since the start of the pandemic to improve COVID-19 testing. The recent study was a collaboration between University of Pennsylvania’s de la Fuente Lab and William Reis de Araujo, Professor in Analytical Chemistry at the State University of Campinas (UNICAMP) in São Paulo, Brazil.
De Araujo leads the Portable Chemical Sensors Lab and has been pairing his electrochemistry expertise with de la Fuente’s lab for years, Penn Engineering Today noted.
The team wanted to combine the speed and cost-effectiveness of previous rapid tests with an eco-friendly biodegradable substrate material.
Bacterial cellulose (BC) was a great choice because it “naturally serves as a factory for the production of cellulose, a paper-like substance which can be used as the basis for biosensors,” Penn Engineering Today reported.
Additionally, BC has an excellent track record for a variety of uses, such as regenerative medicine, wound care, and point-of-care (POC) diagnostics, the blog post noted. UPenn’s test offers speed and accuracy without needing costly equipment making it desirable for clinical laboratories preparing to fight the next pandemic.
The test has shown to be capable of “correctly identifying multiple variants in under 10 minutes. This means that the tests won’t require ‘recalibration’ to accurately test for new variants,” Penn Engineering Today added.
Innovation Born from Inspiration
Though rapid tests are essential to help curb the spread of COVID-19, the negatives that come with these tests didn’t sit well with the UPenn team. This spurred them to strive for improvements.
PCR tests “are hampered by waste [metal, plastic, and the aforementioned PCBs]. They require significant time [results can take up to a day or more] as well as specialized equipment and labor, all of which increase costs,” Penn Engineering Today noted.
Additionally, “Sophistication of PCR tests makes them harder to tweak and therefore slower to respond to new variants,” the blog post concluded.
“There’s a tension between these two worlds of innovation and conservation,” de la Fuente told Penn Engineering Today. “When we create new technology, we have a responsibility to think through the consequences for the planet and to find ways to mitigate the environmental impact.”
Need for Biodegradable Diagnostic Tests
“COVID-19 has led to over 6.8 million deaths worldwide and continues to affect millions of people, primarily in low-income countries and communities with low vaccination coverage,” the Cell Reports Physical Science paper noted.
“There is a need for biodegradable diagnostic testing,” de la Fuentes told Penn Engineering Today. “We will be continuing to perfect this technology, which could hopefully help many people in the future, while also looking to expand it to other emerging pathogens in anticipation of future pandemics.”
While UPenn’s test will require clinical trials and FDA approval before it can become available to clinical laboratories and for point-of-care testing, it promises a bright, eco-friendly future for rapid viral testing.
Pathologists and clinical laboratory managers will want to stay alert to the concerns voiced by tech experts about the need to exercise caution when using generative AI to assist medical diagnoses
GPTs are an integral part of the framework of a generative artificial intelligence that creates text, images, and other media using generative models. These neural network models can learn the patterns and structure of inputted information and then develop new data that contains similar characteristics.
Through their proposal, the AMA has developed principles and recommendations surrounding the benefits and potentially harmful consequences of relying on AI-generated medical advice and content to advance diagnoses.
“We’re trying to look around the corner for our patients to understand the promise and limitations of AI,” said Alexander Ding, MD (above), AMA Trustee and Associate Vice President for Physician Strategy and Medical Affairs at Humana, in a press release. “There is a lot of uncertainty about the direction and regulatory framework for this use of AI that has found its way into the day-to-day practice of medicine.” Clinical laboratory professionals following advances in AI may want to remain informed on the use of generative AI solutions in healthcare. (Photo copyright: American Medical Association.)
Preventing Spread of Mis/Disinformation
GPTs are “a family of neural network models that uses the transformer architecture and is a key advancement in artificial intelligence (AI) powering generative AI applications such as ChatGPT,” according to Amazon Web Services.
In addition to creating human-like text and content, GPTs have the ability to answer questions in a conversational manner. They can analyze language queries and then predict high-quality responses based on their understanding of the language. GPTs can perform this task after being trained with billions of parameters on massive language datasets and then generate long responses, not just the next word in a sequence.
“AI holds the promise of transforming medicine,” said diagnostic and interventional radiologist Alexander Ding, MD, AMA Trustee and Associate Vice President for Physician Strategy and Medical Affairs at Humana, in an AMA press release.
“We don’t want to be chasing technology. Rather, as scientists, we want to use our expertise to structure guidelines, and guardrails to prevent unintended consequences, such as baking in bias and widening disparities, dissemination of incorrect medical advice, or spread of misinformation or disinformation,” he added.
The AMA plans to work with the federal government and other appropriate organizations to advise policymakers on the optimal ways to use AI in healthcare to protect patients from misleading AI-generated data that may or may not be validated, accurate, or relevant.
Advantages and Risks of AI in Medicine
The AMA’s proposal was prompted by AMA-affiliated organizations that stressed concerns about the lack of regulatory oversight for GPTs. They are encouraging healthcare professionals to educate patients about the advantages and risks of AI in medicine.
“AI took a huge leap with large language model tool and generative models, so all of the work that has been done up to this point in terms of regulatory and governance frameworks will have to be treated or at least reviewed with this new lens,” Sha Edathumparampil, Corporate Vice President, Digital and Data, Baptist Health South Florida, told Healthcare Brew.
According to the AMA press release, “the current limitations create potential risks for physicians and patients and should be used with appropriate caution at this time. AI-generated fabrications, errors, or inaccuracies can harm patients, and physicians need to be acutely aware of these risks and added liability before they rely on unregulated machine-learning algorithms and tools.”
According to the AMA press release, the organization will propose state and federal regulations for AI tools at next year’s annual meeting in Chicago.
In a July AMA podcast, AMA’s President, Jesse Ehrenfeld, MD, stressed that more must be done through regulation and development to bolster trust in these new technologies.
“There’s a lot of discomfort around the use of these tools among Americans with the idea of AI being used in their own healthcare,” Ehrenfeld said. “There was a 2023 Pew Research Center poll [that said] 60% of Americans would feel uncomfortable if their own healthcare provider relied on AI to do things like diagnose disease or recommend a treatment.”
WHO Issues Cautions about Use of AI in Healthcare
In May, the World Health Organization (WHO) issued a statement advocating for caution when implementing AI-generated large language GPT models into healthcare.
A current example of such a GPT is ChatGPT, a large language-based model (LLM) that enables users to refine and lead conversations towards a desired length, format, style, level of detail and language. Organizations across industries are now utilizing GPT models for Question and Answer bots for customers, text summarization, and content generation and search features.
“Precipitous adoption of untested systems could lead to errors by healthcare workers, cause harm to patients, erode trust in AI, and thereby undermine (or delay) the potential long-term benefits and uses of such technologies around the world,” commented WHO in the statement.
WHO’s concerns regarding the need for prudence and oversight in the use of AI technologies include:
Data used to train AI may be biased, which could pose risks to health, equity, and inclusiveness.
LLMs generate responses that can appear authoritative and plausible, but which may be completely incorrect or contain serious errors.
LLMs may be trained on data for which consent may not have been given.
LLMs may not be able to protect sensitive data that is provided to an application to generate a response.
LLMs can be misused to generate and disseminate highly convincing disinformation in the form of text, audio, or video that may be difficult for people to differentiate from reliable health content.
Tech Experts Recommended Caution
Generative AI will continue to evolve. Therefore, clinical laboratory professionals may want to keep a keen eye on advances in AI technology and GPTs in healthcare diagnosis.
“While generative AI holds tremendous potential to transform various industries, it also presents significant challenges and risks that should not be ignored,” wrote Edathumparampil in an article he penned for CXOTECH Magazine. “With the right strategy and approach, generative AI can be a powerful tool for innovation and differentiation, helping businesses to stay ahead of the competition and better serve their customers.”
GPT’s may eventually be a boon to healthcare providers, including clinical laboratories, and pathology groups. But for the moment, caution is recommended.
