Cybersecurity experts recommend clinical laboratories have in place a plan for performing tests and distributing results prior to a cyberattack
Hospitals of all sizes continue to be prime targets for sophisticated cyberattacks, where hackers remotely disable a healthcare network’s computer systems—including its laboratory information system—and extort ransomware payments. Similar attacks are happening to clinical laboratories and other providers, although not with the same frequency.
Recently, hospitals in Illinois, Idaho, Vermont, Indiana, and other states had their ability to treat patients severely reduced and, in some cases, completely shut down by cybercriminals, endangering lives and costing millions of dollars in damages.
Today’s hospitals rely on information technology (IT) for patient care workflow, internal/external communication, billing, and medical laboratory testing. It’s this reliance on computer/internet technology combined with the vast quantities of protected health information (PHI), that makes hospitals such ripe targets for attack.
In June, a US cancer center had to take its digital services offline which “significantly reduced patient treatment capability” following a ransomware attack by a group of hackers known as the TimisoaraHackerTeam (THT), MedCity News reported.
“Patients don’t stop getting sick just because a hospital is hit by a ransomware attack,” Christian Dameff, MD, emergency physician at UC San Diego Health and lead author of a study that looked into how cyberattacks affect other hospitals in the area, told ABC News. “They have to go somewhere. So, what this research shows is that those patients go to neighboring hospitals that can be overwhelmed.” Clinical laboratories can also become overwhelmed with test orders when nearby hospitals lose their ability to distribute the results of critical lab tests. (Photo copyright: UC San Diego Health.)
“The attack halted the hospital’s ability to submit claims to insurers, Medicare or Medicaid for months, sending it into a financial spiral,” Linda Burt, RN, Vice President of Quality and Community Services at St. Margaret’s, told NBC News. “We were down a minimum of 14 weeks. And then you’re trying to recover. Nothing went out. No claims. Nothing got entered. So, it took months and months and months.”
Meabwhile, 88-bed Idaho Falls Community Hospital experienced a cyberattack in May that required it to divert ambulances to other hospitals for 24 hours, CNN reported. The provider’s sister healthcare facility, MountainView Hospital in Las Vegas, which shares the same computer system, was also affected.
The Idaho Falls attack “forced nurses and doctors … to use pen and paper rather than computers for patient charts,” a hospital spokesperson told CNN.
At the University of Vermont Medical Center (UVM), Burlington, Vermont, a ransomware attack affected healthcare services for 28 days, costing the provider $50 million to recover, and preventing healthcare workers from accessing critical treatment plans for cancer patients, ABC News reported.
UVM’s President and Chief Operating Officer, Stephen Leffler, MD, an emergency medicine physician, told ABC News that the 2020 cyberattack significantly disrupted clinical laboratory operations at UVM.
“When the laboratory had a critical lab result on someone, they couldn’t put it in the electronic medical record,” he explained. “They couldn’t call the floor. And so, we literally had our administrators start going in the lab, standing there and running a paper result to the floors.
“Everything that we do and rely on was down,” he added. “We actually sent some staff to Best Buy to buy Walkie Talkies!
“It can happen to you—even when you think it’s impossible,” Leffler warned.
And at Johnson Memorial Health, Franklin, Indiana, clinical laboratory tests took two hours to perform instead of 30 minutes, NPR said in its report on cyberattacks affecting Indiana providers. The lab had to use “runners” to share handwritten test results with caregivers and patients, NPR explained.
“You ask many CEOs across the country, ‘What keeps you up at night?’ Of course, they talk about workforce, financial pressures, and they say, ‘the possibility of a cyberattack,” John Riggi, National Advisor for Cybersecurity and Risk at the American Hospital Association (AHA), told NPR.
Cyberattacks Affect Surrounding Hospitals
To make matters worse, cyberattacks have a “blast radius” that impacts the healthcare community around an attacked provider, Christian Dameff, MD, Assistant Professor, Emergency Medical Services, University of California, San Diego, told ABC News. Dameff was lead author in a study that looked at how healthcare providers nearby to an attacked provider are affected.
“Hospitals adjacent to healthcare delivery organizations affected by ransomware attacks may see increases in patient census and may experience resource constraints affecting time-sensitive care for conditions such as acute stroke,” Dameff and co-authors wrote in a JAMA Open Network article titled, “Ransomware Attack Associated with Disruptions at Adjacent Emergency Departments in the US.”
“Healthcare cyberattacks such as ransomware are associated with greater disruptions to regional hospitals and should be treated as disasters,” they wrote.
Vigilance Is Required as Cyberattacks Increase
Ransomware attacks on hospitals climbed from 43 to 91 annually during the years 2016 to 2021, a separate study in JAMA Health Forum reported, adding that large organizations with multiple facilities were increasingly targeted.
The US experienced a 57% increase in cyberattacks in 2022 compared to 2021, according to a Check Point Research (CPR) report. Healthcare ranked second on the list of attacked industries due, according to Check Point, to the quantity and availability of personal and sensitive information, such as social security numbers and medical data.
“We expect the increase in cyber activity to only increase. With AI [artificial intelligence] technologies such as ChatGPT readily available, it is possible for hackers to generate malicious code and emails at a faster, more automated pace,” the CPR report noted.
For its part, the AHA said in a statement it plans to:
Work with federal agencies to mitigate cyber threats.
Advocate for increased government cybersecurity assistance.
Hospital clinical laboratory leaders need to be vigilant and work with colleagues to prevent cyberattacks. Check Point’s report advises, for example, avoiding malicious links and unexpected electronic attachments as well as verifying software is legitimate before downloading it. These are standard warnings, but they only work if staff members actually heed these actions.
Also important for diagnostics professionals is having a plan for performing clinical laboratory and anatomic pathology tests and distributing the results in the event of an attack.
Further development of this novel technology could result in new, more sensitive assays for clinical laboratories to use in the effort to improve antimicrobial stewardship in hospitals
Researchers at McMaster University in Ontario, Canada, have used artificial intelligence (AI) to identify a potential antibiotic that neutralizes the drug-resistant bacteria Acinetobacter baumannii, an antibiotic resistant pathogen commonly found in many hospitals. This will be of interest to clinical laboratory managers and microbiologists involved in identifying strains of bacteria to determine if they are antimicrobial-resistant (AMR) superbugs.
Using machine learning, the scientists screened thousands molecules to look for those that inhibited the growth of this specific pathogen. And they succeeded.
“We trained a neural network with this growth inhibition dataset and performed in silico predictions for structurally new molecules with activity against A. baumannii,” the researchers wrote in their published study.
They discovered that the molecule abaucin inhibited the growth of the antibiotic-resistant pathogen in vitro.
This shows how machine learning and AI technologies are giving biomedical researchers tools to identify new therapeutic drugs that are effective against drug-resistant strains of bacteria. This same research can be expected to lead to new clinical laboratory assays that determine if superbugs can be attacked by specific therapeutic drugs.
“When I think about AI in general, I think of these models as things that are just going to help us do the thing we’re going to do better,” Jonathan Stokes, PhD, Assistant Professor of Biomedicine and Biochemistry at McMaster University in Ontario, Canada, and lead author of the study, told USA Today. Clinical laboratory scientists and microbiologists will be encouraged by the McMaster University scientists’ findings. (Photo copyright: McMaster University.)
McMaster Study Details
Jonathan Stokes, PhD, head of the Stokes Laboratory at McMaster University, is Assistant Professor of Biomedicine/Biochemistry at McMaster and lead author of the study. Stokes’ team worked with researchers from the Broad Institute of MIT and Harvard to explore the effectiveness of AI in combating superbugs, USA Today reported.
“This work highlights the utility of machine learning in antibiotic discovery and describes a promising lead with targeted activity against a challenging Gram-negative pathogen,” the researchers wrote in Nature Chemical Biology.
Stokes Lab utilized the high-throughput drug screening technique, spending weeks growing and exposing Acinetobacter baumannii to more than 7,500 agents of drugs and active ingredients of drugs. When 480 compounds were uncovered that blocked the growth of bacteria, this information was then provided to a computer that was trained to run an AI algorithm, CNN reported.
“Once we had our [machine learning] model trained, what we could do then is start showing that model brand-new pictures of chemicals that it had never seen, right? And based on what it had learned during training, it would predict for us whether those molecules were antibacterial or not,” Stokes told CNN.
The model spent hours screening more than 6,000 molecules. It then narrowed the search to 240 chemicals, which were tested in the lab. The scientists pared down the results to the nine most effective inhibitors of bacteria. They then eliminated those that were either related to existing antibiotics or might be considered dangerous.
The researchers found one compound—RS102895 (abaucin)—which, according to Stokes, was likely created to treat diabetes, CNN reported. The scientists discovered that the compound prevented bacterial components from making their way from inside a cell to the cell’s surface.
“It’s a rather interesting mechanism and one that is not observed amongst clinical antibiotics so far as I know,” Stokes told CNN.
Because of the effectiveness of the antibiotic during testing on mice skin, the researchers believe this method may be useful for creating antibiotics custom made to battle additional drug resistant pathogens, CNN noted.
Defeating a ‘Professional Pathogen’
Acinetobacter baumannii (A. baumannii)—the focus of Stoke’s study—is often found on hospital counters and doorknobs and has a sneaky way of using other organisms’ DNA to resist antibiotic treatment, according to CNN.
“It’s what we call in the laboratory a professional pathogen,” Stokes told CNN.
A. baumannii causes infections in the urinary tract, lungs, and blood and typically wreaks havoc to vulnerable patients on breathing machines, in intensive care units, or undergoing surgery, USA Today reported.
A. baumannii is resistant to carbapenem, a potent antibiotic. The Centers for Disease Control and Prevention (CDC) reported that in 2017 the bacteria infected 8,500 people in hospitals, 700 of those infections being fatal.
Further, in its 2019 “Antibiotic Resistance Threats in the United States” report, the CDC stated that one out of every four patients infected with the bacteria died within one month of their diagnosis. The federal agency deemed the bacteria “of greatest need” for new antibiotics.
Thus, finding a way to defeat this particularly nasty bacteria could save many lives.
Implications of Study Findings on Development of new Antibiotics
The Stokes Laboratory study findings show promise. If more antibiotics worked so precisely, it’s possible bacteria would not have a chance to become resistant in the first place, CNN reported.
Next steps in Stokes’ research include optimizing the chemical structure and testing in larger animals or humans, USA Today reported.
“It’s important to remember [that] when we’re trying to develop a drug, it doesn’t just have to kill the bacterium,” Stokes noted. “It also has to be well tolerated in humans and it has to get to the infection site and stay at the infection site long enough to elicit an effect,” USA Today reported.
Stokes’ study is a prime example of how AI can make a big impact in clinical laboratory diagnostics and treatment.
“We know broad-spectrum antibiotics are suboptimal and that pathogens have the ability to evolve and adjust to every trick we throw at them … AI methods afford us the opportunity to vastly increase the rate at which we discover new antibiotics, and we can do it at a reduced cost. This is an important avenue of exploration for new antibiotic drugs,” Stokes told CNN.
Clinical laboratory managers and microbiologists may want to keep an open-mind about the use of AI in drug development. More research is needed to give substance to the McMaster University study’s findings. But the positive results may lead to methods for fine tuning existing antibiotics to better combat antimicrobial-resistant bacteria, USA Today reported.
New study shows how artificial neural networks are leading to improved microscopic capabilities and precision that could help researchers better understand causes of tumors
Pathologists, microbiologists, and clinical laboratory scientists engaged in research into cellular activity will be interested to learn that advances in artificial intelligence (AI) are leading to new opportunities for future research studies to observe and capture—in real time—biological processes in living cells/samples.
“EPFL biophysicists have now found a way to automate microscope control for imaging biological events in detail while limiting stress on the sample, all with the help of artificial neural networks. Their technique works for bacterial cell division, and for mitochondrial division,” according to Phys.org.
Even better, the EPFL scientists are making the control framework available as an open-source software plug-in for the microscope control program Micro-Manager. This enables clinical laboratories to integrate artificial intelligence into existing microscope control software, Phys.org noted.
“An intelligent microscope is kind of like a self-driving car. It needs to process certain types of information, subtle patterns that it then responds to by changing its behavior,” Suliana Manley, PhD, biophysicist and a professor in the Laboratory of Experimental Biophysics at the École Polytechnique Fédérale de Lausanne, told Phys.org. Clinical laboratories and anatomic pathology groups may want to explore the capabilities of this intelligent microscope technology. (Photo copyright: EPFL.)
EPFL Study Breakdown
Suliana Manley, PhD, biophysicist, professor, and head of the Laboratory of Experimental Biophysics at the EPFL, is the principal investigator of the “Intelligent microscope” study. She has spent her career focusing on the development of high-resolution optical instruments and the organization and dynamics of proteins.
Manley and her team learned how to detect mitochondrial divisions in bacteria such as Caulobacter Crescentus. These divisions can occur once every few minutes, but last only seconds. Their infrequency and ability to occur anywhere within the mitochondrial network makes them difficult to spot and photograph, Physics World noted.
To overcome this barrier, the EPFL team trained the neural network to look for mitochondrial constrictions—the shape change in mitochondria that leads to division—and combined that data with observations of the protein DRP1, the presence of which is required for spontaneous divisions to occur, Phys.org reported.
“A common goal of fluorescence microscopy is to collect data on specific biological events. Yet, the event-specific content that can be collected from a sample is limited, especially for rare or stochastic processes,” wrote the EPFL scientists in their Nature Methods paper. “We developed an event-driven acquisition framework, in which neural-network-based recognition of specific biological events triggers real-time control in an instant structured illumination microscope … we capture mitochondrial and bacterial divisions at imaging rates that match their dynamic timescales, while extending overall imaging durations. Because event-driven acquisition allows the microscope to respond specifically to complex biological events, it acquires data enriched in relevant content.”
Manley’s intelligent fluorescent microscope responds more rapidly than human control can achieve. When the microscope senses constrictions and DRP1 protein levels are high, it switches into high-speed image capture mode and gathers multiple images with minute detail. Conversely, when both constrictions and protein are low, the microscope goes into low-speed imaging mode, which preserves the integrity of the sample by avoiding excessive exposure to light, Phys.org noted.
Automating microscope control limits the stress placed on samples, increasing the likelihood of more accurate results. It also allows microscope control for imaging biological events in detail, as it eliminates human error that naturally occurs from trying to keep up with events in real time, Phys.org reported.
“Using a neural network, we can detect much more subtle events and use them to drive changes in acquisition speed,” Manley told Phys.org. “The potential of intelligent microscopy includes measuring what standard acquisitions would miss. We capture more events, measure smaller constrictions, and can follow each division in greater detail.”
What’s Next for EPFL?
Manley and her EPFL team plan to continue working with neural networks to detect different events and bring about different hardware responses.
“For example, we envision harnessing optogenetic perturbations to modulate transcription at key moments in cell differentiation,” she told Physics World. “We also think of using event detection as a means of data compression, selecting for storage or analysis the pieces of data that are most relevant to a given study.”
As research continues in bacterial cell division, there will be a point where the technology enables researchers to observe cell activity and what conditions cause abnormal (tumor) cells to be created. That would be the first step to then investigating ways to stop the cellular process that creates abnormal cells.
It should not surprise pathologists and clinical laboratory managers that researchers and technology developers are exploring ways to “turbocharge” classic light microscopy. Advances in image analysis, combined with machine learning algorithms, are making it possible to tease new insights from the images viewed with a standard microscope.
The speakers also noted that labs must learn to work collaboratively with payers—perhaps through health information technology (HIT)—to establish best practices that improve reimbursements on claims for novel genetic tests.
Harnessing the ever-increasing volume of diagnostic data that genetic testing produces should be a high priority for labs, said William Morice II, MD, PhD, CEO and President of Mayo Clinic Laboratories.
“There will be an increased focus on getting information within the laboratory … for areas such as genomics and proteomics,” Morice told the keynote audience at the Executive War College on Wednesday.
“Wearable technology data is analyzed using machine learning. Clinical laboratories must participate in analyzing that spectrum of diagnostics,” said William Morice II, MD, PhD (above), CEO and President of Mayo Clinic Laboratories. Morice spoke during this week’s Executive War College.
Precision Medicine Efforts Include Genetic Testing and Wearable Devices
For laboratories new to genetic testing that want to move it in-house, Morice outlined effective first steps to take, including the following:
Determine and then analyze the volume of genetic testing that a lab is sending out.
Research and evaluate genetic sequencing platforms that are on the market, with an eye towards affordable cloud-based options.
Build a business case to conduct genetic tests in-house that focuses on the long-term value to patients and how that could also improve revenue.
A related area for clinical laboratories and pathology practices to explore is their role in how clinicians treat patients using wearable technology.
For example, according to Morice, Mayo Clinic has monitored 20,000 cardiac patients with wearable devices. The data from the wearable devices—which includes diagnostic information—is analyzed using machine learning, a subset of artificial intelligence.
In one study published in Scientific Reports, scientists from Mayo’s Departments of Neurology and Biomedical Engineering found “clear evidence that direct seizure forecasts are possible using wearable devices in the ambulatory setting for many patients with epilepsy.”
Clinical laboratories fit into this picture, Morice explained. For example, depending on what data it provides, a wearable device on a patient with worsening neurological symptoms could trigger a lab test for Alzheimer’s disease or other neurological disorders.
“This will change how labs think about access to care,” he noted.
For Payers, Navigating Genetic Testing Claims is Difficult
While there is promise in genetic testing and precision medicine, from an administrative viewpoint, these activities can be challenging for payers when it comes to verifying reimbursement claims.
“One of the biggest challenges we face is determining what test is being ordered. From the perspective of the reimbursement process, it’s not always clear,” said Cristi Radford, MS, CGC, Product Director at healthcare services provider Optum, a subsidiary of UnitedHealth Group, located in Eden Prairie, Minnesota. Radford also presented a keynote at this year’s Executive War College.
Approximately 400 Current Procedural Terminology (CPT) codes are in place to represent the estimated 175,000 genetic tests on the market, Radford noted. That creates a dilemma for labs and payers in assigning codes to novel genetic tests.
During her keynote address, Radford showed the audience of laboratory executives a slide that charted how four labs submitted claims for the same high-risk breast cancer panel. CPT code choices varied greatly.
“Does the payer have any idea which test was ordered? No,” she said. “It was a genetic panel, but the information doesn’t give us the specificity payers need.”
In such situations, payers resort to prior authorization to halt these types of claims on the front end so that more diagnostic information can be provided.
“Plans don’t like prior authorization, but it’s a necessary evil,” said Jason Bush, PhD, Executive Vice President of Product at Avalon Healthcare Solutions in Tampa, Florida. Bush co-presented with Radford.
[Editor’s note: Dark Daily offers a free webinar, “Learning from Payer Behavior to Increase Appeal Success,” that teaches labs how to better understand payer behavior. The webinar features recent trends in denials and appeals by payers that will help diagnostic organizations maximize their appeal success. Click here to stream this important webinar.]
Payers Struggle with ‘Explosion’ of Genetic Tests
In “UnitedHealth’s Optum to Offer Lab Test Management,” Dark Daily’s sister publication The Dark Report, covered Optum’s announcement that it had launched “a comprehensive laboratory benefit management solution designed to help health plans reduce unnecessary lab testing and ensure their members receive appropriate, high-quality tests.”
Optum sells this laboratory benefit management program to other health plans and self-insured employers. Genetic test management capabilities are part of that offering.
As part of its lab management benefit program, Optum is collaborating with Avalon on a new platform for genetic testing that will launch soon and focus on identifying test quality, streamlining prior authorization, and providing test payment accuracy in advance.
“Payers are struggling with the explosion in genetic testing,” Bush told Executive War College attendees. “They are truly not trying to hinder innovation.”
For clinical laboratory leaders reading this ebriefing, the takeaway is twofold: Genetic testing and resulting precision medicine efforts provide hope in more effectively treating patients. At the same time, the genetic test juggernaut has grown so large so quickly payers are finding it difficult to manage. Thus, it has become a source of continuous challenge for labs seeking reimbursements.
Heath information technology may help ease the situation. But, ultimately, stronger communication between labs and payers—including acknowledgement of what each side needs from a business perspective—is paramount.
From ‘new-school’ rules of running a clinical laboratory to pharmacy partnerships to leveraging lab data for diagnostics, key industry executives discussed the new era of clinical laboratory and pathology operations
Opening keynotes at the 28th Annual Executive War College on Diagnostics, Clinical Laboratory, and Pathology Management taking place in New Orleans this week covered three main forces that healthcare and medical laboratory administrators should be preparing to address: new consumer preferences, new care models, and new payment models.
“COVID-19 didn’t change a whole lot of things in one sense, but it accelerated a lot of trends that were already happening in healthcare,” said Robert L. Michel, Editor-in-Chief of Dark Daily and its sister publication The Dark Report, and Founder of the Executive War College, during his opening keynote address to a packed ballroom of conference attendees. “Healthcare is transforming, and the transformation is far more pervasive than most consumers appreciate.
“Disintermediation, for example, is taking traditional service providers and disrupting them in substantial ways, and if you think about the end of fee-for-service, be looking forward because your labs can be paid for the value you originate that makes a difference in patient care,” Michel added.
Another opportunity for clinical laboratories, according to Michel, is serving Medicare Advantage plans which have soared in enrollment. “Lab leaders should be studying Medicare Advantage for how to integrate Medicare Advantage incentives into their lab strategies,” he said, highlighting the new influence of risk adjustment models which use diagnostic data to predict health condition expenditures.
Opening sessions at this week’s annual Executive War College on Diagnostics, Clinical Laboratory, and Pathology Management, presented by Robert L. Michel (above), Editor-in-Chief of Dark Daily and its sister publication The Dark Report, discussed demand for delivering healthcare services—including medical laboratory testing—as consumer preferences evolve, new care models are designed, and as payers seek value over volume. While these three forces may be challenging at the outset, they also create opportunities for clinical laboratories and pathology groups—a focal point of the Executive War College each year. (Photo copyright: The Dark Intelligence Group.)
Medical Laboratories Must Adapt to ‘New-School’ Rules
During his keynote address, Stan Schofield, Vice President and Managing Principal at The Compass Group, noted that while the basic “old-school” rules of successfully running a clinical laboratory have not changed—e.g., adding clients, keeping clients, creating revenue opportunities, getting paid, and reducing expenses—the interpretation of each rule has changed. The Compass Group is a trade federation based in South Carolina that serves not-for-profit healthcare integrated delivery networks (IDNs), including 32 health systems and 600 hospitals.
Schofield advised that when it comes to adding new clients under the “new-school” rules of lab management, clinical laboratory directors must be aware of and adapt to hospital integrations of core labs, clinical integrations across health systems, seamless services, direct contracting with employers in insurance relationships, and direct-to-consumer testing. Keeping clients, Schofield said, involves five elements:
Strong customer service.
A tailored metrics program for quality services based on what is important to a lab’s clients.
Balanced scorecards that look at the business opportunity and value proposition with each client.
Monitoring patients’ experiences and continuous improvement.
Participation in all payer agreements.
As to the problem of commoditization of laboratory goods and services, Schofield said, “Right now, we’re facing the monetization of the laboratory. We’re going to swiftly move from commoditization to monetization to commercialization.”
Pharmacies Enter the Clinical Laboratory Market
In another forward looking keynote address, David Pope, PharmD, CDE, Chief Pharmacy Officer at OmniSYS, XiFin Pharmacy Solutions, discussed the “test to treat” trend which could bring clinical laboratories and pharmacies together in new partnerships.
Diagnostics and pharmacy now intersect, according to Pope. “Pharmacists are on the move, and they are true contender as a new provider for you,” he said. “An area of pharmacy that is dependent upon labs is specialty medications.”
Specialty medicines now account for 55% of prescription spending, up from 28% in 2011, driven by growth in auto-immune and oncology, Pope noted. Other examples include companion diagnostics required for targeted treatments pertaining to all major cancers, and new areas like thalassemia (inherited blood disorders), obesity, next-generation sequencing, and pharmacogenomics, in addition to routine testing such as liver function and complete blood count (CBC).
Federal legislation may soon recognize pharmacists as healthcare providers who will be trained to perform specific clinical services, Pope said. Some states already recognize pharmacists as providers, he noted, explaining that pharmacies need lab data for three primary reasons:
Service—Pharmacies can act as a referral source to clinical laboratories. When referring, pharmacies may need to communicate lab test results to patients or providers to coordinate care.
Value-based care—Pharmacies would draw on data to counsel, prescribe, and coordinate care for chronic disease management, among other services.
Diagnostics and pharmacogenetics—Specialty medication workflows require documented test results within a specific timeframe prior to dispensing.
Another point Pope made: Large pharmacies are seeking lab partners. Labs that can provide rapid turnaround time and good pricing on complex tests provide pharmacies with partnership opportunities.
Using AI to Create Patients’ ‘Digital Twins’ That Help Identify Disease and Improve Care
High-tech healthcare technology underlies many opportunities in the clinical laboratory and pathology market, as evidenced throughout the Executive War College’s 2023 curriculum. An ongoing challenge for labs, however, is how to produce the valuable datasets that all labs have the potential to generate.
“It feels like we’ve come so far,” explained Brad Bostic, CEO of hc1 during his keynote address. “We’ve got the internet. We’ve got the cloud. All of this is amazing, but in reality, we have this massive proliferation of data everywhere and it’s very difficult to know how to actually put that into use. And nobody’s generating more data than clinical laboratories.
“Every single interaction with a patient that generates data gives you this opportunity to create the idea of a ‘digital twin.’ That means that labs are creating a mathematical description of what a person’s state is and using that information to look at how providers can optimally diagnose and treat that person. Ultimately, it is bigger than just one person. It’s hundreds of millions of people that are generating all this data, and many of these people fall into similar cohorts.”
This digital twin opportunity is heavily fueled by medical laboratory testing, Bostic said, adding that labs need to be able to leverage artificial intelligence (AI) to:
“I recommend lab leaders sit down with their teams and any outside partners they trust and identify what are their lab’s goals,” Bostic stated. “Think about how this technology can advance a lab’s mission. Look at strategy holistically—everything from internal operations to how patient care is affected.”
