Pathologists and clinical laboratories have an opportunity to help create newborn rWGS programs in their parent hospitals and health systems
Diagnosing disease in infants is particularly difficult using typical clinical laboratory testing and modalities. Thus, the use of rapid Whole Genome Sequencing (rWGS) is gaining acceptance when such a procedure is deemed “medically appropriate” based on the child’s symptoms.
In “Whole Genome Sequencing for Newborns Gains Favor,” Robert Michel, Editor-in-Chief of Dark Daily’s sister publication The Dark Report wrote, “Evidence is swiftly accumulating that use of rapid Whole Genome Sequencing for certain children in NICUs can enable diagnostic insights that guide effective interventions. Further, these pilot rWGS programs in children’s hospitals are showing a solid return on investment because of improved care. It is predicted that more hospitals may soon offer rWGS.”
Conducted at Tufts Medical Center in Boston, the researchers found that “Whole genome tests are nearly twice as good as narrower tests at unearthing genetic abnormalities that can cause disease in infants—the study found 49% of abnormalities, compared to 27% with more commonly used tests targeting particular types of genetic diseases,” the Associate Press reported.
The AP story follows the medical journey of a now 4-year-old who was diagnosed with a rare bleeding disorder. The nearly fatal condition was only caught because broad genetic testing found she suffered from factor XIII deficiency, a blood disorder characterized by the inability to clot properly.
“I’ve been doing clinical trials of babies for over 40 years,” neonatologist Jonathan Davis, MD (above), Chief, Division of Newborn Medicine at Tufts Children’s Hospital at Tufts Medical Center and Professor of Pediatrics, Tufts University School of Medicine, told the AP. “It’s not often that you can do something that you feel is going to really change the world and change clinical practice for everyone.” Clinical laboratories that work with oncologists to treat children suffering from cancer will understand Davis’ enthusiasm. (Photo copyright: Tufts Medicine.)
Incorporating Rapid Whole Genome Sequencing into Infant Care
Genetic diseases are responsible for 41% of infant deaths, according to a Rady Children’s Institute press release, which goes on to say the usage of rWGS may significantly improve the odds for infants born with genetic disorders.
“Broad use of genomic sequencing during the first year of life could have a much greater impact on infant mortality than was recognized hitherto,” said Stephen Kingsmore MD, President/CEO, Rady Children’s Institute for Genomic Medicine, which was one of the additional study sites for the Tufts Medicine researchers.
Genetic testing is already used to predict infant health outcomes, but the Tufts study highlights further developments that could improve the process. Prenatal genetic testing can be utilized both through carrier testing to determine any potential genetic red flags in the parents, and during prenatal screening and diagnostic testing of the fetus.
When an infant presents symptoms after birth, rWGS can then be implemented to cast a broad net to determine the best course of treatment.
According to ScienceDaily, the Tufts study found rWGS “to be nearly twice as effective as a targeted gene sequencing test at identifying abnormalities responsible for genetic disorders in newborns and infants.”
However, the rWGS tests took an average of six days to come back, whereas the targeted tests took only four days, ScienceDaily reported. Also, there is not full consensus on whether a certain gene abnormality is actually the cause of a specific genetic disorder.
“Many neonatologists and geneticists use genome sequencing panels, but it’s clear there are a variety of different approaches and a lack of consensus among geneticists on the causes of a specific patient’s medical disorder,” Jill Maron, MD, Vice Chair of Pediatric Research, Tufts Medical Center, and a co-principal investigator of the Tufts study, told Science Daily.
rWGS Costs versus Return on Investment
Some also question the upfront cost of genetic testing. It can be high, but it’s coming down and Maron stresses the importance of the tests.
“Genome sequencing can be costly, but in this targeted, at-risk population, it proves to be highly informative. We are supportive of ongoing efforts to see these tests covered by insurance,” she told ScienceDaily.
Each of the doctors associated with the Tufts study emphasized the importance of this testing and the good that can be done for this vulnerable group. The potential value to the children, they say, far outweighs the drawbacks of the testing.
“This study provides further evidence that genetic disorders are common among newborns and infants,” Kingsmore told ScienceDaily, “The findings strengthen support for early diagnosis by rapid genomic sequencing, allowing for the use of precision medicine to better care for this vulnerable patient population.”
For clinical laboratories, there is also good news about reimbursement for rWGS. In a story published last fall KFF Health News wrote, “Since 2021, eight state Medicaid programs have added rapid whole-genome sequencing to their coverage or will soon cover it, according to GeneDX, a provider of the test. That includes Florida … The test is also under consideration for coverage in Georgia, Massachusetts, New York, and North Carolina, according to the nonprofit Rady Children’s Institute for Genomic Medicine, another major provider of the test.”
“Collectively, these developments are encouraging children’s hospitals, academic centers, and tertiary care centers to look at establishing their own rWGS programs,” wrote Michel in The Dark Report. “In settings where this is appropriate, hospital and health system-based clinical laboratories have an opportunity to take an active role in helping jump start a newborn rWGS program in their institutions.”
Pathologists should continue to monitor rWGS, as well as prenatal and carrier testing, to have a full awareness of its growing use in infant and young child cancer screening.
Though they are a mystery, once solved, Obelisks could lead to new biomarkers for clinical laboratory testing
Microbiologists and clinical laboratories know that human microbiota play many important roles in the body. Now, scientists from Stanford University have discovered an entirely new class of “viroid-like” lifeforms residing inside the human body. The researchers detected their presence in both the gut microbiome and saliva samples. Most interesting of all, the researchers are not sure what the lifeforms actually are.
The Stanford researchers, led by PhD student Ivan Zheludev, called the new discovery “Obelisks” due to their RNA structures, which are short and can fold into structures that resemble rods.
The scientists believe the Obelisks went undetected until now in the human microbiome due to their compact genetic elements, which are only around 1,000 characters or nucleotides in size. A typical human DNA structure consists of around three billion nucleotides.
In an article they published on the biology preprint server bioRxiv titled, “Viroid-like Colonists of Human Microbiomes,” the Stanford researchers wrote, “Here, we describe the ‘Obelisks,’ a previously unrecognized class of viroid-like elements that we first identified in human gut metatranscriptomic data. … Obelisks comprise a class of diverse RNAs that have colonized and gone unnoticed in human and global microbiomes.”
The researchers discovered that Obelisks “form their own distinct phylogenetic group with no detectable sequence or structural similarity to known biological agents.”
This is yet another example of how researchers are digging deeper into human biology and finding things never before identified or isolated.
“I am really impressed by the approach. The authors were really creative,” computational biologist Simon Roux, PhD (above) of the Department of Energy (DEO) Joint Genome Institute at Lawrence Berkeley National Laboratory told Science in response to the Stanford researcher’s published findings. “I think this [work] is one more clear indication that we are still exploring the frontiers of this viral universe. This is one of the most exciting parts of being in this field right now. We can see the picture of the long-term evolution of viruses on Earth start to slowly emerge.” How these findings might eventually spark new biomarkers for clinical laboratory testing remains to be seen. (Photo copyright: Berkeley Lab.)
Researchers Bewildered by Obelisks
In their study, “Zheludev and team searched 5.4 million datasets of published genetic sequences and identified almost 30,000 different Obelisks. They appeared in about 10% of the human microbiomes the team examined,” Science reported.
The Stanford researchers found that various types of Obelisks seem to inhabit different areas of the body. In one dataset, the Obelisks were found in half of the oral samples.
The function of Obelisks is unknown, but their discovery is bewildering experts.
Rod-like secondary structures encompassing the entire genome, and
Open reading frames coding for a novel protein superfamily, which the researchers dubbed “Oblins.”
At least half of the genetic material of the Obelisks was taken up by these Oblins. The researchers suspect those proteins may be involved in the replication process of the newly-discovered lifeforms.
The Oblins are also significantly larger than other genetic molecules that live inside cells and they do not have the genes to create protein shells that RNA viruses live within when they are outside of cells.
“Obelisks, therefore, need some kind of host. The researchers managed to identify one: A bacterium called Streptococcus sanguinis that lives mostly in dental plaque in our mouths. Exactly which other hosts obelisks inhabit is yet another mystery, as are what they do to their host and how they spread,” Vice reported.
“While we don’t know the ‘hosts’ of other Obelisks, it is reasonable to assume that at least a fraction may be present in bacteria,” the researchers noted in their bioRxiv paper.
Researchers are Stumped
The Stanford scientists were unable to identify any impact the Obelisks were having on their bacterial hosts—either negative or positive—or determine how they could spread between cells.
“These elements might not even be ‘viral’ in nature and might more closely resemble ‘RNA plasmids,’” they concluded in their paper.
The Stanford scientists are uncertain as to where or what the hosts of the Obelisks are, but they suspect that at least some of them are present in bacteria. However, Obelisks do not appear to be similar to any biological agents that could provide a link between genetic molecules and viruses.
And so, Obelisks are a true mystery—one the Stanford researchers may one day solve. If they do, new biomarkers for clinical laboratory testing may not be far behind.
Initially thought to be an attack by a nation-state, actual culprit turned out to be a known ransomware group and each day brings new revelations about the cyberattack
Fallout continues from cyberattack on Change Healthcare, the revenue cycle management (RCM) company that is a business unit of Optum, itself a division of UnitedHealth Group. Recent news accounts say providers are losing an estimated $100 million per day because they cannot submit claims to Change Healthcare nor receive reimbursement for these claims.
The cyberattack took place on February 21. The following day, UnitedHealth Group filed a Material Cybersecurity Incidents report (form 8-K) with the US Securities and Exchange Commission (SEC) in which it stated it had “identified a suspected nation-state associated cybersecurity threat actor [that] had gained access to some of the Change Healthcare information technology systems.”
A few days later the real identity of the threat actor was revealed to be a ransomware group known as “BlackCat” or “ALPHV,” according to Reuters.
Change Healthcare of Nashville, Tenn., is “one of the largest commercial prescription processors in the US,” Healthcare Dive reported, adding that hospitals, pharmacies, and military facilities had difficulty transmitting prescriptions “as a result of the outage.”
Change Healthcare handles about 15 billion payments each year.
According to a Change Healthcare statement, the company “became aware of the outside threat” and “took immediate action to disconnect Change Healthcare’s systems to prevent further impact.”
Change Healthcare has provided a website where parties that have been affected by the cyberattack can find assistance and updated information on Change’s response to the intrusion and theft of its data.
“The fallout is only starting to happen now. It will get worse for consumers,” Andrew Newman (above), founder and Chief Technology Officer, ReasonLabs, told FOX Business, adding, “We know that the likely destination for [the Change Healthcare] data is the Dark Web, where BlackCat will auction it all off to the highest bidder. From there, consumers could expect to suffer from things like identity theft, credit score downgrades, and more.” Clinical laboratories are also targets of cyberattacks due to the large amount of private patient data stored on their laboratory information systems. (Photo copyright: ReasonLabs.)
Millions of Records May be in Wrong Hands
Reuters reported that ALPHV/BlackCat admitted it “stole millions of sensitive records, including medical insurance and health data from the company.”
The ransomware group has been focusing its attacks on healthcare with 70 incidents since December, according to federal agencies.
In a letter to HHS, AHA warned, “Change Healthcare’s downed systems will have an immediate adverse impact on hospital finances. … Their interrupted technology controls providers’ ability to process claims for payment, patient billing, and patient cost estimation services.”
“My understanding is Change/Optum touches almost every hospital in the US in one way or another,” John Riggi, AHA’s National Advisor for Cybersecurity and Risk, told Chief Healthcare Executive. “It has sector wide impact in potential risk. So, really, this is an attack on the entire sector.” Riggi spent nearly 30 years with the FBI.
Some physician practices may also have been impacted by the Change Healthcare cyberattack, according to the Medical Group Management Association (MGMA). In a letter to HHS, MGMA described negative changes in processes at doctors’ offices. They include delays in paper and electronic statements “for the duration of the outage.”
In addition, “prescriptions are being called into pharmacies instead of being electronically sent, so patients’ insurance information cannot be verified by pharmacies, and [the patients] are forced to self-pay or go without necessary medication.”
Here are “just a few of the consequences medical groups have felt” since the Change Healthcare cyberattack, according to the MGMA:
Substantial billing and cash flow disruptions, such as a lack of electronic claims processing. Both paper and electronic statements have been delayed. Some groups have been without any outgoing charges or incoming payments for the duration of the outage.
Limited or no electronic remittance advice from health plans. Groups are having to manually pull and post from payer portals.
Prior authorization submissions have been rejected or have not been transmittable at all. This further exacerbates what is routinely ranked the number one regulatory burden by medical groups and jeopardizes patient care.
Groups have been unable to perform eligibility checks for patients.
Many electronic prescriptions have not been transmitted, resulting in call-in prescriptions to pharmacies or paper prescriptions for patients. Subsequently, patients’ insurance information cannot be verified by pharmacies, and they are forced to self-pay or go without necessary medication.
Lack of connectivity to important data infrastructure needed for success in value-based care arrangements, and other health information technology disruptions.
Medical laboratory leaders and pathologists are advised to consult with their colleagues in IT and cybersecurity on how to best prevent ransomware attacks. Labs hold vast amount of private patient information. Recent incidents suggest more steps and strategies may be needed to protect laboratory information systems and patient data.
This comes on top of months of strikes by NZ medical laboratory workers seeking fair pay and safe working conditions
Te Whatu Ora (aka, Health New Zealand, the country’s publicly funded healthcare system) recently ordered health and safety checks at multiple clinical laboratories in 18 districts across the country. This action is the result of safety issues detected after procedural discrepancies were discovered in separate labs.
According to Radio New Zealand(RNZ), Health New Zealand found “significant risks” at some medical laboratories and that “staff at one in Auckland were exposed to toxic fumes, at others two [people] caught typhoid, and delays jeopardized patients’ care.”
“Two lab workers were hospitalized this year after having caught typhoid from samples, one at a private lab in Auckland, and a second at Canterbury Health Laboratories, CHL,” RNZ reported.
A Health New Zealand internal document states there will need to be a “comprehensive” fix to deal with risks present in the island nation’s medical laboratory industry. The assessment states that the organization needs “a more detailed picture of the occupational health and health and safety risks present in our laboratories,” RNZ reported.
“The overall state of the laboratories and the practices they have in place pose an inherited risk from the former DHBs [district health boards] and will likely need a comprehensive approach to addressing significant and/or ongoing risks,” Health New Zealand said in the internal document. “There is growing demand on our laboratories in terms of the volume of the work, which can put pressure on processes, and work is often undertaken in facilities that, over time, may have become not fit for purpose.”
This story as an example of how clinical laboratory staff can be exposed to disease and toxic chemicals when procedures are not diligently followed. It is a reminder to all lab managers that diligence in following protective protocols is imperative.
“Te Whatu Ora is committed to identifying, tracking and mitigating all potential risks and issues within our service until they are fully resolved and no longer identifiable as an issue/risk,” Rachel Haggerty (above), Director, Strategy, Planning and Purchasing, Hospital and Specialist Services, for Health New Zealand told NZ Doctor. Clinical laboratory workers in New Zealand have been striking for fair pay and safe working environments for months. Now, they risk becoming infected by deadly pathogens and chemicals as well. (Photo copyright: NZ Doctor.)
Lab Worker Strikes and Staff Shortages
Community Anatomic Pathology Services in Auckland lost its histology accreditation last year because it was discovered that lab workers were exposed to toxic chemical levels at the facility. In addition, patients were forced to wait weeks for test results from that lab.
The laboratory was also penalized back in 2017 for how substances were handled when formaldehyde levels in excess of the recommended limits were detected.
Bryan Raill, a medical scientist at the Counties Manukau District Health Board, said the laboratory workers union in New Zealand believes staff shortages and lab conditions are contributing to the lab woes. Raill is also president of the medical laboratory workers division of APEX, a specialist union representing more than 4,000 allied, scientific, and technical health professionals throughout New Zealand.
“It’s not only your physical environment, being safe there, but you have to be safe in terms of what you do,” Raill told RNZ.
Raill said the two typhoid infections were a red flag and that Te Whatu Ora needs to do more.
“They’re stepping out of the inertia they’ve been bound, so this is a good thing, but it needs to be a wider thing,” he said.
“They should look at the other health and safety aspect of the workload and the work environment that staff are working under,” Raill explained in an iHeart podcast. “The person who caught typhoid in Christchurch spent four days in ICU, and there had been a workplace exposure to another pathogen two years earlier and the recommendations that came out of that hadn’t been followed. For example, [the lab workers] were not vaccinated against typhoid.”
IT Implementation Delays also to Blame
Along with strikes and staff shortages, clinical laboratories in New Zealand are also dealing with information technology (IT) issues. Technical problems have delayed some needed lab upgrades by more than a year.
In addition, “The impacts of new test, surgeries, and medicines/treatments on pathology services have also historically not been understood well nor accounted for and we are considering a number of options, as outlined in the risk register, to manage this,” said Rachel Haggerty, Director, Strategy, Planning and Purchasing, Hospital and Specialist Services, for Te Whatu Ora.
Future efforts will deal with training of lab personnel and focus on ventilation and hazardous substance management.
Dark Daily has reported extensively on the ongoing problems within New Zealand clinical laboratory industry.
Clinical laboratory personnel can be exposed to dangerous diseases and toxic chemicals when procedures are not diligently followed. This latest situation in New Zealand serves as a reminder that following protective protocols is imperative in labs worldwide to protect workers and patients.
Findings suggest new medical guidelines may be needed to determine when to perform clinical laboratory cancer screenings on people under 50
From 1990-2019, new diagnoses of early-onset cancer in individuals under 50 years of age increased by 79%, according to a British Medical Journal (BMJ) news release describing research published last year in BMJ Oncology. The question for anatomic pathology laboratories to consider is, why are more people under 50 being diagnosed with cancer than in earlier years? And do medical guidelines need to be changed to allow more cancer screening for individuals under 50-years old?
This new revelation challenges previously held beliefs about the number of younger adults under 50 experiencing early-onset cancer. Patients can sometimes miss symptoms by attributing them to a more benign condition.
“While cancer tends to be more common in older people, the evidence suggests that cases among the under 50s have been rising in many parts of the world since the 1990s. But most of these studies have focused on regional and national differences; and few have looked at the issue from a global perspective or the risk factors for younger adults, say the researchers. In a bid to plug these knowledge gaps, they drew on data from the Global Burden of Disease 2019 Study for 29 cancers in 204 countries and regions,” the BMJ news release states.
According to the news release, “Breast cancer accounted for the highest number of ‘early-onset’ cases in this age group in 2019. But cancers of the windpipe (nasopharynx) and prostate have risen the fastest since 1990, the analysis reveals. Cancers exacting the heaviest death toll and compromising health the most among younger adults in 2019 were those of the breast, windpipe, lung, bowel, and stomach.”
Although these statistics are being seen worldwide, the highest rates are in North America, Australasia, and Western Europe. However, high death rates due to cancer are also being seen in Eastern Europe, Central Asia, and Oceania. Economic disparities in the latter geographical regions may account for both fewer diagnoses and higher death rates.
“And in low to middle income countries, early onset cancer had a much greater impact on women than on men, in terms of both deaths and subsequent poor health,” the BMJ news release noted.
In an editorial they published in BMJ Oncology on the study findings, Ashleigh Hamilton, PhD (left), Academic Clinical Lecturer, and Helen Coleman, PhD (right), Professor, School of Medicine, Dentistry and Biomedical Sciences, both at the Center for Public Health at Queen’s University Belfast in the UK wrote, “The epidemiological landscape of cancer incidence is changing. … Prevention and early detection measures are urgently required, along with identifying optimal treatment strategies for early-onset cancers, which should include a holistic approach addressing the unique supportive care needs of younger patients.” Anatomic pathology laboratories will play an important role in diagnosing and treating younger cancer patients. (Photo copyrights: Queen’s University Belfast.)
What Caused the Increase?
“It’s such an important question, and it points to the need for more research in all kinds of domains—in population science, behavioral health, public health, and basic science as well,” said medical oncologist Veda Giri, MD, Professor of Internal Medicine, Yale School of Medicine, in a news release. Giri directs the Yale Cancer Center Early-Onset Cancer Program at Smilow Cancer Hospital.
Although experts are still trying to determine exactly where these cases are coming from, signs point to both genetic and lifestyle factors, the BMJ news releases noted. Tobacco and alcohol use, diets high in cholesterol and sodium, and physical inactivity are all lifestyle risk factors. Experts recommend a healthy diet and exercise routine with minimal alcohol consumption.
As for family history? “We’re beginning to recognize that family history is very important,” says Jeremy Kortmansky, MD, also a Yale Medicine medical oncologist.
According to CNN Health, these rates of early-onset cancer are more common in female patients, with rates going up an average of 0.67% each year.
“For young women who have a significant family history of cancer in the family, we are starting to refer them to a high-risk clinic—even if the cancer in their family is not breast cancer,” Kortmansky noted.
Doctors advise patients to implement healthy habits into their lives, not ignore symptoms, advocate for themselves, and be aware of their family history. Cancer patients may be prescribed cancer treatments at a much earlier age. Medical guidelines for patients may continue to shift and change. And oncologists may be incorporating alternative therapies to help younger patients deal with the shock of their diagnosis.
Will Cancer Rates Continue to Rise?
“Based on the observed trends for the past three decades, the researchers estimate that the global number of new early-onset cancer cases and associated deaths will rise by a further 31% and 21% respectively in 2030, with those in their 40s the most at risk,” the BMJ news release noted.
In an editorial they penned for BMJ Oncology on the findings of the cancer study titled, “Shifting Tides: The Rising Tide of Early-Onset Cancers Demands Attention,” Ashleigh Hamilton, PhD, Academic Clinical Lecturer, and Helen Coleman, PhD, Professor, School of Medicine, Dentistry and Biomedical Sciences, both at the Center for Public Health at Queen’s University Belfast in the UK wrote, “Full understanding of the reasons driving the observed trends remains elusive, although lifestyle factors are likely contributing, and novel areas of research such as antibiotic usage, the gut microbiome, outdoor air pollution, and early life exposures are being explored. It is crucial that we better understand the underlying reasons for the increase in early-onset cancers, in order to inform prevention strategies.”
Clinical laboratories should be aware of these findings and the changing landscape of cancer screenings, as they will play a key role in diagnoses. Younger patients may be advocating for cancer screenings and doctors may be ordering them depending on the patient’s symptoms and family history. Anatomic pathology professionals should expect new guidelines when it comes to cancer diagnostics and treatment.
This is the third of a three-part series on revenue cycle management for molecular testing laboratories and pathology practices, produced in collaboration with XiFin Inc.
Automation and AI-Powered Workflow Paves the Way for Consistent, Optimized Molecular Diagnostics and Pathology RCM
Third in a three-part series, this article will discuss how sophisticated revenue cycle management technology, including artificial intelligence (AI) capabilities, drives faster, more efficient revenue reimbursement for molecular and pathology testing.
Financial and operational leaders of molecular testing laboratories and pathology groups are under pressure to maximize the revenue collected from their services rendered. This is no easy task. Molecular claims, in particular, can be especially complex. This article outlines the specific areas in which automation and artificial intelligence (AI)-based workflows can improve revenue cycle management (RCM) for molecular diagnostic and pathology organizations so they can better meet their operational and financial goals.
AI can play a number of important roles in business. When it comes to RCM for diagnostic organizations, first and foremost, AI can inform decision-making processes by generating new or derived data, which can be used in reporting and analytics. It can also help understand likely outcomes based on historical data, such as an organization’s current outstanding accounts receivable (AR) and what’s likely to happen with that AR based on historic performance.
AI is also deployed to accelerate the creation of configurations and workflows. For example, generated or derived data can be used to create configurations within a revenue cycle workflow to address changes or shifts in likely outcomes, such as denial rates. Suppose an organization is using AI to analyze historical denial data and predict denial rates. In that case, changes in those predicted denial rates can be used to modify a workflow to prevent those denials upfront or to automate appeals on the backend. This helps organizations adapt to changes more quickly and accelerates the time to reimbursement.
“Furthermore, AI is used to automate workflows by providing or informing decisions directly,“ says Clarisa Blattner, XiFin Senior Director of Revenue and Payor Optimization. “In this case, when the AI sees shifts or changes, it knows what to do to address them. This enables an organization to take a process in the revenue cycle workflow that is very human-oriented and automate it.”
AI is also leveraged to validate data and identify outcomes that are anomalous, or that lie outside of the norm. This helps an organization:
Ensure that the results achieved meet the expected performance
Understand whether the appropriate configurations are in place
Identify if an investigation is required to uncover the reason behind any anomalies so that they can be addressed
Finally, AI can be employed to generate content, such as letters or customer support materials.
Everything AI starts with data
Everything AI-related starts with the data. Without good-quality data, organizations can’t generate AI models that will move a business forward. In order to build effective AI models, an organization must understand the data landscape and be able to monitor and measure performance and progress and adjust the activities being driven, as necessary.
Dirty, unstructured data leads to unintelligent AI. AI embodies the old adage, “garbage in, garbage out.” The quality of the AI decision or prediction is entirely based on the historical data that it’s seen. If that data is faulty, flawed, or incomplete, it can lead to bad decisions or the inability to predict or make a decision at all. Purposeful data modeling is critical to AI success, and having people and processes that can understand the complicated RCM data and structure it so it can be effectively analyzed is vital to success.
The next step is automation. Having effective AI models that generate strong predictions is only as valuable as the ability to get that feedback into the revenue cycle system effectively. If not, that value is minimal, because the organization must expend a lot of human energy to try to reconfigure or act on the AI predictions being generated.
There is a typical transformation path, illustrated below, that organizations go through to get from having data stored in individual silos to fully embedded AI. If an organization is struggling with aggregating data to build AI models, it’s at stage one. The goal is stage five, where an organization uses AI as a key differentiator and AI is a currency, driving activity.
The transformation starts with structuring data with an underlying data approach that keeps it future-ready. It is this foundation that allows organizations to realize the benefits of AI in a cost-effective and efficient way. Getting the automation embedded in the workflow is the key to getting to the full potential of AI in improving the RCM process.
Real-world examples of how AI and automation improve RCM
One example of how AI can improve the RCM process is using AI to discover complex payer information. One significant challenge for diagnostic service providers is ensuring that the right third-party insurance information for patients is captured. This is essential for clean claims submission. Often, the diagnostic provider is not the organization that actually sees the patient, in which case it doesn’t have the ability to collect that information directly. The organization must rely on the referring physician or direct outreach to the patient for this data when it’s incorrect or incomplete.
Diagnostic providers are sensitive to not burdening referring clients or patients with requests for demographic or payer information. It’s important to make this experience as simple and smooth as possible. Also, insurance information is complicated. A lot of data must be collected or corrected if the diagnostic provider doesn’t have the correct information.
Automating this process is difficult. Frequently, understanding who the payer is and how that payer translates into contracts and mapping within the revenue cycle process requires an agent to be on the phone with the patient. It can be very difficult for a patient to get precise payer plan information from their insurance card without the help of a customer service representative.
This is where AI can help. The goal is to require the smallest amount of information from a patient and be able to verify eligibility through electronic means with the payer. Using optical character recognition (OCR), an organization can take an image of the front and back of a patient’s insurance card, isolate the relevant text, and use an AI model to get the information needed in order to generate an eligibility request and confirm eligibility with that payer.
In the event that taking an image of the insurance card is problematic for a patient, the organization can have the patient walk through a simplified online process, for example, through a patient portal, and provide just a few pieces of data to be able to run eligibility verification and get to confirmed eligibility with the payer.
AI can help with this process too. For example, the patient can provide high-level payer information only, such as the name of the commercial payer or whether the coverage is Medicare or Medicaid, the state the patient resides in, and the subscriber ID and AI can use this high-level data to get an eligibility response and confirmed eligibility.
Once the eligibility response is received, the more detailed payer information can be presented back to the patient for confirmation. AI can map the eligibility response to the appropriate contract or payer plan within the RCM system.
Now that the patient’s correct insurance information is captured, the workflow moves on to collecting the patient’s financial responsibility payment. To do that, the organization needs to be able to calculate the patient’s financial responsibility estimate. The RCM system has accurate pricing information and now has detailed payer and plan information, a real-time eligibility response, as well as test or procedure information. This data can be used to estimate patient financial responsibility.
AI can also be used to address and adapt to changes in ordering patterns, payer responses, and payer reimbursement behavior. The RCM process can be designed to incorporate AI to streamline claims, denials, and appeals management, as well as to assign work queues and prioritize exception processing (EP) work based on the likelihood of reimbursement, which improves efficiency.
One other way AI can help is in understanding and or maintaining “expect” prices—what an organization can expect to collect from particular payers for particular procedures. For contracted payers, contracted rates are loaded into the RCM system. It’s important to track whether payers are paying those contracted rates and whether the organization is receiving the level of reimbursement expected. For non-contracted payers, it’s harder to know what the reimbursement rate will be. Historical data and AI can provide a good understanding of what can be expected. AI can also be used to determine if a claim is likely to be rejected because of incorrect or incomplete payer information or patient ineligibility, in which case automation can be applied to resolve most issues.
Another AI benefit relates to quickly determining the probability of reimbursement and assigning how claims are prioritized if a claim requires intervention that cannot be automated. With AI, these claims that require EP are directed to the best available team member, based on that particular team member’s past success with resolving a particular error type.
The goal with EP is to ensure that the claims are prioritized to optimize reimbursement. This starts with understanding the probability of the claim being reimbursed. An AI model can be designed to assess the likelihood of the claim being reimbursed and the likely amount of reimbursement for those expected to be paid. This helps prioritize activities and optimize labor resources. The AI model can also take important factors such as timely filing dates into account. If a claim is less likely to be collected than another procedure but is close to its timely filing deadline, it can be escalated. The algorithms can be run nightly to produce a prioritized list of claims with assignments to the specific team member best suited to address each error.
AI can also be used to create a comprehensive list of activities and the order in which those activities should be performed to optimize reimbursement. The result is a prioritized list for each team member indicating which claims should be worked on first and which specific activities need to be accomplished for each claim.
Summing it all up, organizations need an RCM partner with a solid foundation in data and data modeling. This is essential to being able to effectively harness the power of AI. In addition, the RCM partner must offer the supporting infrastructure to interface with referring clients, patients, and payers. This is necessary to maximize automation and smoothly coordinate RCM activities across the various stakeholders in the process.
Having good AI and insight into data and trends is important, but the ability to add automation to the RCM process based on the AI really solidifies the benefits and delivers a return on investment (ROI). Analytics are also essential for measuring and tracking performance over time and identifying opportunities for further improvement.
Diagnostic executives looking to maximize reimbursement and keep the cost of collection low will want to explore how to better leverage data, AI, automation, and analytics across their RCM process.
This is the third of a three-part series on revenue cycle management for molecular testing laboratories and pathology practices, produced in collaboration with XiFin Inc. Missed the first two articles? www.darkdaily.com
