Switching from non-profit to for-profit may affect how clinical laboratories operate in the new healthcare system
Shifting away from fee-for-service payment models and towards value-based healthcare is the goal of many non-profit hospital systems. One such transformation is underway at Summa Health, one of the largest integrated delivery networks (IDNs) in Ohio. On January 17, venture capital firm General Catalyst announced that its subsidiary—Health Assurance Transformation Corporation (HATCo)—had entered into an agreement to purchase Summa Health.
“HATCo’s investment into Summa Health will drive not only near-term benefit to the organization and the patients it serves but also sustainable, long-term transformation through a true shift to value-based care and access to new revenue streams, resources, innovations, and technologies,” states a General Catalyst news release penned by Marc Harrison, MD, CEO of HATCo.
Harrison was formerly President and CEO of Intermountain Healthcare, a 33 hospital not-for-profit IDN in Salt Lake City, Utah. This is a noteworthy fact because Intermountain Health has a national reputation as an innovative multi-hospital health system. Some observers believe that Harrison’s involvement signals that General Catalyst believes it has a care model that can deliver better patient care in a profitable manner.
“Under its new structure, Summa will become a for-profit organization, and General Catalyst says it will introduce new tech-enabled solutions that aim to make care more accessible and affordable,” CNBCreported.
“This is the first time that anybody has done anything quite like this,” Harrison told CNBC. “There are many digital health solutions that are out there as point solutions. This is the first holistic transformation of a health system to a thoughtful combination of digital and in-person care.”
“Our intent is to build on and augment the system’s considerable strengths. First and foremost, we share Summa Health’s commitment to serving all members of the community,” wrote HATCo CEO Marc Harrison, MD (above), in a news release. “The Summa Health team also shares our belief that achieving healthcare transformation will require a shift to value-based care … Together, we intend to demonstrate that a model that is better for patients can also be good for business, creating a blueprint for other health systems to effectively serve all people in their communities.” How this shift will affect Summa’s clinical laboratories remains to be seen. (Photo copyright: General Catalyst.)
Betting on Healthcare
In 2023, General Catalyst, an American venture capital firm headquartered in Cambridge, Mass., unveiled its Health Assurance Transformation Corporation (HATCo) and began shopping for a health system to buy.
HATCo has 20 healthcare systems in a network that spans 43 states and four countries, according to Healthcare Dive. The company’s news release states it has been focused on three areas since its start-up:
Helping its partners on their “transformation journeys.”
Planning to “acquire and operate a health system for the long-term.”
“The goal of the purchase is for the health system to act as a proving ground for General Catalyst to test ways to improve hospital operations and patient care, without risk aversion or cash shortfalls, management said,” Healthcare Dive reported.
Thus, the firm’s announcement to purchase a health system last October “sent shockwaves through the healthcare industry” according to Healthcare Dive.
“At its core, General Catalyst’s long-term Health Assurance thesis is that value-based care not only is good for patients, but also can be a successful business model if deployed with innovative technology at meaningful scale. Its rationale for buying a health system is a belief that it can improve on the traditional model of not-for-profit health system governance and management by embedding new incentives,” wrote Christopher Kerns, CEO and co-founder of Washington, D.C-based research firm Union Healthcare Insight, in a blog post analysis.
General Catalyst’s HATCo may offer up “a profit motive, a longer time horizon, and a channel for dozens of innovative companies to demonstrate value,” he noted.
“The single biggest barrier to promising young healthcare companies is an inability to scale. Many of their innovations—in digital health, patient engagement, revenue cycle workflow, etc.—require willing health system partners who are famously conservative in their investments and service providers, and rarely take risks on newbies. The addition of Summa provides an open laboratory for those innovations,” Kerns added.
Is the Summa Health Deal Good for Healthcare?
Some in the industry were taken aback by General Catalyst’s announcement.
“A lot of people feel like a PE (private equity) or venture capital company owning a hospital is kind of like asking Freddy Krueger to come babysit your kids. It just makes people a little nervous, and it doesn’t feel quite aligned with this concept of healthcare being a human right,” John Bass, CEO of Hashed Health, a Nashville, Tenn.-based healthcare venture studio, told CNBC.
Nevertheless, it’s a moot point. HATCo is moving forward with its purchase of Summa Health.
“For this bet to work, Summa will have to be a solid proving ground for [General Catalyst’s] portfolio companies. And that means either Summa itself will have to grow, or it will have to act as a force multiplier for its other value-based portfolio companies to justify the considerable capital expended. I have to say, that’s a tall order, but not an insane one,” said Kerns in the Union Healthcare Insight blog post.
Healthcare managers may find it interesting to follow HATCo and Summa Health on their planned journey. The results may speak for themselves. Either way, clinical laboratories and anatomic pathology group practices in HATCo’s health system may be in for some interesting changes.
Forces in play will directly impact the operations and financial stability of many of the nation’s clinical laboratories
With significant regulatory changes expected in the next 18 to 24 months, experts are predicting a “Perfect Storm” for managers of clinical laboratories and pathology practices.
Currently looming are changes to critical regulations in two regulatory areas that will affect hospitals and medical laboratories. One regulatory change is unfolding with the US Food and Drug Administration (FDA) and the other regulatory effort centers around efforts to update the Clinical Laboratory Improvement Amendments of 1988 (CLIA).
The major FDA changes involve the soon-to-be-published Final Rule on Laboratory Developed Tests (LDTs), which is currently causing its own individual storm within healthcare and will likely lead to lawsuits, according to the FDA Law Blog.
In a similar fashion—and being managed under the federal Centers for Medicare and Medicaid Services (CMS)—are the changes to CLIA rules that are expected to be the most significant since 2003.
The final element of the “Perfect Storm” of changes coming to the lab industry is the increased use by private payers of Z-Codes for genetic test claims.
In his general keynote, Robert L. Michel, Dark Daily’s Editor-in-Chief and creator of the 29th Executive War College on Diagnostics, Clinical Laboratory, and Pathology Management, will set the stage by introducing a session titled, “Regulatory Trifecta Coming Soon to All Labs! Anticipating the Federal LDT Rule, Revisions to CLIA Regulations, and Private Payers’ Z-Code Policies for Genetic Claims.”
“There are an unprecedented set of regulatory challenges all smashing into each other and the time is now to start preparing for the coming storm,” says Robert L. Michel (above), Dark Daily’s Editor-in-Chief and creator of the 29th Executive War College on Diagnostics, Clinical Laboratory, and Pathology Management, a national conference on lab management taking place April 30-May 1, 2024, at the Hyatt in New Orleans. (Photo copyright: The Dark Intelligence Group.)
Coming Trifecta of Disruptive Forces to Clinical Laboratory, Anatomic Pathology
The upcoming changes, Michel notes, have the potential to cause major disruptions at hospitals and clinical laboratories nationwide.
“Importantly, this perfect storm—which I like to describe as a Trifecta because these three disruptive forces that will affect how labs will conduct business—is not yet on the radar screen of most lab administrators, executives, and pathologists,” he says.
Because of that, several sessions at this year’s Executive War College conference, now in its 29th year, will offer information designed to give attendees a better understanding of how to manage what’s coming for their labs and anatomic pathology practices.
“This regulatory trifecta consists of three elements,” adds Michel, who is also Editor-in-Chief of Dark Daily’s sister publication The Dark Report, a business intelligence service for senior level executives in the clinical laboratory and pathology industry, as well in companies that offer solutions to labs and pathology groups.
According to Michel, that trifecta includes the following:
Element 1
FDA’s Draft LDT Rule
FDA’s LDT rule is currently the headline story in the lab industry. Speaking about this development and two other FDA initiatives involving diagnostics at the upcoming Executive War College will be pathologist Tim Stenzel, MD, PhD, former director of the FDA’s Office of In Vitro Diagnostics. It’s expected that the final rule on LDTs could be published by the end of April.
Stenzel will also discuss harmonization of ISO 13485 Medical Devices and the FDA’s recent memo on reclassifying most high-risk in vitro diagnostics to moderate-risk to ease the regulatory burden on companies seeking agency review of their diagnostic assays.
Salerno will also cover the CDC’s efforts to foster closer connections with clinical labs and their local public health laboratories, as well as the expanding menu of services for labs that his department now offers.
Element 3
Private Payer Use of Z-Codes for Test Claims
On the third development—increased use by private payers of Z-Codes for genetic test claims—the speaker will be pathologist Gabriel Bien-Willner, MD, PhD. He is the Medical Director of the MolDX program at Palmetto GBA, a Medicare Administrative Contractor (MAC). It is the MolDX program that oversees the issuance of Z-Codes for molecular and diagnostic tests.
UnitedHealthcare (UHC) was first to issue such a Z-Code policy last year, although it has delayed implementation several times. Other major payers are watching to see if UHC succeeds with this requirement, Michel says.
Other Critical Topics to be Covered at EWC
In addition to these need-to-know regulatory topics, Michel says that this year’s Executive War College will present almost 100 sessions and include 148 speakers. Some of the other topics on the agenda in New Orleans include the following and more:
Standardizing automation, analyzers, and tests across 25 lab sites.
Effective ways to attract, hire, and retain top-performing pathologists.
Leveraging your lab’s managed care contracts to increase covered tests.
“Our agenda is filled with the topics that are critically important to senior managers when it comes to managing their labs and anatomic pathology practices,” Michel notes.
“Every laboratory in the United States should recognize these three powerful developments are all in play at the same time and each will have direct impact on the clinical and financial performance of our nation’s labs,” Michel says. “For that reason, every lab should have one or more of their leadership team present at this year’s Executive War College to understand the implications of these developments.”
Visit here to learn more about the 29th Executive War College conference taking place in New Orleans.
Following the loss of its histology accreditation, pressure on APS laboratory continues to mount
Government-run healthcare systems around the world often under-invest as demand grows and new healthcare technologies enter clinical practice. One such example is taking place in New Zealand, where public pathology and medical laboratory services are under extreme stress as physician test orders exceed the ability of the island nation’s clinical laboratories to keep up.
“The escalating pressure is complicating what was already a very difficult rescue job at one of the country’s busiest labs—Community Anatomic Pathology Services (APS),” RNZ reported. In 2023, APS lost its histology accreditation after it came to light that lab workers were not only exposed to toxic chemical levels at the facility, but that patients were waiting weeks for test results to return from the lab.
“The service is in crisis mode and, without urgent investment … there is a real risk that it will fail. The changes required are of such urgency that it is recommended that they be placed at the top of the agenda,” the report reads, RNZ reported.
“The size of New Zealand’s economy is restricting what our country spends on health. Health is already the second highest demand on the New Zealand tax dollar,” wrote Andrew Blair, CMInstD (above), then General Manager of Royston Hospital, Hastings, New Zealand, in an article he penned for Jpn Hosp, the journal of the Japan Hospital Association. “The tolerance of New Zealanders would be challenged if a government attempted to increase taxes further to meet the growing demands for expenditure on health, but at the same time the population’s expectations are increasing. This is the challenging situation we face today.” For New Zealand’s clinical laboratories, the demand for testing is increasing annually as the country’s population grows. (Photo copyright: Blair Consulting.)
Increased Demand on APS Leads to Problems
Established in 2015, APS tests thousands of anatomic and tissue samples yearly and is utilized by approximately a third of NZ’s population, according to RNZ.
The big story, however, is that from 2022 to 2023 utilization increased by a third. “The overall increasing demand is greater than the capacity of the service,” Te Whatu Ora (Health New Zealand), the country’s publicly-funded healthcare system, told RNZ.
As planned care increased, public hospitals started outsourcing operations to private surgical centers. A domino effect ensued when all of those samples then made their way to APS. There was an “increased volume of private surgery being carried out by 600 specialists in the region and 2,000 general practitioners, with up to 450 histology cases a day,” RNZ noted, adding, “The backlog has hit turnaround times for processing samples, which had been deteriorating.”
To make matters even more dire, working conditions at the country’s clinical labs is unfavorable and deteriorating, with short staffing, outdated workspaces and equipment, and exposure to dangerous chemicals.
“Conditions got so bad from 2019-2021 that workers were exposed to cancer-causing formaldehyde in cramped workspaces, and flammable chemicals were stored unsafely,” RNZ reported.
While pay increases and safety improvements have provided some relief, the memory of past incidences coupled with increasing delays continue to undermine confidence in New Zealand’s laboratory industry.
Patients Also at Risk Due to Long Delays in Test Results
“We recognize the concern and impact any delayed results can cause referrers and their patients,” Health New Zealand said in a statement, RNZ reported.
Nevertheless, a 2023 article in The Conversation noted that, “38,000 New Zealanders had been waiting longer than the four-month target for being seen by a specialist for an initial assessment.”
However, according to plastic surgeon and Melanoma Network of New Zealand (MelNet) Chair Gary Duncan, MBChB, FRACS, when patients return to their doctors for test results, those results often have not come back from the medical laboratory. Therefore, the physician cannot discuss any issues, which causes the patient to have to make another appointment or receive a melanoma diagnosis over the telephone, RNZ reported.
“Slow pathology services are unfair to patients. Such delays could result in the spreading of the melanoma to other parts of the body and require major surgery under anesthetic,” dermatologist Louise Reiche, MBChB, FRACS, told RNZ. “Not only will they suffer an extensive surgical procedure, but it could also shorten their life.”
Improvements at APS Underway
Changes are currently underway that may decrease the long delays in test results at New Zealand’s labs. “A business case was being done to set up an electronic ordering system to cut down on manual processing errors,” RNZ reported.
Additionally, “the situation is much improved due to dispersal of work around [the] city and country for now. The teamwork around the region has been a veritable lifesaver,” a source familiar with the work told RNZ.
Construction of a new lab for APS is also allegedly in the works. However, to date no announcement has been made, according to RNZ.
Time will tell if New Zealand’s government can repair its pathology system. News stories showcasing damage caused by lengthy delays in clinical laboratory test results—and the ensuing patient harm due to rationed care in general—continue to reveal the weakness in government-run healthcare systems.
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
