New ‘simple’ pricing scheme will provide transparency and value to all stakeholders, says company’s Chief Pharmacy Officer
Woonsocket, R.I.-based CVS Health (NYSE:CVS) is planning to scrap what it says is an old-school prescription reimbursement model and turn to a new way to price prescription medications at its 9,000 CVS pharmacies nationwide. Why is this relevant for clinical laboratory and pathology managers? It shows the disruption that is ongoing in healthcare.
Like clinical laboratories, retail pharmacies have significant reimbursement, competition, and labor challenges to address. But unique to retail pharmacies is the emergence of pharmacy benefit management (PBM) companies that work between health insurance plans and drug makers.
“National pharmacy chains found themselves disintermediated from providing prescriptions to patients by pharmacy benefit management (PBM) companies. By 2021, PBMs had captured $484 billion of the total prescription drug spending of $576.9 billion. That meant PBMs controlled 84% of the prescription drug market! That caused retail pharmacies to look for new sources of revenue,” noted Dark Daily’s sister publication The Dark Report.
This arrangement may be motivating retail pharmacy companies to seek ways to recover the volume lost to PBMs.
CVS’ new CostVantage model will work with a formula based on how much CVS paid for the drug, a set markup over those costs, and a fee for pharmacy services to fill the prescription, according to a news release. Some experts and publications have compared the change to the approach used by the Mark Cuban Cost Plus Drug Company.
CVS Health expects to start CostVantage in 2024 before introducing it to PBMs for commercial payers in 2025.
CVS is “committed to lowering drug pricing,” CVS Health Chief Executive Officer Karen Lynch (above), CVS Health’s President and Chief Executive Officer, told CNBC. “What this (the new model) does is it essentially aligns the economics of our pricing for drugs to what consumers will pay at the pharmacy counter,” she added. Clinical laboratory managers and pathologists should understand that this new pricing strategy may be an attempt by CVS to win back prescription business lost to pharmacy benefit management companies. (Photo copyright: Rick Burn/Wikipedia.)
CVS Aims for Value and Transparency
CVS Health’s leaders believe it is time for a change in how the company’s pharmacies are reimbursed by PBMs and other payers.
Generic drugs dispensed in CVS pharmacies reached 90%. “That limits the capacity or the amount of value remaining through the higher levels of generic dispensing,” he said.
Also branded drugs have risen in price about 40% since 2019, leading to “higher costs for patients, our customers’ plans, and PBM plan sponsors.”
“This model has reached an inflection point that is just ripe for change,” Shah said. “We’re changing this outdated reimbursement model that made sense for the last decade, but no longer works today or in the future. We’re introducing a new simple model that provides value for all stakeholders across the supply chain in a much more simple, transparent, and comprehensive way,” he continued.
Cost-Plus Plans versus Retail Drug Prices
Fierce Healthcare compared CVS CostVantage to the Mark Cuban Cost Plus Drug Company, which claims it offers prescription drugs at prices below traditional pharmacies and openly shares with customers the “15% markup over its cost, plus pharmacy fees.”
Some examples on the company’s website include: Abiraterone acetate (generic for Zytiga), a prostate cancer treatment. It is priced at $33.50, compared to $1,093 retail. Cost Plus Drug Company says its costs are:
Manufacturing: $24.60
15% markup: $3.90
Pharmacy labor fee: $5.00
Another drug offered is canagliflozin (generic for Invokana), a type 2 diabetes medication, which sells for $245.92, compared to $676.14 retail. Cost Plus Drug Company says its costs are:
Fein predicts there will be more cost-plus models by retail pharmacies. “Other large pharmacies will likely follow CVS with attempts to force payers and PBMs to accept some form of cost-plus reimbursement,” he wrote.
Fein noted pharmacies prefer cost-plus models for reasons including the “stripping away of complexity and hidden cross-subsidies. … For a pharmacy, the same PBM would pay the same price for the same prescription regardless of the PBM’s arrangement with different plan sponsors.”
Turbulent Retail Pharmacy Market
CVS has also been dealing with limited growth, pharmacist labor relations issues, and a decline in COVID-19 testing, Healthcare Dive reported.
Meanwhile, pharmacies have been closing store sites and affiliated physician practices. CVS announced plans to close 900 stores between 2022 and 2024, according to a news release.
Rite Aid Corporation, Philadelphia, announced last year that it had filed for bankruptcy and may eventually close 400 to 500 of its 2,100 stores.
Walgreens Boots Alliance, Deerfield, Ill., intends to close 150 US and 300 United Kingdom locations, according to its former Chief Financial Officer James Kehoe’s remarks in a third quarter 2023 earnings call transcribed by Motley Fool.
The turbulence in the retail pharmacy market is another sign of ongoing disruption in healthcare. Long-established sectors are experiencing market shifts that are eroding their access to patients and ability to generate adequate profits.
Understanding how pharmacies approach these issues may help medical laboratory and pathology managers develop strategies for adding value to their relationships with healthcare providers and insurance plans.
The Office of Management and Budget (OMB) concluded its review of the final rule on April 22. Former FDA commissioner Scott Gottlieb, MD, and other regulatory experts expect the White House to send the final rule to Congress as early as late April and no later than May 22.
On Tuesday morning, Lâle White, executive chair and CEO of San Diego’s XiFin, Inc., will present a keynote on new regulations and diagnostics players that are “poised to reshape lab testing.” Her presentation is followed by a general session on Clinical Laboratory Improvement Amendments (CLIA) regulations featuring Salerno Reynolds, PhD., acting director at the U.S. Centers for Disease Control and Prevention (CDC) Center for Laboratory Systems and Response.
Robert Michel, Editor-in-Chief of The Dark Report will wrap day one with a general session on the regulatory trifecta coming soon to all labs, from LDT to CLIA to private payers’ policies for genetic claims.
Innovation in the spotlight
“It’s a rich mix of expert speakers, lab leaders who are doing innovative things in their own organizations, along with the consultants and the lab vendors who are pushing the front edge of laboratory management, operations, and clinical service delivery,” says Michel, who each year creates the agenda for EWC.
Several sessions, master classes, and speakers will look to the future with discussions about how healthcare data drives innovations in diagnostics and patient care, digital pathology adoption around the world, and hot topics such as artificial intelligence (AI), big data and precision medicine.
Panels offer a variety of viewpoints
“One valuable benefit of participating at the Executive War College is the various panel discussions,” Michel says. “Each panel brings together national experts in a specific area of the laboratory profession. As an example, our lab legal panel this year brings together four prominent and experienced attorneys who share opinions, insights, and commentary about relevant issues in compliance, regulations, and contractual issues with health plans and others.”
This allows attendees to experience a breadth of opinions from multiple respected experts in this area, he adds.
For example, a digital pathology panel will bring together representatives from labs, service providers, and the consultants that are helping labs implement digital pathology. The session will be especially helpful to labs that are deciding when to acquire digital pathology tools and how to deploy them effectively to improve diagnostic accuracy, Michel says.
And a managed care panel will feature executives from some of the nation’s biggest health plans—the ones that sit on the other side of the table from labs—to provide insights and guidance on how labs can work more effectively with them.
Networking opportunities abound
The event is about much more than politics and policy, however. There’s also a distinct social aspect.
“Everyone is welcome, and everyone appreciates the camaraderie, so don’t be shy about going up and introducing yourself to someone. The quality of the crowd is top-notch, yet I’ve always experienced a willingness for those of us who have been to this rodeo to always be welcoming,” she notes.
Michel agrees. “One of the special benefits of participation at the EWC is the superb networking interactions and collaboration that takes place,” he says.
“From the first moments that attendees walk into our opening reception on Monday night until the close of the optional workshops on Thursday, one can see a rich exchange happening amongst circles of attendees. Introductions are being made. Connections are developing into business opportunities. The sum of an attendee’s experience at the Executive War College is to gain as much knowledge from the networking and collaboration as they do from the sessions.”
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 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
This is the first of a three-part series on revenue cycle management for molecular testing laboratories and pathology practices, produced in collaboration with XiFin, Inc.
Setting Your Organization Up for Success: Maximizing Revenue for Molecular Diagnostics and Pathology Testing Starts Well Before Billing
What progressive revenue cycle management technology reveals about revenue levers, test clearances, and strategic planning for molecular and pathology testing.
CFOs and other leaders of molecular testing laboratories and pathology groups need to raise their awareness of the most vulnerable aspects of revenue. To this end, this article outlines three specific areas of potential revenue cycle management (RCM) improvement so molecular diagnostic and pathology organizations can better identify and adapt to localized market dynamics and individual patient needs.
“Many people look at RCM as just billing or getting a clean billing process, but laboratory testing is getting more complex; consequently, reimbursement is getting more complicated, and continually changing payer policies are also making it more challenging for labs to keep up. It is important for business executives, revenue cycle leaders, and CFOs to look more broadly at the revenue cycle,” explained Clarisa Blattner, XiFin Senior Director of Revenue and Payor Optimization. XiFin recommends lab and pathology leaders consider revenue cycle within the broader context of the patient journey, which generally includes, among other things, three key revenue-impacting patient engagement stages.
The first of the three stages, patient access and financial clearance, begins when patient demographics and insurance information are captured. Following demographics and insurance details is a determination of benefits coverage and verification of eligibility. Financial information on any required copay and deductibles are determined, and pre-payment is collected. Finally, the patient receives a financial responsibility estimate for any out-of-pocket expenses.
In stage 2, clinical/medical clearance requires ordering physician engagement to address medical necessity questions and obtain supporting documentation. Clinical assessment and diagnostic testing are conducted. The encounter document is completed. Results are shared via secure, seamless, connected communication between the ordering physician’s office, the lab of the diagnostic provider, and the patient. Finally, the claim is submitted for reimbursement with all relevant supporting documentation.
The third stage is when payer management activities are essential to maximizing reimbursement by ensuring claim submissions include prior authorizations, clinical documentation, proprietary payer forms and comply with payer policies and requirements. Through this stage, patient engagement ensures all the correct data is in place, and insurance information or coverage hasn’t changed or is appropriately updated. Anticipating payer responses and subsequent actions is critical to collecting the full amount payers are responsible for to minimize patient financial impact. Once all payer activities are exhausted, the patient must be sent their statement for the remaining balance in their preferred communication method (paper, text, email, portal, etc.). Additionally, payment collection is accelerated when a diagnostic provider makes it easy and convenient to make payments, manage payment plans, and change payment methods.
These three stages in the patient journey encompass important revenue levers that cannot be overlooked. They are foundational to automating the financial performance engine needed for molecular diagnostics and pathology practices, Blattner continued. Whereas specialty diagnostics are rapidly coming to market and localized with varying reach, availability, and insurance coverage assurance, activating specific “clearance” functions or “engagement” opportunities within these levers will be key to smooth claims processing, timely filing, and optimizing all payment avenues.
Blattner stresses that when not built into automatic administrative functions, these three types of stages (i.e., patient access, physician engagement, and payer management) will slow or indefinitely stall payment for molecular diagnostics and pathology providers.
Market Expansion and Shift in at-Home Testing Stresses Traditional Administrative Approaches
Novel diagnostics are being introduced in record numbers as physicians and diagnostic business leaders seek to address and fulfill unmet diagnostic and medical needs to support better health outcomes. Along with these new medical breakthroughs comes the demand for traditional administrative approaches to reinvent themselves – including RCM. This major operational shift and frequent payer policy changes with advanced diagnostics have strained traditional administrative practices. According to Blattner, when executives realize that manual processes and inadequate electronic billing functions have reached a breaking point, specialized automation is the natural next step. The items corresponding to the highest value revenue cycle activities may sound surprising within the three revenue levers—patient access, medical clearance, and payer management.
Patient Access, Engagement, and Financial Clearance
“Making it easy for physicians to order molecular diagnostics and pathology tests is so important for success in today’s market,” Blattner continued. Ordering physicians and lab teams must have accurate and timely information regarding a patient’s ‘financial clearance’ (the likelihood a test will be covered, what the patient is likely to be charged out-of-pocket, and whether prior authorization is required). Patient portals and multi-channel communications are important parts of effective RCM functionality that facilitate patient access and financial clearance.
“It used to be that a patient went to the lab, and a phlebotomist saw the patient, but now more tests involve specimen collection at home. A kit is distributed at the physician’s office or ordered online and shipped to the patient,” Blattner said. “There is more follow-through needed to make sure not only did the test get done, but did it get returned, because while there are upfront costs to serve the patient, the lab doesn’t get paid until the test is completed, returned, processed and the diagnosis is determined for the claim to be processed. That is an evolution as these tests leave the laboratory or the business and enter the home environment.”
Patient access and engagement tools provide various benefits, including offering a cost-effective alternative to traditional customer service calls and supporting patients’ communication preferences. Effective physician access and engagement programs and technology help diagnostic providers offer self-service tools that enable patients to securely log in, anytime, to:
View statements
Make credit card payments
Set up payment plans (using lab-specified rules and parameters)
Establish paperless billing
View patient responsibility estimates
View test results
Another critical aspect of patient financial clearance for diagnostic testing is the ability to provide patients with an accurate estimation of their out-of-pocket costs associated with a test. Practical patient communication tools enable ordering physicians’ staff members to assist patients in preparing for out-of-pocket expenses, which increases test completion rates and has been proven to reduce write-offs.
To accurately assess a patient’s financial responsibility, the estimation tool must consider relevant provider and plan specific pricing and test or procedure information, as well as provide access to real-time eligibility data. A proper estimation of a patient’s out-of-pocket expenses is also predicated on receiving complete and accurate information from the payer. Examining payer behavior can uncover responses that create inaccurate patient responsibility estimates.
Physician engagement programs help diagnostic providers integrate communication and data exchange more deeply with ordering physicians and complete clinical clearance. Clinical clearance involves things like medical necessity, familial history, and social determinants of health. Robust RCM also requires diagnostic providers, laboratories, and pathology practices to be able to seamlessly communicate with patients to ensure that samples, devices, or readings are collected and returned to the diagnostic provider so that services/tests can be completed.
Effective physician engagement and clinical clearance increase ordering volume, maximize clean claims and automate denials and appeals management. Physician engagement technology, including electronic communication tools such as portals, helps physicians and their teams streamline the online correction of missing information and errors. This improves satisfaction, expedites reimbursement, and provides cost savings. With effective physician engagement programs and technology tools, physicians and their staff can more effectively:
Perform order entry
Access clinical decision support
Examine statements at the line-item level
View test information and pricing
Correct billing errors upfront to expedite reimbursement
Provide patients with an estimate of their out-of-pocket cost
Payer Management
Molecular diagnostic and genetic tests are famously complex and present many unique operational and financial challenges for laboratories. Payer policies and behavior are constantly changing, and labs (and their billing partners) must stay abreast of changes to avoid lengthy delays that denials and subsequent appeals can cause. Intelligent automation of prior authorizations, insurance discovery, and benefits determination are especially important for these tests.
Unfortunately, it is common for diagnostic providers to only learn about a change in reimbursement after the month-end close. These changes manifest in billing as:
New denials
Changes in denial rate
Changes in reimbursement rate
Change in time to payment
Failure to quickly recognize and adapt workflows to payer reimbursement changes can result in costly appeals and write-offs. XiFin recommends that providers adopt a proactive strategy to identify changes in reimbursement earlier. It is essential to understand the impacts and risks of price discrepancies and changes in pricing to patients. Staying abreast of policy changes for Medicare and commercial payers enables molecular diagnostic laboratories and pathology groups to proactively employ front-end billing system edits to avoid denials.
Keys to Success
For molecular diagnostic providers and pathology groups to maximize reimbursement, CFOs, and revenue cycle leaders must take a broader view of RCM. The RCM process starts well before billing and runs parallel to the patient journey in many respects. This means that effective RCM technology and tools also stretch beyond the billing system to incorporate seamless communication between systems and parties throughout the patient journey.
Adaptive RCM approaches require automation, intelligence, and real-time communication for the three key revenue-impacting stages discussed in this article: patient access, medical clearance, and payer management. This involves seamless integration with various tools that enable insurance discovery, patent demographic and eligibility verifications, patient financial responsibility estimation, and reporting and analytics that allow early identification of and response to changes in payer behavior.
Molecular diagnostic labs and pathology practices must have tools and technology to align with payers on evidence requirements, including clinical utility evidence, current billing policies, and preferred coding approaches. They must have seamless connectivity to ordering physicians to order tests and ensure the completeness of medical necessity and medical record documentation.
Finally, XiFin recommends that diagnostic organizations use analytics to enable early insight into changes in payer behavior, address root causes, and be able to adjust to changes in ordering patterns and client data quality. Be sure to consider an RCM platform that has embedded artificial intelligence (AI) to drive efficient automation of workflow adaptation to payer changes and future-proof your RCM investment.
Financial executives seeking to maximize market access and capitalize on growth opportunities in key markets will want to explore how successfully their administrative teams are navigating the unique revenue cycle landscape specific to molecular testing and pathology.
Part 2 of this three-part series is coming soon. Watch for updates here at DarkDaily.
As doctors become more familiar with using biomarkers to monitor Crohn’s disease, clinical laboratories may play a greater role in that process
New evidence-based guidelines from the American Gastroenterological Association (AGA) that call for using specific biomarkers to help manage Crohn’s disease (CD) may decrease the number of invasive procedures patients must undergo and increase the role clinical laboratories play in monitoring the disease.
The new AGA guidelines “recommend using the C-reactive protein (CRP) biomarker in blood and the fecal calprotectin (FCP) biomarker in stool to measure inflammation levels and assess whether Crohn’s disease is in remission or active,” Medical News Today reported.
Crohn’s disease is a chronic inflammatory bowel disease (IBD) that causes inflammation in the digestive tract, primarily in the small and large intestine. The cause of the disease is unknown, but genetics may play a role.
Typically, CD patients must undergo repeated colonoscopies to monitor the disease’s progression or remission. This has long been standard practice. Now, however, “AGA recommends the use of biomarkers in addition to colonoscopy and imaging studies,” according to an AGA news release. This hints at a greater role for clinical laboratories in helping physicians manage patients with Crohn’s Disease.
“Patients’ symptoms do not always match endoscopic findings, so biomarkers are a useful tool to understand and monitor the status of inflammation and guide decision making in patients with Crohn’s disease,” said gastroenterologist Siddharth Singh, MD, Assistant Professor of Medicine at UC San Diego Health and a co-author of the new AGA guidelines.
The AGA’s new guidelines demonstrate how medical science is generating new insights about how multiple biomarkers can be associated for diagnosis/management of a disease in ways that change the standard of care, particularly if it can reduce invasive procedures for the patient by the use of less invasive methods (such as a venous blood draw instead of a colonoscopy).
“Based on this guideline, biomarkers are no longer considered experimental and should be an integral part of inflammatory bowel disease care,” Ashwin Ananthakrishnan MD (above), a gastroenterologist at Massachusetts General Hospital and co-author of the guidelines, told Medical News Today. Under the new AGA guidelines, clinical laboratories will play a greater role in helping patients monitor their disease. (Photo copyright: Massachusetts General Hospital.)
Patient’s Needs Determine Biomarker vs Endoscopy Monitoring
AGA’s new guidelines could give patients a more comfortable, cost-effective, and possibly more efficient treatment plan to manage their Crohn’s disease. That’s even true if a patient’s Crohn’s disease is in remission.
With these new guidelines, Crohn’s disease patients in remission would only need their biomarkers to be checked every six to 12 months. Patients with active symptoms would need their biomarkers checked roughly every two to four months.
Biomarker testing can be seen as a useful addition to Crohn’s disease care rather than a full replacement of other forms of care. For example, the new AGA guidelines do not fully omit imaging studies and colonoscopies from treatment. Rather, they are recommended in treatment plans based on the patient’s needs.
In their Gastroenterology paper, the AGA authors wrote, “A biomarker-based monitoring strategy involves routine assessment of symptoms and noninvasive biomarkers of inflammation in patients with CD in symptomatic remission to inform ongoing management. In this situation, normalization of biomarkers is an adequate treatment target—asymptomatic patients with normal biomarkers would continue current management without endoscopy, whereas those with elevated biomarkers would undergo endoscopy.”
Fecal Matter Biomarkers
In speaking with Medical News Today on the benefits of using fecal biomarkers to assess a patient’s disease maintenance, gastroenterologist Jesse Stondell, MD, an Associate Clinical Professor at UC Davis Health, said, “If we start a patient on therapy, they’re not responding appropriately, they’re still having a lot of symptoms, we can check that fecal calprotectin test and get a very quick sense of if things are working or not.
“If the calprotectin is normal, it could be reassuring that there may be other reasons for their symptoms, and that the medicine’s working. But if they have symptoms, and a calprotectin is elevated, that’s a signal that we have to worry the medicine is not working. And that we need to change therapy in that patient,” he added.
“This is a win for Crohn’s disease patients,” Ashwin Ananthakrishnan, MD, a gastroenterologist at Massachusetts General Hospital and co-author of the AGA’s new guidelines, told Medical News Today. “Biomarkers are usually easier to obtain, less invasive, more cost-effective than frequent colonoscopies, and can be assessed more frequently for tighter disease control and better long-term outcomes in Crohn’s disease.”
Clinical laboratories should expect these guidelines to increase demand for the processing of blood or fecal matter biomarker testing. As Crohn’s disease monitoring becomes more dependent on biomarker testing, clinical labs will play a critical role in that process.
