News, Analysis, Trends, Management Innovations for
Clinical Laboratories and Pathology Groups

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News, Analysis, Trends, Management Innovations for
Clinical Laboratories and Pathology Groups

Hosted by Robert Michel
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A Dark Daily Extra!

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

— Leslie Williams

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A Dark Daily Extra! Overcoming the Common Challenges Facing Molecular Diagnostics Labs to Maximize Revenue

This is the second of a three-part series on revenue cycle management for molecular testing laboratories and pathology practices, produced in collaboration with XiFin, Inc.

Second of a 3-part series, this article will detail what molecular diagnostics and pathology groups need to understand about coding, billing, and denial management to maximize revenue and cash flow successfully.

In the first article, we discussed how molecular diagnostics and pathology groups can enhance the patient experience, physician engagement, and payer relations. Now, we will detail how denial management can successfully maximize revenue and cash flow. As we discussed in the last article, revenue cycle management (RCM) is much more than billing.

Today’s rapidly changing environment of directives and expectations from payers, patients, and health systems require deeper understanding, great agility, and strategy in every aspect of business. Creating opportunities to provide better service, adopt state-of-the-art technologies, and build robust processes and partnerships can make or break the long-term success of a laboratory or pathology practice.

Technical assessments are often required to establish clinical validity and utility to achieve payer coverage for novel genetic tests. Achieving payer coverage requires a deep understanding of how-to code tests compliantly and to facilitate reimbursement.

“We recommend that molecular diagnostics laboratories consult with coding experts to fully understand the coding requirements for each genetic test,” says Clarisa Blattner, XiFin Senior Director, Revenue and Payor Optimization.  “Ensuring reimbursement requires knowing payer policies and to track denial trends by payer over time to identify changes.”

Blattner noted that payer policies and behavior are constantly changing. Labs, and their billing partners must stay abreast of changes to avoid lengthy delays that denials and subsequent appeals can cause. Understanding the documentation that is required with claims is invaluable. Knowing these requirements up front and submitting complete claims with all required medical records and documentation of medical necessity goes a long way toward facilitating reimbursement.

Payers are adopting increasingly rigid policies that are often inconsistent with others. Reimbursements continue to be cut while quality reporting requirements rise.

Diagnostics laboratories that conduct genetic testing must also overcome four common challenges:

  1. Achieving and expanding payer coverage with coverage determination that defines reasonable and medically necessary services and tests.
  2. Knowing how to code the tests correctly with medical nomenclature to report services and/or tests to a payer.
  3. Ensuring payment/reimbursement for services/tests based on services/tests rendered and coverage determination.
  4. Maintaining compliance and keeping abreast of billing compliance and having a voice in reform

“We also recommend that laboratories conduct internal audits that reconcile laboratory information system (LIS) data with RCM system data,” Blattner continued. “Labs with a robust business intelligence (BI) solution can proactively identify outliers, such as accessions that exist in one system but not the other.”

Maintain Your Billing System and Maximize Clean Claim Submissions

Laboratories should be sure that these four payer services are being handled appropriately, whether it is by the lab or an RCM partner:

1.         Payer relations: An effective payer relations team monitors denials and coordinates with payers. This team reviews front-end payer rejections, coordinates with clients (i.e., ordering physicians), and identifies and updates edits based on payer policies and behavior changes.

2.         Electronic data interchange (EDI) enrollment: This team handles monitoring and proactive enrollment for electronic submissions and helps ensure bidirectional transaction automation.

3.         EDI analysts: Experts in healthcare EDI who investigate errors, participate in standards development and testing, as well as payer education and coordination.

4.         EDI operations: These specialized technicians configure files and ensure the reconciliation of claim-level submissions.

Efficiently Upload and Store Medical Records and Documentation

Although laboratories do not directly control patient medical records, it is essential to understand that diagnosis codes alone are generally insufficient.

Laboratory sales representatives must work with clients and ordering physicians to ensure medical records have all the information required for payment. Ensuring that the payers expedite payment requires efficient uploading and storing of medical records and documentation:

  • Align with payers on clinical utility evidence requirements, current billing policies, and preferred coding approach.
  • Leverage the support and advocacy of key opinion leaders (KOLs).
  • Collaborate with clinicians on the prior authorization process.
  • Select an RCM partner that helps you maximize process automation and front-end edits.
  • Leverage a business intelligence (BI) system that simplifies the tracking of key performance indicators (KPIs), helps identify payer policy and behavior changes early, and highlights changes in key business trends.

The RCM system must be able to upload and store medical records and documentation. The required medical information typically includes the following:

Who? Ordering/referring provider.

What? What service(s)/test(s) is/are being ordered?

Where? Where is the specimen being sent?

When? What is the date of service (DOS)?

Why? What are the patient’s signs/symptoms, or what prompted the test to be ordered?

How? How are the test results used to manage the patient’s medical condition?

But even after including all of the correct medical information, denials are inevitable. There are important steps labs can take to streamline denial management.

The Importance of Patient Engagement in Maximizing Reimbursement

Patient engagement plays an essential role in facilitating reimbursement and maximizing cash collection. Patients expect transparency and ease of information access from their healthcare encounters, just as they experience in all other areas of their lives. Because most laboratory, pathology, and molecular encounters are not directly patient-facing, proven payment accelerating engagement tools are essential. Dynamic portals, electronic statements, and text messages are essential, especially when it comes to communication regarding errors and patient financial responsibility.

XiFin customer data show a substantive increase in patient payments received in the first 30 days of the dunning cycle after integrating texting and automated calls into the traditional process. For example, a XiFin customer collected 26.6% more of the revenue in the first 30 days after implementing a text reminder between the first and second paper statements. Prior to implementation, the customer followed a traditional three-statement dunning cycle:

  • 42.6% of total payments received occurred after the first statement (within the first 29 days of the dunning cycle).
  • 34.8% occurred after sending the second statement (between days 30-59 of the dunning cycle).
  • 22.6% were received after sending the third and final statement (during days 60-90 of thedunning cycle).
Dunning Cycle PeriodBeforeAfterIncrease/ (Decrease)
Days 1-2942.6%69.2%26.6%
Days 30-5934.8%27.8%-7.0%
Days 60-9022.6%3.0%-19.6%

The convenience of text messaging allows patients to connect to the call center or to the patient portal, where a payment can be made immediately. XiFin customers can customize their dunning cycle, depending on how their specific patient population responds to texts, paper statements, and the timing between billing cycles. Studying the behaviors of patient interactions at the client level, rather than only referencing the status quo of macro-level trending, empowers a more strategic approach to engagement and improving overall patient satisfaction.

Denial Trends Driving Reduced Revenue and Higher Costs

Denials extend time in accounts receivable, contributing to bad debt on services already rendered and laboratory expenses absorbed. Denials also often require the most attention from staff – increasing the cost of billing. Hard denials, such as Medical Necessity, make up the most challenging revenue to collect, comprising about 5-10% of total denials received. In addition to creating delays and revenue loss, denials illustrate how payers administer their policies, even when those policies are unpublished.

Fundamentally, an effective RCM process is rooted in the ability to file clean claims to the degree that is possible. Improving those outcomes requires focus on the exceptions – the dirty claims – the denials.

“At XiFin, we invest in front-end configurations and workflows to catch denials prior to submitting the claim to the payer,” continued Blattner.  “As we monitor denial trends, we build more robust front-end workflows and add automation (such as integrating with insurance discovery and prior authorization vendors) to reduce the associated burden on billing teams.”

In addition, molecular testing coverage continues to expand, reducing non-covered denials. The stabilization of these medical policy-related denials is positive. The jump in demographic denials, however, requires additional consideration.

Paid vs. Denied by Payer Group

Denial patterns vary among payers. The percentage of claims denied also differs by segment, largely due to the type of testing performed.

Of the claims XiFin processes annually (approximately $50 billion in charges), 22.5% are denied. The graphs below demonstrate molecular testing’s higher propensity for denial (27.5% of claims billed), driven by non-covered, medical necessity, and prior authorization requirement challenges.

Routine pathology has closer to a 20% denial rate overall. The average percentage of billed claims that are denied by segment are:

■ Clinical: 13.62%

■ Molecular: 27.19%

■ Pathology: 19.82%

Molecular testing has a higher propensity for denial (27.5% of claims billed), driven by non-covered, medical necessity, and prior authorization requirement challenges. Routine pathology has closer to a 20% denial rate overall.

Clinical laboratory denial rates averaged 13.62% in 2021. As seen in the table below, clinical laboratories saw a significant decline in experimental/investigational denials between 2018 and 2021.

Denial TypeMolecular % of Total Denied 2018Clinical % of  Total Denied 2021Variance (% change 2021 vs. 2018)
Benefit Maximum Reached39.3%29.7%-24.4%
Claim Specific Negotiated Discount17.6%18.1%2.8%
Coordination of Benefits4.1%16.3%298%
Coverage Terminated6.6%13.4%103%
Diagnosis Not Covered11.3%6.4%-43.4%
Duplicate Denial8.3%3.4%-57.8%
Experimental Investigational0.1%2.7%2600%
HSA2.1%2.4%14.3%
Incorrect Payer0.9%1.6%77.8%
Non-Covered2.2%1.1%-50.0%
Patient Cannot be Identified0.7%0.8%14.3%
Patient Enrolled in Hospice0.5%0.5%0.0%
Prior Authorization0.2%0.2%0.0%
Procedure Code Inconsistent with the Modifier Used  or a Required Modifier is Missing1.6%0.1%-87.5%
Procedure Not Paid Separately0.5%0.1%-60.0%
Service Not Payable per Managed Care Contract0.1%0.0%-100%

Molecular claims continue to experience the highest denial rates of any laboratory segment. With an average denial rate of 27%, molecular continues to be a revenue recovery workflow heavy on the back-end. As a percentage of the total denial population, between 2018 and 2021, XiFin experienced increases in patient-coverage denials, such as coordination of benefits (298%), coverage terminated (103%), and experimental/investigational (2600%). Decreases in diagnosis not covered denials (-43.4%) and duplicate denials (-57.8%) are also recognized.

Exome/Genome Testing must be administered by specialized technicians with specific credentials, creating potential backlogs. They can take 8, 12, or even 16 weeks to complete, depending on testing methodologies. This presents a high risk of timely filing denials for the many payers that have adopted 90-day timely filing limits. XiFin recommended practice: Explore amending your payer contracts to extend timely filing limits on these tests.

Denial TypePathology % of Total Denied 2018Pathology % of  Total Denied 2021Variance (% change 2021 vs. 2018)
Prior Authorization28.9%36.1%24.6%
Duplicate Denial21.5%21.2%-1.9%
Non-Covered14.1%10.1%-27.7%
Services Not Prov. By Network/Primary Care Provider8.8%8.5%-3.4%
Procedure Not Paid Separately4.4%5.1%15.9%
Services Not Authorized by Network/Primary Care Provider3.6%3.8%5.6%
Procedure Code Inconsistent with the Modifier Used  or a Required Modifier is Missing1.5%3.3%120%
Coverage Terminated2.2%2.6%18.2%
Coordination of Benefits3.8%2.4%-34.2%
Patient Cannot Be Identified3.1%2.3%-25.8%
Remark Code5.9%2.1%-64.4%
Experimental Investigational1.0%1.2%20.0%
Benefit Maximum Reached0.4%1.0%175%
Patient Enrolled in Hospice0.4%0.1%-75.0%
Incorrect Payer0.0%0.1%100%
Service Not Payable per Managed Care Contract0.2%0.0%-100%

Anatomic pathology denials have increased by approximately 5% from 2018 to 2021. As a percentage of the total denial population, the lack of prior authorization is the highest contributor to this increase, having grown 24.6%. There was an increase in procedure code inconsistent with modifier denials (120% increase) and a decrease in non-covered denials (-27.7%).

Importance of an Efficient and Effective Appeals Process

Front-end edits and configurations help mitigate backend denials. Capturing potential denial-related issues proactively are the most effective way to maintain a manageable AR and improve the propensity to pay. For example, payers that observe National Correct Coding Initiative (NCCI) and Medically Unlikely Edits (MUEs) will consider all Current Procedural Terminology (CPT) codes billed for that patient for the same Date of Service (DOS), even when not billed on the same claim form.

Denials are inevitable if your current billing process does not have edits in place to perform a historical review of charges for the same patient on the same DOS.

Denials are unavoidable, and not all known issues can be addressed on the front end of the process. An example of this is denial code CO252, which is an additional information denial. It indicates the payer is requesting additional documentation (i.e., clinical information, medical records, and test results) before issuing payment – essentially performing an audit to ensure the services billed are reasonable and necessary and medical necessity is justified and documented.

“These are not always complex molecular tests; they can be routine pathology claims,” said Blattner “Each time we receive a CO252 denial it has to be appealed with additional documentation found in the patient’s medical records. Though it is inevitable, we must wait on the denial before we can take action.”

SegmentAppeal-Payments as  % of Total Insurance Payments ReceivedAverage Payment  Amount per Appeal
Clinical0.11%$121
Molecular6.56%$1,420
Pathology1.12%$327
Industry Average3.39% $623

Payment collection per appeal continues to be stable in the pathology (averaging 1-2%) and clinical segments, where appeals are less prolific. Revenue recovered by corrected claims is excluded since these claims follow a separate process and impact denial codes such as CO97 (Procedure or service isn’t paid for separately), CO18 (Duplicate), and CO234 (Procedure not paid separately). Further, a single appeal process is not sufficient. A robust appeals process here becomes critical. Specifically in molecular testing, appeals carry a heightening impact on revenue collection. In 2020, appeals accounted for 5% of the total revenue generated by XiFin customers. In 2021, that increased to 6.5%.

Appeal Success Rates by Payer Group by Segment

The next four charts show appeal success rates by payer group for 2021, overall and by market segment for clinical, molecular, and pathology. The fifth chart illustrates the incremental impact of multiple appeal attempts by market segment.

This assessment only includes activity related to revenue recovery through an appeals process. Some denials can be addressed by filing of a corrected claim and can be a much more efficient process. Although ideal, corrected claims are not always possible, depending on denial type and individual payer preferences.

 % of Total  Appeals Filed% of Appeals Paid after 1st Attempt% of Appeals Paid after 2nd Attempt% of Appeals Paid after 3rd AttemptAvg Payment per Appeal
Clinical 17.4%17.8%9.9% $ 276
Additional Information70.1%20.9%20.3%10.0% $ 258
COVID Medical Necessity8.9%3.9%50.0%  $ 78
Medical Necessity4.8%30.4%18.4%  $ 553
Out of Network6.9%4.4%2.4%  $ 594
Prior Authorization0.0%14.3%0.0%  $ 421
Underpayment9.3%6.9%6.3%  $ 10

The clinical laboratory segment maintains the lowest volume of denials. But this does not negate the need for robust editing processes. Implementing robust front-end logic and leveraging intelligent automation to correct potential issues dramatically streamlines the process from submission to payment, especially in the high-volume clinical laboratory segment.

 % of Total  Appeals Filed% of Appeals Paid after 1st Attempt% of Appeals Paid after 2nd Attempt% of Appeals Paid after 3rd AttemptAvg Payment per Appeal
Molecular 21.4%17.2%19.4% $1,420
Additional Information47.7%23.9%20.7%23.3% $1,285
Medical Necessity23.0%17.6%14.0%12.8% $1,518
Prior Authorization11.4%18.9%11.7%13.1% $1,944
Experimental and Investigational / Non-Covered5.6%13.2%9.0%9.0%$4,234
COVID Underpayment3.8%44.7%24.6%10.7% $52
Timely Filing3.5%10.1%8.3%18.9% $551
Out of Network3.5%14.0%10.8%8.4% $2,513
Underpayment1.1%31.2%17.8%15.3% $2,154
COVID Medical Necessity0.4%46.4%27.0%0.0% $124

Appeal Trends: Molecular and Genomic Testing   At $1,420, the average payment per appeal for molecular testing is more significant due to the high-dollar value of the testing. Additional information appeals account for 47% of the total appeals filed in 2021 in the molecular segment and have an average success rate of 23%. Another 23% of appeals are for claims denied for medical necessity, followed by prior authorizations at 11.4% of total appeals filed. Prior authorization appeal volumes have remained consistent year-over-year in this segment, averaging 10% in 2020, despite a higher volume of prior authorization requirements than pathology or clinical laboratory.

XiFin’s RCM platform has integrated automation with prior authorization partners, allowing claims meeting prior authorization criteria to be submitted to a prior authorization solution automatically.  Utilizing “real-time data exchange” via application programming interfaces (API) without partners, XiFin can more quickly acquire the necessary prior authorization number and update the patient’s information in XiFin RPM upon those values being returned.

 % of Total  Appeals Filed% of Appeals Paid after 1st Attempt% of Appeals Paid after 2nd Attempt% of Appeals Paid after 3rd AttemptAvg Payment per Appeal
Pathology 22.6%20.6%21.8% $327
Additional Information33.4%28.8%23.4%27.9% $337
Medical Necessity19.0%23.5%23.4%27.6% $398
Out of Network17.9%17.6%12.4%17.7% $318
Prior Authorization12.2%21.5%32.9%36.5% $350
Experimental and Investigational / Non-Covered9.2%17.8%8.9%3.1% $195
COVID Underpayment5.8%9.0%3.4%16.7% $31
Timely Filing2.5%20.5%15.6%13.3% $191
Underpayment0.1%52.2%0.0%  $177

Appeal Trends: Pathology

Approximately 2% of the pathology accessions received into XiFin RPM require an appeal. Those appeals will be responsible for approximately 1-2% of the pathology practice’s revenue. As noted above, the revenue reclaimed is largely attributed to the first attempted appeal. A robust process that includes multiple attempts is critical in revenue recovery in the event the first appeal is not overturned.

If Not Documented, It Did Not Happen

Payer edits and guidelines can be difficult to follow, particularly if physicians, coders, or billing staff are expected to memorize those requirements.

Making the situation even more challenging is the fact that edits vary widely among payers and are constantly changing. RCM platforms should be updated routinely (XiFin RPM is updated monthly) with payer edit updates, while remaining configurable so that custom edits can be easily built to accommodate specific payer requirements.

Whether it is a payer audit or packaging an appeal, documentation in the pathology report and/or clinical notes should clearly outline the services provided and the medical necessity of those services. If it is not documented, it did not happen. Further, understand the various programs that drive payer edits and guidelines. These edits drive an increased need for discipline and documentation. Be conscious of payer-specific requirements. Cigna, Aetna, and UHC require proprietary forms to be completed when appealing claims.

Benchmarking Productivity

Proactively preventing a denial and avoiding the need to submit a corrected claim or file an appeal reduces the time to reimbursement by four to eight weeks, depending on the payer and type of denial. If denials are not addressed properly and manual workflows persist, diagnostic labs will continue to experience a loss of revenue, and staffing will be insufficient to keep up.

Productivity rates for anatomic and molecular billing teams historically average between 12,000-15,000 accessions per person per full-time equivalent (FTE) per year (clinical laboratory is often much higher). However, with the increases in denials, the resulting demands on back-end teams have increased substantially and impacted productivity rates. This holds particularly true for particularly non-covered, medical necessity, and prior authorization denials.

Further, speed to payment is also improved. By automating appeals, the turn-around-time on submitting back to the payer is reduced, on average, from 45 days to 1-3 days, as seen in the blue bar in the chart above.

By installing front-end edits to help maximize clean claims, up to an additional 54 days can be saved, moving from 135 days to just 30 days for full adjudication.

Automating Workflows with AI

Opportunities to automate the process will reduce time and labor and make decisions more consistent. Once there is a deep understanding of coding, billing, denial management, and strategic appeals, there is the ability to automate the important processes across the RCM process. Automation and AI-powered workflows pave the way for consistent, optimized molecular diagnostics and pathology RCM.

Part 3 will demonstrate how AI can be used in RCM to inform, accelerate, automate, validate, and generate. Watch for updates here at DarkDaily.

— Leslie Williams

­A Dark Daily Extra!

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.

Price and Volume Modeling

Physician Engagement Programs Facilitate Clinical Clearance

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.

Revenue Cycle Management Process

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.

— Leslie Williams

New American Gastroenterological Association Guidelines for Managing Crohn’s Disease Suggest More Clinical Laboratory Tests and Fewer Colonoscopies

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).

The AGA published its new guidelines in the journal Gastroenterology titled, “AGA Clinical Practice Guideline on the Role of Biomarkers for the Management of Crohn’s Disease.”

Ashwin Ananthakrishnan MD

“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.

—Ashley Croce

Related Information:

Fewer Colonoscopies? New Crohn’s Guidelines Emphasize Blood, Stool Tests as Management Tool

AGA Clinical Practice Guideline on the Role of Biomarkers for the Management of Crohn’s Disease

Biomarker- vs Endoscopy-Based Monitoring Strategy in Crohn’s Disease

First Comprehensive Guideline on Using Biomarkers for Monitoring Crohn’s Disease

National Library of Medicine: Crohn’s Disease

Crohn’s Disease Is on the Rise

Former Theranos CEO Elizabeth Holmes Fights Prison Sentence While Claiming She Was ‘Not Being Authentic’ with Public Image

Founder of now defunct clinical laboratory testing company was supposed to report to prison April 27, but a last-minute legal challenge has delayed that judge’s order

Anatomic pathologists and clinical laboratory leaders who are following the continuing saga of Theranos and Elizabeth Holmes may be interested to learn that the former CEO’s attorneys are making last-minute legal moves to delay her prison sentence while she appeals her guilty verdict. At the same time, Holmes appears to be on a mission to revamp her public image.

Apparently, the twists and turns in Holmes’ never-ending story are not yet over when it comes to Theranos, its maligned clinical laboratory technology, and the company’s convicted founder.

On May 7, The New York Times (NYT) profiled Holmes in a massive, 5,000-word story that attempted to portray her as a flawed businessperson who now prefers a simpler life with her partner and two young children.

Elizabeth Holmes

“I made so many mistakes and there was so much I didn’t know and understand, and I feel like when you do it wrong, it’s like you really internalize it in a deep way,” disgraced Theranos founder Elizabeth Holmes recently told The New York Times. Anatomic pathologists and clinical laboratory directors impacted by the revelation that Theranos hide the fact that its blood testing technology was faulty may not sympathize with Holmes’ position. (Photo copyright: Stuart Isett/Fortune Global Forum.)

Legal Team Secures Last-Minute Delay in Holmes’ Surrender

Holmes admitted to the news outlet that the deep voice she used in public, along with her black turtleneck sweaters, were part of a character she created.

“I believed it would be how I would be good at business and taken seriously and not taken as a little girl or a girl who didn’t have good technical ideas,” Holmes told the NYT. “Maybe people picked up on that not being authentic, since it wasn’t.”

Holmes was scheduled to report to a federal prison in Texas on April 27 after several unsuccessful motions were filed to delay the start of her sentence for the fraud convictions. Dark Daily covered Holmes’ conviction in “Disgraced Theranos Founder Elizabeth Holmes to Serve 11 Years, Three Months in Prison, Ending the Latest Chapter in the Story of the Failed Clinical Laboratory Company.”

However, on April 26, the 9th Circuit Court of Appeals stayed her surrender date until that court rules on Holmes’ latest bid to stay free while she appeals her conviction, The Washington Post reported.

Just days earlier on April 10, a district court judge ruled that Holmes would not stay free while her appeal progresses. The 9th Circuit announcement curtailed the district court ruling. It is not known when the 9th Circuit will issue a decision in the matter.

In “Theranos Ex-CEO Elizabeth Holmes Convicted on Three Counts of Wire Fraud and One Count of Conspiracy to Commit Fraud after Seven Days of Jury Deliberations,” Dark Daily reported that Holmes was convicted in January 2022 of defrauding Theranos investors out of $121 million. Theranos marketed a blood-testing machine called Edison, although it was later uncovered that results attributable to the technology were actually produced on traditional clinical laboratory analyzers.

New York Times Reports on Holmes’ Change in Personality

The somewhat odd New York Times profile of Holmes varied between reflections on her past crimes and on her current personal life, where she is known as “Liz.”

“In case you’re wondering, Holmes speaks in a soft, slightly low, but totally unremarkable voice—no hint of the throaty contralto she used while running her blood-testing startup Theranos, now defunct,” the NYT reported.

Holmes still lives in California with her partner, Billy Evans (whose parents own a luxury hotel chain), and their two children: a son who is almost two years old and a daughter born in February. She works at home for a rape-crisis hotline.

Balwani’s Role in Theranos Again Publicly Debated

In the NYT interview, Holmes talked about being raped while a student at Stanford University and about alleged abuse from her Theranos business partner and former lover, Ramesh “Sunny” Balwani.

Balwani, Theranos’ former President and Chief Operating Officer, began his 12-year, 11-month prison sentence on April 20 in a Southern California facility for his role in defrauding Theranos investors, KTVU TV reported. Balwani has also appealed his conviction on the 12 fraud charges.

Holmes reiterated to the NYT past statements she made in court that Balwani allegedly exerted social and sexual control over her when they both worked at Theranos and were in a romantic relationship.

“She lived by entrepreneurial tenets that she said Balwani told her she needed to follow in order to succeed,” the NYT reported. “These included not sleeping for more than five hours, going vegan, getting to the office daily by 5 a.m., no alcohol.”

“[I] deferred to [Balwani] in the areas he oversaw because I believed he knew better than I did,” including on clinical lab activities at Theranos, Holmes said.

Balwani’s attorneys dismissed Holmes’ allegations, as they have in the past.

Clinical laboratory professionals can reasonably make two broad observations from the continuing saga of Theranos and Elizabeth Holmes:

  • Justice for healthcare crimes is often deferred for those who have influence and money.
  • Holmes’ image overhaul may be a last-ditch effort to sway public opinion about her, in the event that she receives a new jury trial as a result of her appeal.

Dark Daily will continue to keep you updated on further developments in this case.

Scott Wallask

Related Information:

Liz Holmes Wants You to Forget about Elizabeth

Hot Startup Theranos Has Struggled with Its Blood-Test Technology

Theranos Ex-CEO Elizabeth Holmes Convicted on Three Counts of Wire Fraud and One Count of Conspiracy to Commit Fraud after Seven Days of Jury Deliberations

Holmes, Balwani Get Lengthy Prison Terms for Theranos Fraud

Disgraced Theranos Founder Elizabeth Holmes to Serve 11 Years, Three Months in Prison, Ending the Latest Chapter in the Story of the Failed Clinical Laboratory Company

Federal Prosecutors Seek $878 Million Restitution from Former Theranos Founder/CEO Elizabeth Holmes

Medical Residency ‘Match Day’ Yields Rare Mother and Son Placements with Mother Matched to Pathology Program at the University of Wisconsin-Madison

It was a special and unusual moment for this mother and son duo as they applied for acceptance into residency programs and were both matched on the same day

Pathologists and other clinical laboratory scientists who underwent the matching process will be interested to learn how a mother and son were matched on the same day as part of the National Resident Matching Program (NRMP) 2023 Match Day.

Match Day is the next step for medical and medical technology students to be placed into desired training programs in chosen specialties. According to the NRMP website, pairings are determined by a mathematical algorithm to match applicants with residency positions.

Wenjing Cao, MD, PhD, and her son Hefei Liu, MD, didn’t plan to apply for residency together, but when Cao wanted to return to medicine, the pair realized they could be matched to programs at the same time, Good Morning America reported.

Cao, 54, is currently a research scientist/professor at the University of Kansas. She graduated from medical school in China and spent 10 years practicing internal medicine there before immigrating with her family to the US in 2006. Liu, 26, is finishing his oncology studies at the Medical College of Wisconsin where he expects to graduate in May.

Hefei Liu, MD and Wenjing Cao, MD, PhD

Hefei Liu, MD (left), a radiation oncology student at Medical College of Wisconsin, and his mom hematologist Wenjing Cao, MD, PhD (right), a research scientist and professor at the University of Kansas, matched residencies on the same day during the annual National Resident Matching Program 2023 Match Day. Pathologists and clinical laboratory scientists know how exciting this day can be for residency applicants. (Photo copyright: Good Morning America.)

Pair Express Their Excitement, Awe

The matching program will take the pair to different locations for their training. Cao will be headed to the clinical pathology residency program at the University of Wisconsin-Madison and Liu to the University of Pennsylvania for the radiation oncology residency program, Good Morning America noted.

“When she told me she was going to reapply this year and it was the same year I was applying, I thought, this could actually happen. Somehow it did and it’s still incredible to me,” Liu said.

Cao is also thrilled. “This is incredible and amazing, something I feel very excited about. I never thought I would go through this process with my son together,” she told Good Morning America.

National Resident Matching Program

Though this is a special and rare moment, it’s not the first time the NRMP matched a parent/child in the Main Residency Match. However, Stephanie Bartek, Senior Communications Analyst for the NRMP, told Dark Daily that the NRMP does not track whether applicants are related, so there is no way to provide odds of it occurring.

The NRMP has matched physicians to residency training programs since 1952, but in 1984 it formalized the Medical Specialties Matching Program (MSMP) which matches physicians into fellowships and subspecialty training programs.

The first fellowship match was for Colon and Rectal Surgery. Since then, the NRMP has grown the MSMP to 73 subspecialties in 20 separate fellowship Matches, according to an NRMP press release.

2023’s Matches Speak to Healthcare Growth

“The 2023 Main Residency Match proved once again to be a highly successful Match with outstanding results for participants. We were excited to see the record number of primary care positions offered in this year’s Match and how the number of positions has consistently increased over the past five years, and most importantly, the fill rate for primary care has remained steady,” said Donna L. Lamb, PhD, NRMP President and CEO, in a press release announcing the release of “Results and Data Specialties Matching Service, 2023 Appointment Year for Fellowship Matches Conducted by the NRMP’s Specialties Matching Service (SMS)” in April.

The report shows 13,919 active applicants competed for 13,365 fellowship positions offered by 5,734 programs, according to the press release.

“For the past 70 years, the NRMP has been proud to play a part in helping physicians transition into residency training and begin careers serving their patients and community,” she added.

Age is Only a Number

Cao hopes her match will impact individuals who are holding back from following their desires.

“I hope my story can inspire so many others like me, at my age, [in their] 50s, and as a mother, as a woman, as an immigrant, [anyone] can pursue their dream, as long as you want it,” she said. “It’s your dream, put hard work on it. Keep positive. Stay motivated. You can get it.”

Her son Liu mirrored her sentiment. “If you see your parents or any of your family members who are interested in pursuing medicine and they have an interest, but they clearly have some sort of obstacles in their life, you should … be supportive of them and encourage them to pursue that dream because I think with dedication, hard work, and sometimes just even luck, that you can truly achieve your success.”

With the demand for pathologists in the United States outstripping the supply, Wenjing Cao, MD, PhD, may have her pick of positions when she finishes her pathology residency program and any pathology fellowship programs she may undertake.

—Kristin Althea O’Connor

Related Information:

Mom and Son Celebrate Matching Residency Programs Together: ‘Still incredible to me’

NRMP Publishes Comprehensive Data Book for Fellowship Matches

Medical Specialties Matching Program

Results and Data Specialties Matching Service, 2023 Appointment Year for Fellowship Matches Conducted by the NRMP’s Specialties Matching Service

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