Do You Have a Healthcare Fraud Prevention Strategy Ready for COVID-19?

Do You Have a Healthcare Fraud Prevention Strategy Ready for COVID-19?

Artificial Intelligence allows health plans to more nimbly address FWA while reducing false positives

To make an obvious understatement, the new coronavirus (COVID-19) pandemic is an event like we’ve never seen. While essentially the whole country is shut down, the healthcare system is both slowing and accelerating at the same time. All of us in the FWA business know that 99.9% of providers are working tirelessly to treat affected patients, calm those with symptoms, and manage an unprecedented healthcare event. At the same time, both intentional and unintentional changes may spur a spike in healthcare fraud, waste and abuse.

I have recently seen personal examples of how changes to treatment and patient care during this time will change, with both my primary care and multiple specialists moving to Telehealth visits.

You have probably already seen that the Department of Health and Human Services (DHHS) and the Center for Medicaid and Medicare Services (CMS) have eased some of the coverage and benefit restrictions for many enrollees to allow for less administrative issues on the part of providers as well as quicker time to treatment. The Coronavirus Preparedness and Response Supplemental Appropriations Act, 2020 (§H.R.6074) was signed into law on March 6 along with authorized federal spending to help with the pandemic. There are several aspects to the bill but perhaps most pertinent to the SIU involves the ability for the DHHS secretary to temporarily waive certain Medicare requirements for Telehealth services.

Foremost among the Telehealth changes (Telehealth Services During Certain Emergency Periods Act of 2020) that initially affect Medicare beneficiaries by allowing more lenient guardrails around Telehealth include:

  • Waiving originating site (such as hospital, physician office, etc.) and the geographic requirement
  • To qualify for the waiver, the provider must have treated the patient within the past 3 years or have been in the same practice as a rendering provider
  • Telehealth patients can use their Smartphones to receive the Telehealth visit

Medicaid changes and reimbursement will, obviously, be on a state-by-state basis, but several U.S. House Representatives are requesting their states relax Telehealth requirements similarly to CMS. We are already seeing some of our commercial payer customers changing Telehealth reimbursement (CPT 99201-99215; HCPCS G0425-G0427; G0406-G0408; G2012, G2010) to reflect a typical office visit (CPT 99210-99215). In addition, we should expect that not only will many commercial plans duplicate the CMS recommendations, but we should expect some copays may be waived as well.

If some estimates are accurate, as much as 80% of the visits in the coming weeks and months will be via Telehealth. Therefore, payers need to be prepared to identify not only potential fraud, waste and abuse, but also to recognize when the encounter is a false positive due to the pandemic.

Because our Pareo Fraud solution incorporates multiple layers and scoring modalities, there are 4 primary areas where AI can assist in quick and accurate recognition.

Look at more than a just query of CPT, ICD-10 codes

If you’re using only a rules-based system for detection, queries into codes alone will show a limited range of views into an encounter and, more importantly, a trend. Since the pandemic is, by its nature, time-based and characterized by specific symptoms, a multi-faceted view is important.

An example of this would be using Artificial Intelligence to dig deeper and wider to look at metrics such as specialty, dates of service, patient acuity, and past treatment history of the individual patient in coordination with each other. The model then compares like providers based on those metrics, as well as like patient history, past SIU history of the provider, and other key indicators. The model continues to learn and evolve as the system reviews more claims so what might not be a trend today, could be recognized as one tomorrow. This helps SIUs instantly recognize an issue and take immediate action.

Spikes in volume from week-week, month-month, especially with highly likely specialties

Monitoring spikes in claim volume based on dollars paid or number of unique patients is always important and common among most SIUs. But COVID-19 identification and treatment are moving so fast that it may be difficult to keep up with a spike. Therefore, your detection should be able to determine what was “normal” at what points in time, when did it become “abnormal” and for how long. This may seem like a retrospective approach, but AI enables you to simultaneously look at historical normal, recent and current spikes, and predict what the “new normal” should look like.

The AI models in Pareo Fraud combine the time frequency, frequency of codes billed during the time frame, volume and frequency of length of time that the provider has been seeing the affected patient population, any previous payment integrity audits on the codes, and others. As of March 13, 2020, the AMA created a new CPT code to help streamline Coronavirus testing, so the utilization of dates and billing frequency becomes even more important.

Scope of Practice and Specialties

Most states have requirements around Telehealth and who can provide these services. The medical boards of 49 states, plus those of the District of Columbia, Puerto Rico, and the Virgin Islands, require that physicians engaging in telemedicine be licensed in the state in which the patient is located. Twelve state boards issue a special purpose license, telemedicine license or certificate, or license to practice medicine across state lines to allow for the practice of telemedicine.

However, the symptoms of coronavirus may not be the virus itself but, instead, other illnesses such as flu, bronchitis, pneumonia or simply a common cold. This lack of clarity makes identifying actual COVID-19 cases and legitimate testing and treatment difficult to differentiate from a provider trying to take advantage of the system. Paying careful attention to the specialty of the provider, combined with their history and the patient’s history is important.

The AI models in Pareo Fraud can combine the following to help identify excessive coronavirus testing and treatment outside of the normal:

  • Specialty. We should expect to see, with varying degrees of frequency, all primary care, Pediatrics, ER, Pulmonology, Allergy & Immunology, Infectious Disease
  • Dates of service. When did billing for the common coronavirus CPT and ICD-10 codes start, peak and tail off?
  •  Geography of the provider’s patient population
  • Peer-to-peer analysis of provider vs. same specialty
  • Place of Service to determine ER, hospital, office, Telehealth or elsewhere.

Again, these metrics are incorporated into a single model and, when combined with other AI models, give a fuller picture during a specific time frame (the pandemic).

What about false positives?

Dealing with false positives will always be a challenge when fighting healthcare fraud, waste and abuse. Due to the extreme nature of the coronavirus outbreak, severity of symptoms and overall lack of testing equipment, there is still the concern of people flooding the healthcare system when even just one of the many COVID-19 symptoms are present. This will create enormous volumes of claims that are at least somewhat related to the outbreak. So how does an investigator differentiate from a concerned patient and a diligent provider versus a potential suspect?

By using the AI models described above, much of the differentiation can be accomplished within the technology itself, before an investigator must make a judgment call. Because of the self-learning nature of the models, they can determine a one-off from a trend, and look at multiple dimensions of providers, members, claims, and overall encounters during a finite (hopefully!) period. This helps alleviate inconveniencing a provider about legitimate claims and focus on the those trying to take advantage of a once-in-a-lifetime situation.

Let’s hope that this is a temporary challenge but also be vigilant in helping those who need it while identifying those trying to profit off some very trying times.


Talk to ClarisHealth about how Pareo® comprehensive payment integrity technology is helping health plans deliver on their most advanced digital strategies. 

Evaluate Advanced Healthcare Fraud Solutions in 3 Questions

Evaluate Advanced Healthcare Fraud Solutions in 3 Questions

How can your health plan tell if a fraud solution’s claims are valid? 

Just in the last year, dramatic leaps forward have occurred in advanced technology, and new healthcare fraud solutions have emerged to take full advantage of these improvementsAccording to futurist Peter Diamandis, these advances are made possible by one thing, but its impact is far-reaching: “Computation is the foundation. Be it classical or quantum computing, as it becomes faster and cheaper lots of technologies that use it also become more capable. For example, communication networks, sensors, robotics, augmented and virtual reality, blockchain, and AI are all exponentially improving.  

As applications of Artificial Intelligence (AI) evolve beyond buzzwords to usefulness in the real world, some legacy healthcare fraud solutions have adjusted their messaging to put a new shine on old technologyIf you’re a data scientist, you may easily intuit the difference. For the rest of us, it requires a bit of investigating.  

Maybe the fraud solution you are evaluating actually is an application of AI as the technology vendor claims. Maybe it isn’t. But, how can you tell? Here are three questions you should be asking when you seek out a modern healthcare fraud solution. 

1. What do you mean by “AI”? 

Too many technology vendors – in all industries – throw around the term “AI” because it’s largely and too easily misunderstoodLayperson understanding of the term implies AI is “computers doing stuff for you.” Academically speaking, AI refers to building algorithms that produce outcomes indistinguishable from human cognition. They key word here is “artificial” not “intelligence.”  

True AI applications should not additionally tax your already-constrained data science resources, but rather free them up to focus on higher-value activities. In a recent survey, industry leaders said they see AI as a pragmatic solution today for “a variety of administrative challenges such as automating pre-authorizations, managing electronic health records, and detecting fraud, waste or abuse in reimbursement. 

In fact, one innovative regional health plan that serves 4.5 million members has reported significant progress towards detecting fraud schemes pre-pay after adding AI methods to their multi-pronged approach to mitigating FWA. 

Red flag: Vendor can’t provide a thoughtful answer to this question.

2. What methods support your AI approach?

Because AI is an application of methods, it pays to question your potential vendor partner about these details. Especially if your “sixth sense” kicked in after their answer to the first question, this question is key to digging deeper into those fuzzy details. But first, let’s define a couple of terms you may hear during this line of questioning: 

Neural networks: Seeks to simulate human brain processing, which is facilitated by networks of neurons. At its simplest, a neural network processes information in three layers: 1. Input layer where data enters the system, 2. Hidden layer where data is processed, and 3. Output layer where the system decides what to do with the information. 

Deep learning: Allows for increasing numbers of layers through which data passes, where each layer of nodes trains on a distinct set of features based on the previous layer’s output. The further you advance through the layers, the more complex the features your nodes can recognize, since they aggregate and recombine features from the previous layer. 

Though these terms are often used interchangeably, neural networks and deep learning are related but different. The way they differ lies primarily in how they process information. Neural networks require a great deal of structured historical data in order to train their learning and decision making. As a follow-up question for vendors claiming this method, ask them how they train the neural nets, which require historical dataTraining on just SIU data, for instance, would limit the neural net’s effectiveness because it isn’t fully representative of broader claims data. 

On the other hand, deep learning is able to learn from data that is both unstructured and unlabeled. A boon for healthcare where at least 80% of data – images, medical records, etc. – is unstructured. A recent article explains the advantage of this model. “Unlike the resource-intensive and largely static nature of traditional payment integrity processes, intelligent algorithms continually learn and evolve with each claim.” 

Red flag: Vendor can’t articulate what type of underlying method supports their AI approach. Or, they refer to SQL queries, clustering, etc. that are remnants of older, less robust technology.

3. How is domain knowledge and expertise being incorporated into analytics?

No matter how reality-based the AI application is or how sophisticated the underlying methods are, the models will be insufficient to the task of detecting healthcare fraud unless they thoughtfully incorporate domain knowledge. 

On one end of the spectrum are rules-based engines, which are static and therefore surface only known schemes. Legacy fraud solutions often fall into this category; still relevant but not flexible enough for the modern environment.  

On the other end of the spectrum are naive data analytics, which detect plenty of outliers but don’t distinguish between good/bad data and therefore result in too many false positives. Think of credit card fraud detection systems, which can’t account for the complexity inherent to healthcare fraud scenarios. 

What’s the happy medium between these two extremes? For SIU divisions to prioritize cases appropriately, they need to be able to understand the motivators for flagging potential fraud. By combining the best parts of each approach, a modern FWA solution should be able to detect aberrancies from a data perspective and use domain knowledge to impute meaning into findings. 

Red flag: Vendor can’t speak to false positive rate or can’t articulate how domain knowledge is incorporated into analytic models.

You can have it all.

Modern technology has finally caught up to the complex scenarios inherent to healthcare FWAInstead of persisting with outdated solutions that simply check fraud compliance off the list, your SIU department can find previously unknown schemes, reduce false positives and improve time to resolution. 

ClarisHealth is continuing to develop Pareo Fraud Detection using deep learning methods to build nuanced algorithms and multi-tiered provider scoring on multiple models, weighted in importancein a payer-specific hierarchical nature, so investigators can understand exactly why a claim is flagged for further investigation. This structure also ensures that the issues relevant to the individual payer are taken into consideration.  

The models are being developed in partnership with the University of Illinois Chicago Center for Research in Information Management. Its leading-edge academic research, ties to the UIC College of Medicine, and analytic methods and technology is headed by a data scientist with over 20 years of experience leading Payment Integrity and FWA analytics for payer organizations are a boon for health plans adopting Pareo Fraud. 

  • Robotic Process Automation (RPA) allows your most valuable resources to concentrate on high-value activities instead of tedious administrative tasks. Get to exactly what you need in fewer clicks. 
  • Modern analytics based on deep learning methods push the leads to you, rather than manual queries to pull leads.
  • Automated reporting for state Medicaid and non-government entities keeps you in compliance. 
  • Seamless integration of detection – analysis – case management to Audit, COB, Data Mining and other areas of Payment Integrity minimizes provider abrasion and administrative burden. 



Talk to ClarisHealth about how Pareo® comprehensive payment integrity technology is helping health plans deliver on their most advanced digital strategies. 

Your FWA solution may not be as modern as you think.

Your FWA solution may not be as modern as you think.

The package may have changed, but the truth is most FWA solutions are still relying on legacy technology. 3 ways to spot the difference.

To prepare for the advancing disruptions to healthcare, most plans we speak with have made some progress towards digital modernization. Often, they’re starting with evaluating their current technology vendors, except for one glaring oversight: fraud, waste and abuse solutions. Did you know, those on the market today are by and large relying on 30 to 40 year old technology? Even many “new” solutions are old products dressed up in new packaging. 

While it can be comfortable to use products we are most familiar with, the problem is, the way we’ve always done things just won’t cut it anymore. It’s very possible that with each passing year, your tried and true technology isn’t quite so effective. Recent advancements in automation and predictive analytics have yielded modern FWA solutions that promote transparency and integration with other systems. 

Got a hunch the FWA solution you’re using may not be as modern as it should be? Get ready to evaluate the evidence for the three big signs of outdated technology. 

1. Reporting Struggles

Your health plan’s FWA solution may be legacy if… it relies solely on rules-based reports. While rules-based reporting is foundational functionality that is still useful, it only addresses known schemes. Fraudsters are changing up their schemes more often than what legacy solutions can keep up with, meaning this outdated approach will leave health plans in a precarious place (and do you really need to combat more false positives?). 

Rules-based reporting is not multi-dimensional and this impairs an investigator’s ability to ascertain legitimate leads. What’s more, some algorithms are actually rules-based which holds them back from being the robust solution so desperately needed in this industry. “Traditional analytics solutions built on relational databases aren’t up to the task,” writes Fierce Health Payer. That’s because fraud schemes are growing increasingly complex, and flat views of them will make legacy FWA solutions a drain on the SIU’s limited resources.

Another reporting issue? The “pull” approach. If your reporting lags and is centered around knowing the right questions to ask, you aren’t accessing the bigger picture. In comparison to a robust data analytics system, pulling reports does not prioritize issues. “Payers should look for platforms that visualize data in an informative way, develop insights using financial big data, and support predictive analytics capabilities,” writes Health Payer Intelligence.

2. Too Little Information on Providers

Lacking visibility into providers? You’re not alone, and it’s yet another sign of older FWA technology. The SIU is by and large missing the ability to efficiently and effectively access provider details, which may range from a particular provider’s associated practices to a lack of visibility into provider education (and no way to measure efficacy of that education). 

When investigators lack visibility into provider data, efforts to obtain that information come at a cost. And while manually communicating to determine provider details or check in on remediation programs, health plans run the risk of a greater cost in the form of provider abrasion. While most fraud schemes may happen at the provider level, very few providers are fraudsters. Communications from the SIU have to be considerably more precise and streamlined than what legacy technologies may afford.

According to NHCAA, “the majority of healthcare fraud is committed by a very small minority of dishonest health care providers.”

Research by the Government Accountability Office (GAO) shows the following trends in provider fraud schemes: 

  • Falsifying claims or diagnoses
  • Participating in illegal referrals or kickbacks
  • Prescribing unnecessary medications to patients
  • Upcoding for expensive, medically unwarranted services

3. Limited to Pay-and-Chase

Health plans are weakened without the proper tools to navigate away from pay-and-chase and towards prevention. But the standard approach to FWA is chasing down improper payments, rather than preventing them. If your current FWA solution does not allow you to effectively detect the risk of an improper payment before that claim is paid, you’re likely using a legacy system.  

Now that the technology is improving, more sophisticated approaches are available. These preventive solutions tend to rely on predictive modeling, but be warned the quality can vary greatly. If a vendor you are considering uses buzzwords like “AI” and “machine-learning” to describe their product functionality, you should know these terms are often used incorrectly. 

It behooves SIU and Compliance teams to drill down into vendor claims of advanced technology to see how predictive capabilities function. Are they dynamic and do they rely on good data? Are they using the right set of metrics? And perhaps more importantly, can these advanced technologies integrate intelligently with a plan’s overall payment integrity processes? Because more and more, effective FWA detection is reliant on more than the SIU. 

So your FWA solution is outdated, now what? 

If you think your FWA solution is no longer up to the task, it may be helpful to focus first on what your organization needs from a technology provider. A true FWA solution is one that gives investigators the tools they need to separate the signal from the noise, quickly and effectively. Advanced integrative technology that provides broader access to real-time data will allow your health plan to modernize the SIU. 


Talk to ClarisHealth about how Pareo® comprehensive payment integrity technology is helping health plans deliver on their most advanced digital strategies. 

Here’s What You Don’t Know about Fraud, Waste and Abuse

Here’s What You Don’t Know about Fraud, Waste and Abuse

Fraud is different from Waste and Abuse, and most technology solutions don’t adequately address either issue.

Think you know how to manage fraud, waste and abuse at your healthcare organization? CMS doesn’t agree. In fact, the promises of change and reform coming from CMS and GAO suggest that our government doesn’t feel that healthcare organizations are adequately managing fraud, waste and abuse at all. The data we have supports this. FWA estimates are in the billions, with the latest estimates pegging waste at 20-25% of healthcare spending.

Technology and services vendors who sell you components of fraud, waste and abuse management programs are doing you a small disservice if they market it as a total solution. They know as we do that, without system visibility, health plans and managed care organizations can only hope to control FWA – not eliminate it.

We aren’t suggesting that you shouldn’t work with technology vendors and third-party business partners – not at all. What we are saying, however, is that health plans need to do more than casually plug in a piece of technology or adjunct services with the hopes it will improve their FWA efforts. A more robust, proactive method is required to eradicate fraud, waste and abuse in your health organization.

The Confusion Surrounding “Overpayments”

By 2026, at least 7% of healthcare spending is expected to be made up of some sort of overpayments. That’s $400 billion – at least – and only 5% of that is expected to be recovered. But “overpayments” is a broad term that encompasses everything from mistakes to intentional fraud. Though fraud makes the headlines, the greater percentage of cases – and far costlier to the health plan – are incidents of waste and abuse. And they must be handled differently.

Going back to our earlier point, a health plan must be fully aware that programs to manage fraud, waste and abuse are only a piece of the puzzle. The key to gaining traction at your health plan is visibility. This is why CMS and GAO promote interoperability; they understand that with access to a broader picture (one that is accurate in real-time), you are less likely to get hung up in waste areas like administrative complexity.

What is your health plan doing about the 10% of inaccurately paid health claims?

Here’s how you can reduce FWA losses by 40% in one year.

We have explored the differences between fraud, waste and abuse in previous blog articles (here and here). To summarize, the primary difference between incorrect payments is intent. Fraud and abuse are categorized as illicit, but only fraud is recognized as willful. Together, fraud and abuse account for7% of healthcare spending. Waste, however, is excessive cost tied to administrative complexity, poor processes, paying costs to suppliers that are too high, and other wasteful spending practices. Clinical waste alone accounts for 14% of healthcare spending. But these are just examples to showcase the breadth of this problem.

In truth, there’s a lot that many health plans don’t know about fraud, waste and abuse – and it’s costing them millions.

“Fraud, waste and abuse is a huge contributor to unnecessary costs and the rise of spend within healthcare in the U.S.”

Forrester Research, 2019

What You Don’t Know About FWA – And How to Fix It

In order to fully solve the overpayment crisis in America – including fraud, waste and abuse – health organizations need to shine a light on the areas of this problem that remain uncovered. In 2016, CMS estimated the Medicaid improper payment rate at 10.5% or $36 billion.

A good FWA solution, integrated as part of a broader overpayment prevention program, should be able to make quick progress of identifying leakage at your healthcare organization. Here are 6 things you don’t know about FWA – and how to fix them:

Modern Fraud Solutions Combat Modern Schemes

The fragmented capabilities of most existing FWA solutions simply can’t keep up with the increasingly sophisticated schemes that keep emerging. Success is stymied by false positives, deeply hidden issues go undetected, and increasing time to detection and action prolongs losses. Advanced technology featuring predictive analytics promises to be able to analyze the massive amounts of healthcare data, flag likely fraud before it starts, and quickly build evidence needed to bring a case forward. When fully integrated across your health plan’s cost containment efforts, total payment integrity leverages all aspects of your PI program to bring insights that help increase savings, reduce redundancy and improve efficiencies and workflow.

Waste is Eliminated with Efficiency

Health Affairs defines waste as “spending that could be eliminated without harming consumers or reducing quality of care that people receive.” And wasteful spending, by some estimates, can amount to as much as one-third to one-half of all US healthcare spending. Administrative complexity shoulders the majority of the blame, and while it’s true that waste can be complex, the answer is more straightforward. Waste can be eliminated with efficiency. And efficiency is as much as mindset as it is a practice. Health plans that don’t focus on and achieve efficiency in their processes will struggle to combat FWA.

Waste and Abuse Outsize Fraud

Fraud is intentionally “playing the system” to erroneously benefit from it. It’s also rare, making up only 7% of healthcare spending when combined with abuse. But it’s easy for a health plan to be sold on the fear of fraud, perhaps leading to an overinvestment in technology that addresses fraud moreso than waste and abuse (which when combined far exceed fraud in the US). Health plans face increased audits from CMS, so it’s more important than ever to understand what percentage fraud, waste and abuse contribute to your health plan’s own payment rates.

Overpayments are the Bigger Issue

A report released three years ago by Harvard Business Review found that “even if the United States implemented all the approaches whose effectiveness had been measured, only 40% of the estimated $1 trillion of wasteful spending would be addressed, leaving a significant opportunity for innovation in all areas of health care.” The report estimates that innovations could reduce waste by $600 billion alone, presumably betting that healthcare (like many other industries) stands to benefit from technological improvements. Our takeaway from this report? A total payment integrity program must address more than FWA in order to maximize effectiveness. Innovations to reduce waste need to involve broader overpayment-prevention technologies.

Provider-Payer Partnerships Help Combat FWA

“Combating waste is an area that will require collaboration between employers, health plans, patients, and providers. The benefits are worth the effort: improving patient safety and reducing unnecessary health care costs,” writes Mercer US Health News. Working with providers in a meaningful way means treating the relationship as a partnership, one where both parties have a vested interest in resolving or preventing fraud, waste and abuse. In fact, improving this relationship is a top tactic for mitigating excessive prices, the number 2 culprit of waste at $231-241 billion per year. Tighter provider partnerships allow both parties to better tie prices to efficiency, outcomes and a fair profit. 

Reporting Should Be Ongoing – And Shared

Your health plan’s goal should be to transition efforts from post-pay to prevention. To that end, health plans should regularly measure certain metrics (Mercer recommends measures of misuse, over-use, and under-use be built in to provider contracts) but also share their findings. It may be helpful to share certain information with vendors, providers and staff from other departments. If information is shared more freely and interoperability is obtained, we can all benefit from the data that comes from payment integrity programs.

One Solution for All

You’ve likely heard the statistic that for every $1 spent on FWA investigations, more than $4 is recovered. What if you were able to take that investment even one step further? Pareo® was created to do something no other payment integrity solution can: plug in at multiple levels to provide health plans with the total system visibility that’s necessary for eliminating overpayment problems.

Our innovative technology combats wasteful spending by introducing more efficient processes for our clients. These accommodations include:

  • Unique differences by line of business
  • Integrated institutional and provider environment
  • Various payment methodologies: DRG, APC, ASC, per diem, fee schedule, percent of charge
  • Automated medical coding and billing

Talk to ClarisHealth about how Pareo® can transform your health plan’s payment integrity operations.

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An Aggressive Plan to Move your Claims Recovery to Prepay Status

An Aggressive Plan to Move your Claims Recovery to Prepay Status

Transitioning more payment integrity operations to internal prepay is more than just a pipe dream for health plans

Transitioning prepay. It’s the holy grail for health plans — and viewed as equally unattainable. And, in the not-so-distant past, this viewpoint would have been correct. But now, with the assistance of innovative technologies, health plans can take an aggressive approach to transitioning claims recovery to an internal prepay model. Here’s a look at the challenge of transitioning to prepay, the solution we propose, and why your health plan can’t continue the business-as-usual efforts in this area. 


The “Challenge”

Historically, health plans applying post-pay concepts in a prepay environment have been mutually exclusive ideas

In today’s market, it’s essential for health plans to get a handle on payment accuracy. But, without the proper technology tools in place, it’s difficult for payers (and other healthcare stakeholders) to gain true visibility into their operations. In the case of third-party technology suppliers, who rely on their partners to perform at peak level, these murky waters may prove especially hard to navigate. 

Without comprehensive insight and management, it is very difficult for payers to move the needle on claims recovery. Especially when attempting to shift claims from post-pay to prepay, though doing so promises improved efficiencies and higher rates of return for health plans. We see two common barriers to making this shift:

  1. Even if your third-party vendors possess the kind of technology that would enable you to move more claims to prepay resolution, health plans have no ability to store the most successful concepts and apply advanced analytics prepay. 
  2. Even if you do have insights, limited data analytics resources prevent you from taking full advantage of advanced technology.

You may know that some health plans have been able to shift claims recovery efforts to internal prepay activities, but do you fully understand how? In part, successful plans achieve this by breaking down data barriers. With the right solution in place, payers can actually overcome the limitations that poor data visibility place on them. 


Why Prepay is an Urgent Concern

Health plans need the efficiencies that comprehensive payment accuracy technology brings, and prepay is an opportunity to make quick strides. 

We get it. You have a laundry list of to-do’s, all vying for top priority. Digital-first strategy, member experience improvements, optimizing costs and outcomes — these are all important goals. But, it could be that a focus on claims recovery gives your health plan the breathing room it needs for these significant investments. And as professional program integrity problem solvers, we think a shift to prepay is a valuable opportunity for health plans looking to gain traction on aggressive payment accuracy targets. 

We aren’t alone in suggesting a technology solution to improve claims recovery (and management in general). Earlier this year, Fierce Healthcare pointed out, down to the dollar, how much it costs a payer to manage claim inquiries. “When a provider contacts a payer to check a claim status, it takes an average of 14 minutes and costs the provider $7.12… multiplied by millions of requests each year, the time and money add up. In 2018 alone, providers made 173 million claim status inquiries by phone, fax or email.” 

Investing in data analytics is a growing trend. In fact, 60% of surveyed health executives say they are investing more in predictive technologies in 2019. Claims recovery will continue to be an important facet of your health plan’s payment accuracy operations. With the right solution in place, the ability to shift to internal prepay concepts will be in your hands. 


The “Solution”: Pareo® is How

With a centralized solution like Pareo in place, everyone can get on the same page, including vendors and other departments responsible for payment accuracy. 

It may take time, it may necessitate a change in how you do things, but we believe all health plans have the opportunity to deploy a centralized solution for payment accuracy (and reap the benefits). Here’s an idea of how a PI solution like Pareo works from a holistic vantage point to quickly turn around recoveries at your health plan: 

Our team works with you to develop a specific implementation and use plan for Pareo that meets (and often exceeds) the goals you’ve outlined for your plan. If shifting to prepay cost avoidance is a goal of your health plan, Pareo is the comprehensive solution that will help you get there.

Talk to ClarisHealth about how Pareo® advanced payment integrity technology is helping health plans deliver on their most advanced digital strategies.

Lack of Documentation is a $23 Billion Overpayment Problem for Medicare

Lack of Documentation is a $23 Billion Overpayment Problem for Medicare

Medicare overpayment is a massive problem, and lack of documentation is a significant contributor.

When we see errors adding up to billions of dollars in improper payments, we pay attention. As payment integrity technology experts and also healthcare consumers we take notice when Medicare fee-for-service programs get slammed for $23 billion in improper payments due to documentation errors. More jaw dropping? Poor documentation processes cause 64% of improper payments in Medicare.

Let’s take a deeper look at how the problem of insufficient documentation became so huge and what you can reasonably do to address documentation errors at your health plan.We have considerable experience on the provider side of healthcare, and our interest in payment integrity is hyper-focused on automating some of the documentation processes required by the federal government.

Just How Big of a Problem are Medicare Overpayments?

When we discuss Medicare overpayment issues, it’s usually a million+ or billion-dollar problem. Recent headlines point to this fact:

CMS may overpay Medicare Advantage plans by billions, study finds


$50 billion in Medicare waste? Yes, that’s how much in ‘improper payments’ are made per year

We’ve spent a considerable amount of time on our blog discussing fraud, waste and abuse and the role these elements play in improper payments. The problem is complex, and the solutions have to be agile and at-the-ready in order to be effective. According to Seto Bagdoyan, a director of audit services at the Government Accountability Office (GAO), of the “billion dollar a week” waste figures cited for 2017, $45 billion can be attributed to overpayments.

Some experts counter that the way HHS calculates waste is “weak,” and Medicare may actually have a larger problem than the already outsized figures making headlines. It’s hard to fathom the depths that Medicare waste truly runs, but being the problem solvers we are, we urge you to look at one sizable chunk of the problem: Improper Documentation.


What is “Poor Documentation” and What Causes It?

If you can’t easily see the patient’s medical “story,” you’re likely looking at insufficient documentation.

Poor documentation has devastating impacts on patient care and is also a large driver of the improper payment problem. Health leaders attribute poor documentation problems to:

  • Busy Providers
  • Lack of specificity
  • Need for documentation education
  • Diluted content from “copy and paste” methodologies

CMS indicates that documentation needs to occur during or quickly following a patient visit and should follow the principles outlined in this document (which includes stating the rationale behind ancillary services or documenting in a way that makes the reason easily inferred).


“In fiscal year 2017, insufficient documentation comprised the majority of estimated FFS improper payments in Medicare and Medicaid, with 64 percent of Medicare and 57 percent of Medicaid improper payments due to insufficient documentation.” (source)


Most Overpayments Stem from Documentation Errors

Recently, the GAO reported in detail that overpayments in Medicare and Medicaid are mostly due to “insufficient documentation.” GAO figures the amount to be $23.2 billion for Medicare alone and $4.3 billion for Medicaid. CERT review criteria changed in 2009 and was attributed as a primary cause for discrepancies between FFS programs; Medicaid’s rate of insufficient documentation is only 1.3% while Medicare is over 6% on all claims.

The way medical reviews have been conducted is now being questioned, with the GAO citing the following four areas of difference:

  1. Face-to-face examinations
  2. Prior authorizations
  3. Signature requirements
  4. Documentation from referring physicians for referred services

The truth is, poor documentation is a problem we saw coming. We know that providers are busy, that their primary focus is serving patient needs, and that most EHR “solutions” are just more manual obligations for busy medical staff. Across the board, the ability to connect data between disparate systems is one that our industry has struggled to solve. That’s what makes Pareo® so unique. And with administrative complexity only growing, we’ve worked up a solution.

Pareo® Clinical: Our Hyper-focused Solution

Pareo® Clinical is the answer to streamlined workflows, a full document repository to support the audit findings, and the ability to develop more robust analytics that can be implemented earlier in your processes to catch documentation deficiencies before the payment goes out the door.

And if under-documentation is an ongoing problem with certain providers, Pareo® Provider can open up the lines of communication between payer and provider and offer education to mitigate that issue in the future. Providers want to submit clean claims, after all.

Talk to ClarisHealth about how Pareo® can transform your health plan’s payment integrity operations.

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