The payment integrity guide for health plans

Although healthcare payments have undergone major transformations over the past decade, one thing is constant—the need for claims payment integrity remains paramount for payers. Not only does every inappropriately overpaid claim represent a cost that takes away from member care, these errors also erode the payer-provider-member relationship.

Health plans have bolstered their ability to prevent inappropriate claim payments before they’re paid through advanced analytics and new pause-and-review programs in recent years, but postpay solutions such as data mining and contract compliance continue to remain vital, coupled with optimizing coordination of benefits in tandem with the member lifecycle  and managing fraud, waste, and abuse (FWA). 

Read on as we break down the fundamental strategies behind implementing a comprehensive, end-to-end approach to payment integrity.

Prepay claims editing: Execute more accurately with less provider abrasion

Claim editing is generally a health plan’s first line of defense within its prospective payment integrity program. It’s a practice based on following guidelines and rules from organizations like the Centers for Medicare & Medicaid Services (CMS) and the American Medical Association (AMA) and codifying them into claim editing rules. How hard can it be to stand up a strong claim editing system? The answer may be surprising.

Some payers develop homegrown claim editing while many others follow the advice of organizations like Gartner, investing in vendor-supplied solutions to alleviate dependency on internal IT. But whether building or buying, health plans must understand and be prepared to handle claim editing challenges or be sure that their vendor solution can.

Recency, compliance, accuracy, and transparency of claim editing is of the utmost importance to a successful claim editing solution. One cannot just “set and forget” claim editing software. It requires constant maintenance and oversight for the highest accuracy and transparency, and there are many resources needed to adequately maintain it. Payers should consider several best practices when deploying a claim editing solution that pays claims with the highest accuracy and the lowest provider abrasion.

Extensive clinical resources

Broad and diverse clinical resources are needed to help you achieve and maintain the highest levels of payment integrity. And the more variety the better: certified coders, specialized registered nurses, and medical directors have different perspectives and areas of expertise when it comes to researching, building, and maintaining editing policies for regulatory requirements from AMA, CMS, state Medicaid agencies, and other bodies.

Regulatory alignment

When industry sources release updates to code sets (such as HCPCS, CPT, and ICD-10), teams must be prepared to review all new and deleted codes for a clear picture of how changes affect policies. This includes staying abreast of the timeline for these updates, as changes need to be made before the effective dates of the new code sets. For example, evolving National and Local Coverage Determinations (NCD/LCD), which often change without notice, require constant review to stay current. Similarly, every state in which a plan has licensed Medicaid business has different payment rules and documentation practices that need to be constantly monitored for change to avoid falling behind on payment integrity practices.

Technical resources and support

Technical resources are also key to updating the claim editing application—especially when there’s a regulatory update or policy change. And there’s no time to wait in a technical request queue, as delays can cause improper payments and noncompliance. Claim editing applications must reflect software updates released by vendors of integrated claim processing systems, while a dedicated technical staff must translate policies into properly functioning claim edits and maintain those edits for every policy and/or regulatory update. To update systems per these changes, payers may need to hire more technical staff.

Accurate claim editing also depends on a high level of agility. Most policies will change multiple times throughout the year, and a payer must be willing and able to handle that volume of change. To put this need for agility in perspective, it is not uncommon for a health plan to need to update as much as 96% of its policies at least once a year—with many updated twice or more annually. This could easily require 10 quarterly/semi-annual industry change reviews (e.g., CPT, HCPCS, ICD) and monthly reference reviews to help maintain the amount of avoided overpayment savings accrued for these policies. 

When a payer implements a vendor’s software system, it must ensure the vendor is prepared to handle such changes without exorbitant maintenance fees. The vendor should also support the client in optimizing data exchange, including implementation of new data elements to support new payment policy content.

Analytic and reporting resources

A health plan building its own or maintaining third-party claim editing software should also employ analytic and reporting staffers to provide leadership with ad-hoc reports and claim spend insights, as well as a strong understanding of provider trends for proactive policy enhancement.

For example, a plan may use analytics and reporting resources to identify potential over-coding rates among certain providers for evaluation and management (E&M) claims, where a level 4 or 5 was coded on the claim unnecessarily. Analysts should be able to prepare reports showing leadership the potential losses from physician office E&M policies not being followed by outlier physicians. With information in hand and leadership approval, the plan would be able to immediately turn on the right editing rule for a specific line of business, targeting only the highest outlier physician offices to start with to minimize abrasion.

Decreased provider abrasion

By creating a fast claim editing process, payers increase cost-effectiveness and decrease the provider abrasion that results from delaying claims payment or recovering overpayments. By implementing an automated claims editing system, supplemented with all the necessary human experts mentioned above, payers gain a payment integrity solution that is constantly and reliably updated for accuracy and regulatory changes, ultimately satisfying most providers.

Another component for decreasing provider abrasion is being transparent with providers about existing updates, and new claim editing policies. The user experience for both plans and providers looking into the details of particular claim decisions is an important component of claim editing. For example, a user-friendly system and process that allows claim inquiries to be answered quickly and with full, defensible rationale by claim analysts, while extending that same rationale through the plan’s web portal, gives providers the convenience of self-service. Together, these factors can help cut out lengthy processes that can frustrate both payers and providers.

Provider abrasion can also be decreased by health plans understanding the relative provider “acceptability” rate of new edits before deploying them, no matter the level of defensibility of the source. For example, knowing that 75% of providers in a health plan’s region are exposed to the same edits with very low appeal rates would give the payer much less pause to deploy them.

A reasonable solution

Though claim editing can look simple from afar, its many moving parts make it a complex, constantly changing machine. However, it doesn’t need to be overwhelming, and it doesn’t need to increase provider abrasion.

Optimal prospective payment integrity solutions require diverse components to function with speed, efficiency, and transparency. Whether your chosen route is internally made or outsourced, ensure that its total cost of ownership is worth it. When choosing to go your own way or to go with a managed service, be sure that teams have the capacity to research and develop edits, ensure system interoperability, and perform constant maintenance. If partnering with a vendor, an independently owned solutions and service provider that has nationwide experience with both payers and physicians offers the greatest breadth and depth of experience, ensuring that your payment integrity solutions can scale as your organization grows.

Postpay data mining and contract compliance: Why retrospective solutions are still vital

Prospective payment integrity solutions continue to gain traction among health plans to lower medical costs and improve relationships with providers. However, prepay solutions are only one tool available to ensure payment integrity. The foundational value of retrospective solutions, particularly for complex claims, makes them a vital part of any successful enterprise payment integrity program.

When it comes to payment integrity, prospective solutions are lauded for how much they accomplish before payment. And indeed, prepay solutions help speed the payment process so that claims can be verified faster. But prepay solutions are based on an existing high level of confidence in the accuracy of the claim information, which is most effective for less complex, routine claims. Postpay solutions are necessary to handle complex claims that require deeper scrutiny for verification. Claim complexity increases as data, validation, and timing requirements rise—and the more complex the claim is, the more plans need to rely on retrospective solutions. 

Here are a few scenarios where retrospective payment integrity solutions are preferred and even necessary.

Additional scrutiny for complex claims

Although payment for many claims can be automated, complex claims benefit from an added level of examination. In fact, part of the benefit of postpayment integrity solutions is that they can catch more problematic claims than prepay solutions can, whether due to the technological limits of a plan’s system, prepay time constraints, or claims excluded from the prepay data set: our analysis shows that 74% of the overpaid claims we identify with our postpayment data mining tools were excluded from the prepayment data set provided by our client.

Simpler claims align to pre-approved policies and require only claim data—and possibly a quick look at medical records—for validation, but more complex claims need additional data or provider outreach and can benefit from going through a postpay data mining solution. This is because postpay data mining solutions can catch issues such as complex incorrect modifiers, procedures, or revenue code mappings; multiple claim payments; or corrected claim modifications that prepay solutions may not capture. 

Human intervention for outreach and judgment

Claims that are even more intricate require specialized, human expertise to accurately analyze. After a thorough cycle of automated data mining to flag possible incorrect claims, human intervention from certified experts, beyond the interventions performed in prepay solutions, offers an in-depth, white-glove touch to claim editing. The human intervention component of a postpay solution can perform additional outreach needed to verify claims manually, especially in cases of adjudication errors. Human intervention can identify billing errors that need to be corrected, invoice or billing reviews, complex unit issues, or simply wrong information, such as claim edits that target incorrect providers or services that automated prepay processes would not identify. Other examples include contract-based reviews to ensure the intent of all terms, service-level definitions, and controls to ensure that rate hierarchies are applied correctly.

Clarity for claims triggered by future events

Postpay solutions are an imperative for claims that will be triggered by events that haven’t yet occurred. From late charges to retroactive fee schedule changes, there are many scenarios requiring a complete and thorough review of services over multiple claims and dates of service. Retroactive terminations are a good example of this. As dictated by the Affordable Care Act, retroactive terminations are only allowed in specific scenarios, and require a second look to verify. They therefore must be verified after the fact.

Other examples of increased complexity involve scenarios such as:

• Claim-level duplicates
• Corrected claims
• Retroactive contract pricing issues
• Medicare/other insurance primacy confirmation
• Drug frequency
• Adjudication errors

Contract compliance review

Contractual terms, prompt pay laws, and other state regulations all form the foundations on which healthcare claims should be quickly and accurately reimbursed per your providers’ agreements. To add another layer of complexity, payers must keep data safe and follow regulatory mandates such as HIPAA, HITECH, and SOC. Postpay claim reviews, supported by advanced analytics and data mining tools, must be deployed to remain compliant with relevant regulation and contracted policy.

Using postpay solutions in concert with prepay analytics is the key to a well-rounded payment integrity strategy. Whether as an added verification measure, a need for additional human intervention, or to navigate multilayered complexities, plans should consider what balance of postpay and prepay intervention work for them.

DRG validation: Sharpening auditing with better analytics and prepay review

Over the past several years, there has been an increase in costs related to inpatient care. Even before COVID-19, inpatient hospital stays were trending towards being more and more expensive. As such, plans should take care that diagnosis-related groups (DRG) are being validated correctly for inpatient visits. 

DRG validation is the review of inpatient paid claims data and its associated DRG designation to validate accurate claims payment. It’s typically made up of three components: documentation, coding, and clinical data. Documentation verifies the medical record contains the necessary information to support claim payment, coding verifies the diagnosis code on the medical record, and clinical data verifies the procedure codes and/or diagnosis noted on the medical record. For plans looking to keep DRG validation as accurate as possible, relying on analytics-driven chart selection, investing in prepay review, and performing cross-claim clinical review are the way of the future.

Analytics-driven chart selection

Analytics-driven chart selection is the most effective way to home in on the right charts that a plan wants to pursue for its inpatient audit program. Leveraging machine learning models and historic audit results drives precision in chart selection, reducing both cost and provider abrasion. Once Cotiviti selects the right claims for audit, using proprietary algorithms and predictive analytics, medical professionals with a deep understanding of evidence-based medical literature, including registered nurses, coding professionals, and physicians, can identify inaccuracies requiring a clinical perspective.

DRG validation with prepay claim review

Traditionally, most plans have relied on postpay claim review to catch inaccuracies in DRG claims. While this can be valuable, there is significant room for improvement. Cotiviti data suggests that time to value can exceed 90 days, with recovery yield hovering at about 70%. To boost value capture, prepay claim review is the next step to optimize inpatient claim DRG validation. Prepay claim review for DRG validation can save plans the headache of ”pay and chase,” where payment of the inpatient claim is made, an audit identifies an overpayment, and the plan is tasked with adjusting the claim and either preparing an offset or pursuing recovery. Prepay DRG review also streamlines processes so that DRG and chart data are shared from the beginning of the claim review process, increasing program value by as much as 20% while retaining sustainability rates of 90% or better. 

The value of cross-claim clinical review

Cross-claim clinical review incorporates a member-centric approach that enables clinicians to review multiple claims across multiple providers at many points on a member’s healthcare continuum. Combining machine learning algorithms and clinical expertise can enable payment accuracy determinations without a medical record, decreasing provider abrasion and allowing for reviews even when providers limit records requests. Leveraging the outpatient and professional history of the patient in lieu of the medical record, experts can then conduct the initial review of the inpatient claim. Cotiviti data suggests that cross-claim clinical review can raise the medical cost savings potential of our own DRG review by 12–15%. 

Coordination of benefits: Keeping members in mind

Coordination of benefits (COB) requires health plans to navigate significant complexities. The order of benefit determination rules rely on an ever-changing member landscape that is as variable and unique as the members themselves. It can be easy, therefore, to forget to put the claims lifecycle in context against the actual member experience—getting a new job, getting married or divorced, starting a family, or retirement. These are just a few life events relevant to COB that should be considered during the claims adjudication and payment process.

While there is no simple, single solution to simplifying COB, designing a robust COB process that considers the entire member experience is a significant step forward. Why? Because it can:

• Help capture an additional 30% medical cost savings beyond internal teams and vendors
• Set the stage for early intervention where possible—assessing COB before a claim is paid, or even before it is received or treatment is rendered
• Provide the opportunity to integrate prospective and retrospective payment integrity processes into a streamlined process with varying intervention points
• Improve the overall member experience, limit provider abrasion, and accelerate speed to value

Identifying COB members for review

While identifying members in need of a COB review can be somewhat daunting, plans can start with the data on hand. Entitlement and eligibility information from CMS and the Council for Affordable Quality Healthcare (CAQH) can provide some valuable data points to fuel your investigation. Machine learning algorithms can also speed up this process, helping find members with both dual entitlement and other primary coverage.

A word of caution: while these data sources can be extremely valuable, these information repositories are not standalone solutions. Rather, they can serve as an instrument in your broader COB program and should be used in conjunction with other tools and strategies. For populations and data points outside of available in-house assets, a rich COB validation plan goes back to the member lifecycle, reviewing members that present with specific data points and events that tie to COB relevant life events.

For example, let’s take a family with two parents and three dependent children. The eldest dependent child is turning 26 and will no longer be eligible for coverage under their parents as a dependent. It doesn’t cost the parents anything additional to keep their oldest child on the plan. And there don’t appear to be any claims for the oldest child in the past four months after a period of continuous treatment. This trend could indicate that this young adult got a job that now offers health insurance, which overlaps with prior treatment, for which your health plan was the primary payer. It’s certainly worth exploring.

Finding the other insurance

The next thing to do is to identify the second insurance. Investigating whether someone has Medicare entitlement is more of a straightforward process as there is only one source to contact, whether through a CMS representative or a web-based portal.

Trying to identify a commercial payer or payers can be a little more challenging. First, plans must understand who the payers are in the state and/or region where the contract was issued, and then communicate with them for additional information. Another method to identify the other payer is to work with the provider when investigating gaps in coverage and routine claims. For example: Cotiviti observed a member that had been receiving routine injections. After a year, the claims for the provider stopped for four months and then picked up again. We spoke to the provider, who confirmed that during the lapse, they had been receiving payment from another payer. With this new information, we were able to work with the other payer to establish primacy order.

Determining the order of benefits

Once you’ve selected your member population and identified the other payers, the next step is to make the order of benefit determination. To complete this, examine the member’s data profile to ensure that the information is the most current needed to make the order of benefit determination. 

The employment status of the subscriber, for example, is one critical item to verify. You may need to perform an employment verification, as oftentimes working status updates are only captured during annual open enrollment time frames. Employment verifications can also be a great source for information pertaining to group size, which is another data element that may be needed to perform the order of benefits determination.

When reaching out to employers, you want to make sure you are asking the right questions and tailoring the outreach method to your employer group preferences (such as whether they prefer emails, spreadsheets, or even a shared data repository). 

The bottom line: by designing a COB process predicated on the lifecycle of your members, rather than just claims, you can address and resolve payment issues earlier—often before claims are received or paid.

Healthcare fraud, waste, and abuse: Combining prepay and postpay approaches to payment integrity

As fraud, waste, and abuse (FWA) continually evolves and new schemes emerge, health plans must create solid strategies for prevention. One of the best ways to create a full-scale defense against inappropriate payment is to combine prepay integrity and postpay integrity efforts. By integrating the two, plans benefit from a continual defense that proactively identifies outliers on the prepay end while simultaneously feeding new learnings from the postpay end. Read on to learn the value of this approach as well as a case study from a real application.

Integrating prepay and postpay approaches

Combining prepay and postpay approaches simultaneously ties the two together for a comprehensive, holistic provider story—and it’s the most effective way to optimize processes and results.

Marrying prepay and postpay efforts starts with sequencing in the prepay editing process and ends with the postpay FWA process. There are many benefits to this cyclical structure:

• Prepay editing process: Here, plans can examine current edit bypasses, edit circumventions, and edit interventions that shift provider behavior
• Prepay claim review: At this stage, analysis can uncover claim-level review pattern detection and modifier usage insights that could point to inappropriate billing
• Prepay FWA review: Getting more advanced, plans can benefit from provider-level review pattern detection and new scheme identification, decreasing losses to fraud over time
• Postpay FWA review: Finally, postpay FWA review provides the possibility for new automation opportunities, feeds a continued focus on egregious behavior, and enables continued fraud compliance

All of these steps feed into each other on a continuous loop, providing data that informs new steps going forward.

Prepay-postpay integration in action

Our case study focuses on a specific example from an out-of-network provider in genetic testing. 

Genetic testing can be problematic in the FWA space: it comes at a significant cost, it’s complex to audit, and FWA within this segment is on the rise. In fact, 15-40% of the genetic testing claims Cotiviti analyzes are found to be coded inaccurately. 

In this case, using outlier analysis to identify providers for audit, one was flagged for using an unlisted code. Since there are more than 400 CPT codes related to genetic testing, the choice to use an unlisted code was unusual. After digging into the data and conducting a peer comparison, the number of patients and corresponding tests seemed suspicious. The provider identified as a significant outlier among peers for:

• Using unlisted procedure codes
• Unbundling and duplicate billing, bypassing prepay edits/reviews
• Billing a large number of patients for genetic testing
• Billing genetic tests without corresponding supporting diagnosis

For example, the provider billed multiple Tier 2 molecular pathology procedures for the same patients on the same date of service (DOS). Billing patterns were also consistent across the patient population, showing a disregard for specific patients. The provider also appeared to be billing a high volume of unnecessary tests for each stage of the patient’s care. One patient might have chronic kidney disease, stage 3, unspecified, but numerous additional patients with varying diagnoses received the same combination of tests.

The case progression

An in-depth policy review helped determine the appropriateness of the claims, sparing more comprehensive audits and catching behavior in the beginning so there’s less pay-and-chase. By implementing prepay analytics upstream, we had a high volume of patterns tracked to be able to catch this provider as an outlier. Investigators started to see a steady increase in edited claims within a 12-month period. This type of pattern—up or down—warranted further scrutiny. Performing a postpay intervention made sense since there was a high amount of spend needed to be recovered, but the case for prepay intervention was also solid since the provider activity was spiking.

The provider was placed on prepay review for 20 genetic codes and simultaneously placed on postpay audit encompassing the previous two years. After requests for records went unanswered, the provider’s claims were denied due to lack of submissions and overpayment was initiated for postpay review. The provider appealed the postpay audit, but determinations were upheld on appeal, after which the provider became unresponsive. The prepay reviews continued and the provider began to comply with record requests, with claims offset for postpay audit and overpayments were identified.

The resulting investigation found a 100% error rate and a denial for all claims in question. Cotiviti has been able to recover more than $2 million in inappropriate overpayments for the client so far.

Flagging suspicious behavior

In this case, provider behavior was a contributing factor to the decision for deeper analysis. In the case of billing error, expected behaviors from the provider usually include a willingness to comply with requests, questions about the review, requests for peer-to-peer analysis, and appeals to findings. By contrast, this provider exhibited several noncompliant behaviors: withholding records, a willingness to forego payment, spikes in billing, changes to new code or billing patterns, the halt of billing altogether, and changing codes and modifiers. These unexpected behaviors can indicate a knowledge of wrongdoing.

The benefits of combining prepay and postpay integrity in FWA

By creating a continuous loop across prepay and postpay approaches to payment integrity, plans are better able to minimize healthcare FWA. Combining prepay and postpay approaches expedites provider responses and reduces administrative time. Simultaneous intervention of provider and claim-level reviews increases program effectiveness by changing a provider's behavior and mitigating future risk. Plans benefit from having one comprehensive analysis from a holistic review of suspect providers, and providers benefit from the plan identifying and addressing all billing issues at once.

Consider combining prepay and postpay to streamline the review process. Correct aberrant billing behavior through historical and current claim reviews and evaluate internal opportunities for updates to existing billing policies, putting new safeguards in place if needed. Get started implementing a proactive approach to waste and abuse prevention by minimizing unrecoverable financial losses while maximizing payment integrity. 

How to achieve better payment integrity value

By using the programs, solutions, and strategies outlined in this guide, you can increase savings, improve provider relations, and optimize member interactions with your organization.

Key lessons from this guide:

• Follow best practices when deploying a prepay claim editing solution
• Don’t underestimate the value of postpay data mining
• Improve DRG review with a targeted approach to clinical chart selection 
• Design a holistic COB process that considers the entire member experience
• Combing prepay and postpay approaches to fraud, waste, and abuse

We hope this guide empowers you to take the necessary steps towards transforming your payment integrity programs. 

Navigating new frontiers in payment integrity

As healthcare FWA schemes continue to evolve and cost the system as much as hundreds of billions of dollars per year, cutting-edge technologies and holistic approaches are an increasingly critical requirement. Watch as Cotiviti's Erin Rutzler, vice president of fraud, waste, and abuse, explains how Cotiviti is committed to greater value, innovation, and partnership in helping our clients better prevent payment integrity errors and FWA.

As health plan claim volumes grow amid cost increases and changing guidelines, the opportunity for inappropriate claims to slip through the cracks and get paid grows, too. Especially when plans use a siloed and disconnected approach to payment integrity.

Cotiviti’s Payment Accuracy suite helps you knock down those silos and perform beyond time pressure by shortening time-to-value from more than 90 days to less than five. With dynamic solutions that can work together to review 100% of all major claim types at the right intervention point, our clients can flexibly manage their MLR and unlock more incremental savings value, with less burden on provider partners and administrative teams. In fact, we’ve helped our clients achieve more than $8 billion in annual payment integrity savings through our scale, expertise, integration, and unparalleled accuracy.