COVID-19 exposed many weaknesses in our healthcare system and exacerbated fraud, waste and abuse. As the federal government waived restrictions around various reimbursements for Medicare patients as well as encouraged plans to be more lenient around prior authorization and early refills, abusive and fraudulent actors quickly adapted, and health plans are among the primary victims.
Payers must recognize that healthcare waste and fraud impact both financial and care integrity. These problems waste valuable resources, hinder appropriate payment of claims, and put patients’ health at risk through unnecessary care and misutilization.
During the pandemic, we’re seeing a rise in suspicious billings for care. Some relate to cost-sharing waivers for COVID-19 testing or treatment. Expanded access to certain telehealth services and levels of care, bypass of certain diagnoses, relaxed restrictions around delivery of prescription drugs and temporary removal of prior authorization requirements and prescription refill limits also present bad actors with an opportunity to exploit the system.
As a result, the measures taken to support access to care at a time when in-person resources are overtaxed appear to have led to an uptick in billing for unnecessary services, upcoding and even services that were never rendered. This is on top of email and online phishing schemes, with cybercriminals sending emails that appear to be from business partners—such as an invoice for personal protective equipment—which unleash malware attacks once they are opened.
It is not yet clear how much money health plans have lost to fraud, waste and abuse schemes during the pandemic—and financial losses resulting from healthcare fraud were high even before the pandemic, totaling nearly $300 billion annually.
At a time when claims are increasingly complex and resources are strained, health plans need a data-driven defense to prevent fraudsters from taking advantage of the system. Here are three ways health plans can better protect themselves from fraud, waste and abuse during COVID-19.
Monitor utilization patterns for COVID-related testing and treatment. While investigations around fraud, waste and abuse take time to unfold, data captured during the pandemic point to trends in fraudulent activity. These include upcoding, unbundling of services and billing for in-person visits in areas where the likelihood of a face-to-face visit was extremely low, such as in New York during the surge in coronavirus cases last spring. Codes related to coronavirus testing—such as HCPCS codes U0001 and U0002 and CPT code 87635—are especially ripe for abuse because of the volume of claims submitted that feature these codes.
Monitoring utilization patterns for COVID-related codes and building edits into your system that flag suspect claims for review, such as add-on tests in conjunction with coronavirus testing, can help to provide defensive cover. For example, a trend analysis by the U.S. Department of Health and Human Services points to schemes such as billing for respiratory pathogen panel (RPP) tests and even allergy tests or genetic tests in addition to COVID-19 testing. By applying algorithms that automatically flag suspect testing claims such as these for review by nurses and coding experts, health plans can support accurate payment determination in near-real time. This avoids costly overpayments as well as claim processing delays.
Look for spikes in facility claims and a rise in certain diagnoses and encounter code combinations. Health plans should closely scrutinize claims from organizations and physicians that demonstrated a tendency toward suspicious billing before the pandemic as well as those that exhibit unusual patterns of billing activity. Such patterns include a rise in facility claims, such as rehabilitation facilities or nursing homes owned by a health system; telehealth evaluation and management (E&M) overcoding, such as telehealth claims coded at E&M levels 4 and 5; and encounter code combinations where a COVID-19 diagnosis may have been used to upcode or misrepresent services. They also include scenarios when claims are submitted for a specific provider potentially working more than 24 hours in a single day.
Artificial intelligence (AI) is increasingly being used to spot suspicious activity such as this excessive billing and instances where simple encounters have been coded to appear more complex. Both machine learning and predictive analytics demonstrate strong potential for health plans to stop improper payment before claims are paid. Currently, the Centers for Medicare & Medicaid Services is exploring the use of AI—including machine learning—to boost payment integrity, citing its ability to perform rapid, seamless and highly accurate claims review.
Create rules and scoring that can automatically detect potential fraud schemes. This involves collecting data around utilization, financial profiles of providers and documented high-impact schemes and then analyzing the data to create an “index of suspicion” for each provider. Such analyses identify providers with the highest probability of fraud, waste and abuse activity. It also detects patterns of abuse by specific providers and the dollars at risk.
Leading health plans are developing logic-based rules for specific types of claims as well as user-defined rules that empower plans to monitor procedure codes, modifiers, providers and members prospectively. These initiatives quickly identify claims tied to unusual patterns in utilization as well as coding mismatches and questionable billing practices. Machine learning tools apply retrospective learnings prospectively, strengthening a plan’s fraud prevention efforts over time. The most effective approaches lower false-positive rates, providing an extra layer of assurance. Some plans choose to apply rules and scoring to specific populations, such as Managed Medicaid.
A Data-Smart Approach to Fraud Prevention
Going on offense against fraud, waste and abuse during COVID-19 gives health plans their best chance of protecting reimbursement and care quality. Health plans should examine opportunities to shore up capabilities for prospective claim review to prevent improper payment before it occurs.
Payers must leverage intelligent analytics and insights to avoid post-payment resolution, which significantly increases time and effort and can lead to provider abrasion. This approach strengthens payment integrity while mitigating the financial impact of COVID-19.