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Preventing Provider Fraud through Health IT, Data Analytics

Payers that want to improve their ability to detect and react to provider fraud must invest in health IT and data analytics solutions to flag criminal activity.

Healthcare fraud is an industry-wide problem can impact a payer’s ability to protect their revenue streams and maintain financial integrity.

Fraud costs the nation’s healthcare payers almost $68 billion annually. Between 3 and 10 percent of the country’s $3 trillion in annual spending is related to fraud, experts believe.  

Provider healthcare fraud can create a string of legal and financial implications for payers that can take months or years to resolve.  Many fraud schemes rack up tens of millions in improper payments, which can pose serious problems for commercial entities.

For example, an internal fraud investigator helped co-conspirators defraud Anthem and other insurance companies of $20 million by using CPT codes to falsify claims submissions.

In a separate incident, federal investigators found a BlueCross BlueShield company in Miami was falsely billed for $10 million through a provider scheme to steal payments.

Payers need to be able to identify provider behaviors that indicate fraud with data analytics, health IT tools, and organization-wide strategies.

Indications of potential provider fraud

Common behaviors that indicate fraud activity include inappropriate billing and provider kickbacks schemes, according to data gathered by the Government Accountability Office (GAO) and the Office of the Inspector General (OIG).

Billing for services not performed, or performing services that are not medically necessary, are among the most common fraudulent activities. In 2016, these cases accounted for 46 percent of provider fraud cases, the highest percentage of any category of fraud scheme.   

Providers also completely falsify claims by using aliases and false identities to establish new revenue channels. In these schemes, providers illegally bill using the credentials of a physician licensed for certain service reimbursements. Falsified claims activity accounted for 25.5 percent of provider fraud cases.

Kickback schemes are also a popular healthcare fraud scheme for providers. Many providers will try to use bribery and financial incentives to redirect patients to seek services from their practices. These incentives may be given to patients themselves, but may also be paid to other providers who then steer referrals in a particular direction.

Provider kickback schemes accounted for nearly 20 percent of provider fraud activity.

Less common schemes include prescribing medically unnecessary medication and upcoding for expensive, unnecessary services.

Unnecessary prescriptions accounted for 10 percent of fraud schemes in 2016 and can lead to medical diversion, which contributes to patient opioid dependence.  Upcoding claims only accounted for 2 percent of all provider fraud activities.

How can data analytics help?

Payers that want to calculate their level of risk for provider fraud, or reduce fraudulent billing rates, should look to technology solutions as a first line of defense.

Payers need analytics platforms and visualization dashboards to detect patterns in provider fraud, visualize fraud activity to determine the prevalence of fraud, and help audit claims information.

Federal leaders have already take steps to implement analytics platforms. Last year, OIG requested stakeholder input for onboarding a data analytics solution that can visualize data and inform OIG officials of anomalies in datasets. A similar fraud prevention partnership from HHS, CMS, and the VA aims to leverage data analytics to detect and deter provider fraud.

Payers should look for platforms that visualize data in an informative way, develop insights using financial big data, and support predictive analytics capabilities.

Organizations can use data visualization tools in order to accurately interpret data and avoid confusion when developing conclusions from large datasets.

Healthcare payers and organizations need financial big data analytics to identify opportunities to identify waste and fraud across large care networks.

Developing financial big data analytics competencies are a struggle for 95 percent of healthcare CFOs because analytics investments require significant monetary and planning resources. Payers that want to scale big data operations for fraud prevention should make informed analytics investments by researching which vendors or solutions have the most expertise in fraud prevention.

A predictive analytics strategy can help payers determine which providers have a history of fraud activity and which provider behaviors likely indicate increased fraud risks. Predictive analytics is the practice of using data, algorithms, and available information to determine what activities are likely to happen based on historical analyses.

Just under 90 percent of payers are advancing their big data and predictive analytics capabilities in order to manage their overall healthcare costs, identify fraud, and maintain profitability.

Payers need both visualization and predictive analytics tools to learn about providers with history of fraud and abuse, patterns related to overpaid claims, and if fraud-centric behaviors are emerging within provider organizations.

Developing fraud detection and related fraud prevention strategies

Commercial payers such as Anthem, Humana, and UMPC Health Plan have developed strategies to combat fraud and deter providers from engaging in healthcare fraud.

Staffing an investigation team is critically important for payers that want to effectively limit the impact of fraud on their financial operations.

A Special Investigations Unit (SIU) should employ a mix of individuals that possess specialized skill sets to detect provider fraud.

Professionals that have a coding background can help the team understand if providers are billing for the appropriate services. Legal and criminal experts can then explain if improper billing practices are simply human error or malicious in nature. SIUs also need analytics skills to inform clinical and legal staffers on historical and new billing patterns.

Ultimately, a SIU needs to be collaborative in order to effectively deter fraud, according to Ralph Carpenter, the head of Aetna’s SIU.

“Over the years healthcare fraud schemes have become more and more complex,” Carpenter explained. “We use many tools to fight this fraud, but our collaborative efforts with our legal team and law enforcement are the key to our success. We would not be making the impact we are making without these critical resources.”

The SIU must also accurately benchmark and report the prevalence of fraud within the organization.

Provider fraud metrics help SIUs know if they are effectively reducing fraud. Important metrics include:

  • Number of new fraud cases and referrals
  • Fraud case by scheme type (false billing, upcoding, etc.)
  • Fraud case priority (high, medium, or low) based on financial risks/implications
  • Number of open fraud cases compared to closed fraud cases
  • Recovery amounts per closed fraud case

Payers and their SIU teams also need metrics to record provider activity that correlates to healthcare fraud. For example, SIUs could track the number of office visits compared to diagnoses and billing volume to see if providers are billing payers for redundant or wasteful services.

Payers should also develop educational resources and digital landing pages to help consumers report suspected fraud. Provider fraud schemes sometimes exploit the patient, meaning that informed consumers could act as a useful resource in preventing fraud.

Anthem’s Medicaid customers can report on fraud and explain which members or providers are participating in suspicious activity.

UnitedHealthcare offers a similar portal that educates members on the components of healthcare fraud. Members can then use a tool called EthicsPoint to detail potential fraud activities from providers, pharmacists, and other members.

Private payers can also benefit by collaborating with law enforcement agencies and regulatory groups to establish industry-standard fraud prevention protocols.

The National Health Care Anti-Fraud Association (NHCAA) is a private-public partnership that allow private payers and federal agencies to share information and best practices about healthcare fraud prevention.

In 2017, the NHCAA served 90 member organizations and 134 law enforcement liaison groups, including new members such as BlueCross BlueShield of North Dakota, Washington state’s Medicaid Fraud Control Unit, and the Louisiana Department of Health.

Combating fraud allows payers to maintain positive revenues, protect consumers from overbilling and increased premiums, and ensure that financial assets are secure from criminal activity. Payers that successfully support their fraud prevention activities limit the fiscal damages from fraud and maintain the integrity of reimbursement operations.

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