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Combating Healthcare Insurance Fraud with Great Data

protect-insurancedata
Combating Healthcare Insurance Fraud with Great Data

The Washington Post reported this month that government officials arrested 243 medical insurance fraudsters who stole $712 million in false billings to Medicare in the largest crackdown on healthcare fraud ever. Insurance claims fraud continues to burden the pocketbooks of the average consumer in today’s healthcare industry. According to a study by CIC insurance on outpatient claims, fraud cases were estimated to be between 30-40% of all claims.  Since 2007, the government “strike force” responsible for cracking down on health-care fraud has charged more than 2,300 people accused of falsely billing Medicare for more than $7 billion. Despite advancements and increased investments in fraud prevention programs and technologies, the crimes are still rampant across the country.

According to the National Health Care Anti-Fraud Association, the most common types of healthcare insurance fraud include:

  • Billing for services that were never rendered-either by using genuine patient information
  • Billing for more expensive services or procedures than were actually provided or performed
  • Performing medically unnecessary services solely for the purpose of generating insurance payments
  • Misrepresenting non-covered treatments as medically necessary covered treatments for purposes of obtaining insurance payments
  • Falsifying a patient’s diagnosis to justify tests, surgeries or other procedures that aren’t medically necessary
  • Unbundling – billing each step of a procedure as if it were a separate procedure.
  • Billing a patient more than the co-pay amount for services that were prepaid or paid in full by the benefit plan under the terms of a managed care contract.

Combating insurance fraud is a major task for both private and public healthcare payers. According to the Wall St. Journal, the government recovered $3.3 billion in fiscal 2014 from individuals and companies that tried to defraud federal health programs, part of an effort by the Obama administration to improve enforcement and prevent abusive billing practices.  Investments in the latest fraud detection, predictive analytic, and business intelligence solutions promises to help in this ongoing battle. However, many will struggle to see value from those investments.  Decades of under-investment in data management technology, standards, and best practices pose significant risk to new and existing analytic applications, fraud surveillance, and compliance management solutions and to the overall healthcare industry. What are those data gaps? Here are some common ones we see today:

  • Required data is often locked away in proprietary databases in legacy systems and difficult to access.
  • Raw data from source systems are in formats and structures that require complex transformations
  • Data that is available is often only available month end or and the end of the day, not available for real-time monitoring and alerting
  • Serious data quality issues across systems due to manual data entry errors or data corruption due to the lack of sustainable data governance
  • Multiple sources of the truth, making it difficult to know which one to leverage to feed upstream fraud monitoring and analytic applications.

So where do you start?

Overcoming these data obstacles requires more than just throwing more bodies at these problems or settling on data integration, data quality, and data validation tools that come with your database vendor or free-ware from the internet. Today’s health insurance industry requires enterprise class solutions that allows you to:

  • Access, standardize, profiled, cleansed, and deliver trusted and timely data to operational and analytical applications regardless of data type, volume, to any application regardless whether it is in the cloud, on-premise, or to your mobile device.
  • Provides a single source of unique and related business reference and master data including patient, physician, location, and other critical information that all systems can leverage and trust.
  • Where metadata is integrated both at a technical and business level and data quality management happens upstream vs. at the end by business users, not developers.
  • Where sensitive information is identified and protected from unauthorized access to comply with local data privacy laws and avoid reputation-damaging data breaches
  • Where one platform can serve the data needs of all business groups and projects, that allow developers, data stewards, and business users to collaborate and govern data as a business asset to help your business scale with the growing demands of data.

How Ready are You? Click here to learn more about Informatica’s Healthcare Solutions

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