CMS fraud prevention efforts save $42 billion
Advanced analytics, enforcement agencies aid prevention of erroneous payments.
The Centers for Medicare and Medicaid Services has embraced a multifaceted, proactive approach to preventing fraud, using a heavy investment in analytics and enforcement agency resources to save $42 billion in fiscal years 2013 and 2014.
CMS highlighted the importance of the savings in preventing fraud in order to ensure sustainability of the Medicare program and making sure beneficiaries have future access to care.
In CMS’ annual report to Congress on the effectiveness of the Recovery Audit Program—a strategy to combat fraud, waste and abuse at a federal level—that was released last week, the agency reported $24.8 billion of the $42 billion recovered came from prepayment review that employed advanced analytics.
By employing this tactic to head off questionable payments in advance, rather than a “pay-and-chase” method, program integrity contactors are able to flag potential cases of fraud through proactive data analysis before payments are made.
The Fraud Prevention System applies predictive algorithms and advanced analytics against Medicare fee-for-service claims.
Contractors found 12.7 percent of Medicare fee for service claims in FY 2014 were set at an improper payment rate, up from 10.1 percent in FY 2013. When FPS predictive models identify egregious, suspect or aberrant activity, the system automatically generates and prioritizes leads for further review and investigation, which are primarily used by Zone Program Integrity Contractors, according to the report.
The system uses data sets from called-in tips, the Fraud Investigative Database, the Compromised Numbers Checklist and nationwide claims, among other sources, which are held in the Integrated Data Repository. Analysts use historical claims from the IDR to analyze patterns and develop models for the FPS, which in turn screens the aggregated information.
In FY 2013, recovery auditors conducted prepayment reviews on claims that historically result in high rates of improper payments, according to the report. Seven states—California, Florida, Illinois, Louisiana, Michigan, New York and Texas—had high incidences of fraud and improper payments, while four states—Missouri, North Carolina, Ohio and Pennsylvania—had high claims volumes of short inpatient hospital stays.
Despite large success with the program, CMS will not systematically expand predictive analytics technology beyond Medicare to all Medicaid and Children's Health Insurance Program claims; in the report, CMS notes it is not cost effective for every state to adopt FPS.
CMS highlighted the importance of the savings in preventing fraud in order to ensure sustainability of the Medicare program and making sure beneficiaries have future access to care.
In CMS’ annual report to Congress on the effectiveness of the Recovery Audit Program—a strategy to combat fraud, waste and abuse at a federal level—that was released last week, the agency reported $24.8 billion of the $42 billion recovered came from prepayment review that employed advanced analytics.
By employing this tactic to head off questionable payments in advance, rather than a “pay-and-chase” method, program integrity contactors are able to flag potential cases of fraud through proactive data analysis before payments are made.
The Fraud Prevention System applies predictive algorithms and advanced analytics against Medicare fee-for-service claims.
Contractors found 12.7 percent of Medicare fee for service claims in FY 2014 were set at an improper payment rate, up from 10.1 percent in FY 2013. When FPS predictive models identify egregious, suspect or aberrant activity, the system automatically generates and prioritizes leads for further review and investigation, which are primarily used by Zone Program Integrity Contractors, according to the report.The system uses data sets from called-in tips, the Fraud Investigative Database, the Compromised Numbers Checklist and nationwide claims, among other sources, which are held in the Integrated Data Repository. Analysts use historical claims from the IDR to analyze patterns and develop models for the FPS, which in turn screens the aggregated information.
In FY 2013, recovery auditors conducted prepayment reviews on claims that historically result in high rates of improper payments, according to the report. Seven states—California, Florida, Illinois, Louisiana, Michigan, New York and Texas—had high incidences of fraud and improper payments, while four states—Missouri, North Carolina, Ohio and Pennsylvania—had high claims volumes of short inpatient hospital stays.
Despite large success with the program, CMS will not systematically expand predictive analytics technology beyond Medicare to all Medicaid and Children's Health Insurance Program claims; in the report, CMS notes it is not cost effective for every state to adopt FPS.
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