Did you know that the Centers for Medicare and Medicaid
Services (CMS) uses predictive analytics to analyze all Medicare fee-for-service (FFS) claims?
This is done in part to detect claims that may be considered fraudulent.
The predictive analytics system utilizes algorithms and
models that will examine claims submitted to Medicare so as to determine if the
claims should be flagged for suspicious billing. Moreover, this is done in a
“real time” environment. This process is being incorporated by CMS into the
claims processing part of the equation.
This idea came about through the Section 4241 of the Small
Business Jobs Act of 2010 (SBJS) as it mandated that CMS implement a predictive
analytics system to analyze Medicare claims for areas at high risk of fraud.
This is a similar process to one credit card companies are currently doing in
the pre-payment arena.
As of June 30, 2011 CMS has been running all Medicare FFS
claims through this predictive modeling system. This process builds profiles on
providers, networks, billing patterns, and beneficiary utilization. The outcome
of this process is that CMS can now create risk scores to determine the
likelihood or fraud in the billing process. In addition, they can flag
potentially fraudulent claims and/or billing patterns.
The risk scores will clearly and quickly identify any
billing activity that is unusual and group them by providers, beneficiaries,
and networks with the highest risk scores. This system, a very high-tech
system, is not designed to replace the expertise or experienced analysts as the
analysts still review prioritized cases and history along with identifying any
innocuous billing and they will record this activity directly into the predictive
analytics program and the payment is released as usual. If an analyst finds any
activity that is fraudulent they will alert the CMS Center for Program
Integrity, MACs, or Zone Program Integrity Contractors to enact targeted
payment denials. When the alert involves egregious fraud, the billing
privileges of the provider will be revoked.
The risk scores alone to not initiate any administrative
action and the providers will not be able to appeal these risk scores.
Currently, CMS is not denying any claims based solely on the alerts generated
by this system. The predictive model is still being refined and they are
developing more advanced algorithms that line up more closely to the
complexities of medical treatment and billing.
With all of this said, CMS is dedicated to ensuring prompt
payment to the providers as this is a statutory requirement, but in urgent
circumstances CMS will leverage its authority to waive the prompt payment
process and conduct a more detailed review on the provider.
Overall, by enacting a predictive modeling system, CMS is
staying up with the times and doing its best to combat improper billing
practices and to protect the Medicare Trust Fund.
Submitted by Kevin (Michael) Harrington, Full-Time Faculty at SJC
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