The Past:
It was reported in 2010 that, when
it comes to government fraud, healthcare has topped defense. Since that time Strike Force prosecutors have filed more than 963 cases
charging more than 2,097 defendants who collectively billed the Medicare
program more than $6.5 billion; 1,443 defendants pleaded guilty and 191 others
were convicted in jury trials; and 1,197 defendants were sentenced to
imprisonment for an average term of approximately 47 months.
Recent headlines:
June 2015 - National Medicare Fraud Takedown Results in
Charges Against 243 Individuals for Approximately $712 Million in False Billing
– Click
here
June 2016 - 300 Charged In Largest Takedown Of Medicare,
Medicaid Fraud In U.S. History – Click here
While this is great progress, the Government Accountability Office, has called for
"fundamental improvements" to curb overbilling by the health plans,
which are paying more than $160 billion annually. The GAO also said that the
Centers for Medicare and Medicare Services have spent about $117 million on
these audits, while, so far, recouping just $14 million. As reported in NPR,
CMS officials counter that the mere threat of audits has caused health plans to
voluntarily return approximately $650 million in overpayments – and that
upcoming audits will recover tens of millions more.
This raises 2 questions:
1.
Why are
these audits so expensive? and
2.
What can
be done to make these effective to rout out fraud?
Healthcare, while maturing
in technology adoption, is still manual with processes that are steeped in
historic burden. This makes the audit process very manual and very expensive.
The Present:
The largest fraud takedown
in U.S. history is clear evidence that data is playing a big role in
government. It is a testament to the Office of Inspector General’s (OIG) continued enhancement of data analysis capabilities
for detecting health care fraud, including tools that allow for complex data
analysis. Health and Human Service (HHS) OIG continues to use data
analysis, predictive analytics, trend evaluation, and modeling approaches to
better analyze and target oversight of HHS programs. CMS uses the Fraud Prevention System (FPS) on all
Medicare fee-for-service claims on a streaming, national basis. Similar
to the fraud detection technology used by credit card companies, FPS applies
predictive analytics to claims before making payments in order to identify
aberrant and suspicious billing patterns.
The Future:
There needs to be a
technology enabled framework to fight fraud, that allows for analyzing
historic and real-time transactional data, creates “situational awareness”,
detect fraudulent patterns and prevent fraud. Rather than creating pointed, yet
disjointed, analytics solutions that do transaction by transaction analysis, Real-time
Fraud Prevention and Detection (RFPD) should be thought of as a platform upon
which organizations can build analytics and most importantly let loose some of
the advancements in Machine Learning and AI. @IBM, @Microsoft and @AWS are all
leading the ML revolution but creating meaningful long term investments are few
and far between.
In conclusion, we have a clearly identified need - Medicare, Medicaid and other healthcare related fraud. We also have CMS and the DoJ serious on cracking down these frauds. At this point, it is critical to make the right investments in technology that will cast a wider net to catch a lot more of these frauds. Applying a well thought out platform and framework that compliments state-of-the-art fraud detection technology will only add to the efficiency and effectiveness of fighting health care fraud.
In conclusion, we have a clearly identified need - Medicare, Medicaid and other healthcare related fraud. We also have CMS and the DoJ serious on cracking down these frauds. At this point, it is critical to make the right investments in technology that will cast a wider net to catch a lot more of these frauds. Applying a well thought out platform and framework that compliments state-of-the-art fraud detection technology will only add to the efficiency and effectiveness of fighting health care fraud.
