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Letter to Dr. Peter Budetti, Deputy Administrator and Director of the Center for Program Integrity Centers for Medicare and Medicaid Services, The U.S. Department of Health and Human Services

Letter

By:
Date:
Location: Washington, DC

Today, Senate Federal Financial Management Subcommittee Chairman Tom Carper (D-Del.), Ranking Member Scott Brown (R-Mass.), and Senator Tom Coburn (R-Okla.) sent a letter to the Centers Medicare and Medicaid Services (CMS) requesting an outline of the agency's plans to properly implement the predictive analytics program designed to prevent waste, fraud, and abuse in Medicare and strengthen overall program integrity. CMS deployed predictive analytics technology in July of 2011 to review all of the Medicare fee-for-service claims and to comply with the Small Business Jobs Act of 2010.

In their letter to Dr. Peter Budetti, Deputy Administrator and Director of CMS's Center for Program Integrity, the Senators express concerns that the CMS may not have sufficient metrics and processes in place as part of a comprehensive plan to ensure the success of the predictive analytics technology in order to identify waste and fraud before payments are made. The Senators noted that without the establishment of oversight metrics, the success or failure of predictive analytics for Medicare claims will be difficult, if not impossible, to measure. The Senators also seek CMS's strategy for appropriate responses to potential or identified improper payments and fraud. The Government Accountability Office (GAO) has placed Medicare on its list of "high risk" programs since 1990.

"In the absence of established and consistent measures designed to track the operation of predictive analytics, we are highly concerned that the Centers for Medicare and Medicaid Services and Congress will be unable to properly oversee this important program," wrote the Senators. "We believe it should be a top priority of the Centers for Medicare and Medicaid Services to ensure taxpayer dollars are not used to pay providers or suppliers in the Medicare program who are engaged in fraudulent schemes or criminal activities. As members of the Senate Federal Financial Management Subcommittee overseeing federal spending and improper payments, we have a duty to ensure taxpayer dollars, including those for program integrity functions, are carefully stewarded and spent in an effective manner. We believe the correct implementation of predictive analytics technology could be an important step forward in saving taxpayer dollars."

A copy of the letter follows:

December 20, 2011

Dr. Peter Budetti
Deputy Administrator and Director
Center for Program Integrity
Centers for Medicare and Medicaid Services
The U.S. Department of Health and Human Services
200 Independence Avenue, S.W.
Washington, D.C. 20201

Dear Dr. Budetti:

We are writing to outline some important concerns regarding the Centers for Medicare and Medicaid Services (CMS) implementation of the predictive analytics program designed to prevent waste, fraud and abuse in Medicare. As you announced publicly in July of this year, CMS deployed predictive analytics technology to review all of the Medicare fee-for-service claims. We applaud the work of CMS to implement predictive analytics technology nationwide this summer, and meet the congressionally-required deadlines under the Small Business Jobs Act of 2010. The adoption and correct use of this technology has a great potential to curb waste and fraud.

However, we are concerned CMS may not have sufficient metrics and processes in place to ensure the success of the predictive analytics technology. As is often said, one cannot manage what one cannot measure. Earlier this year, during a July 12th hearing of the Senate Federal Financial Management Subcommittee, you acknowledged that CMS did not yet have metrics in place to monitor the program, nor was there a timeline to establish such metrics.

In the absence of established and consistent measures designed to track the operation of predictive analytics, we are highly concerned that CMS and Congress will be unable to properly oversee this important program. We believe the question of appropriate metrics and processes is crucial for two reasons.

First, we believe it should be a top priority of CMS to ensure taxpayer dollars are not used to pay providers or suppliers in the Medicare program who are engaged in fraudulent schemes or criminal activities. Medicare provides health coverage for roughly 47 million Americans at an annual cost of more than $520 billion. Yet the Government Accountability Office designated Medicare a "high risk" program back in 1990, in part because of its susceptibility to waste, fraud and abuse. In fiscal year 2010 alone, Medicare made nearly $48 billion in improper payments. We were encouraged to learn that the recent data for fiscal year 2011 shows a small drop in the level of improper payments, but we believe that much more work needs to be done to identify, recover and prevent improper payments.

Second, Congress allocated $100 million for predictive modeling, and the initial contract allocation alone is about $77 million. As members of the Senate Federal Financial Management Subcommittee overseeing

federal spending and improper payments, we have a duty to ensure taxpayer dollars, including those for program integrity functions, are carefully stewarded and spent in an effective manner.

We believe the correct implementation of predictive analytics technology could be an important step forward in saving taxpayer dollars. However, based on the information and briefings provided by CMS to our staff, we remain concerned that there is not a comprehensive plan that includes the establishment of the required metrics to ensure the success of the predictive analytics technologies and processes. Without the establishment of performance and oversight metrics, the successes and shortcomings of predictive analytics will be difficult, if not impossible, to measure. Moreover, we are also concerned that there is not yet in place complete strategies, procedures and staffing for appropriately investigating, stopping and otherwise responding to potential or actual identified improper payments and fraud.

Now that the predictive analytics technology and processes have been in place for nearly six months, we request that CMS respond to the questions outlined below.

1. When will CMS have in place metrics for determining the relative successes or failures in operating predictive analytics?

2. When will CMS have in place a complete system for stopping claims before they are paid that are determined to be improper or for which there is credible evidence of fraud?

3. What amount and number of recoveries has CMS made directly related to the predictive analytics technologies?

4. What amount and number of losses has CMS prevented due to the predictive analytics technologies?

5. What changes in provider and supplier behaviors, if any, has CMS measured due to the implementation of predictive analytics technologies?

6. What is the process CMS uses when a suspect claim is identified, including the referral to contractors, the Department of Health and Humans Services Office of Inspector General (HHS OIG), or other entities for further investigation? How many such referrals have been made, and what is the total value of the associated claims?

7. Has CMS identified suspected overuse of timed codes, that is, providers or suppliers billing for more services in a day than is humanly possible? If so, how many and for what total value of the associated claims? If not, why or why not?

8. Has CMS suspended payments for any providers or suppliers based on the use of predictive analytics technologies? If so, how many providers, for what categories of providers, and for what total value of associated claims?

9. Has CMS referred any cases to the HHS OIG or other entities based on the use of predictive analytics technologies? If so, how many and for what total value of associated claims?

10. Has CMS excluded providers or suppliers from billing Medicare based on the predictive analytics technologies? If so, how many?

We remain committed to working with CMS to ensure the success of the predictive analytics program, and other important steps to strengthen program integrity. We look forward to hearing your response.

Sincerely,

Tom Carper, Chairman
Subcommittee on Federal Financial Management, Government Information, Federal Services, and International Security

Scott Brown, Ranking Member
Subcommittee on Federal Financial Management, Government Information, Federal Services, and International Security

Tom Coburn, M.D.
United States Senator


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