The number of Medicare audits is increasing. In the last 5 years, audits have grown by 936%. As reported previously in RACmonitor, this increase is overwhelming the appeals system. Less than three percent (3%) of appeal decisions are given on time within the statutory framework.
It is peculiar that the number of audits has grown rapidly, but without a corresponding growth in the number of employees for RACs. How can this be? Have the RAC workers become more than 900% more efficient? Well, in a way they have. They have learned to harness the power of Big Data.
Since 1986, the world’s ability to store digital data has grown from 0.02 exabytes to 500 exabytes today. An exabyte is one quintillion bytes or 10e+18 bytes. Every day the equivalent 30,000 Library of Congresses is put into storage. Lots of data.
Auditing by RACs has morphed into using computerized techniques to pick targets for audits. An entire industry has grown up that specializes in processing Medicare claims data and finding “sweet spots” on which the RACs may focus their attention. In a recent audit, the provider was told that a “Focused Provider Analysis Report” had been obtained from a subcontractor. Based on that report, the auditor was able to target the provider.
A number of hospitals have been hit with a slew of Diagnosis-Related Group (DRG) downgrades from Internal Hospital RAC Teams camping out in their offices, continually combing through their claims data. DRG is a system that classifies any inpatient stay into groups for purposes of payment.
The question then becomes: How is this work done? How is so much data analyzed? Obviously these audits are not manual. They are Cyber Audits. But how?
An examination of patent data begins to shed light on the answer. For example, Optum, Inc. of Minnesota (associated with United Healthcare) has applied for a patent on “Computer implemented systems and methods of health care claim analysis.” (Application Number 14/449,461, Feb. 5, 2015) These are complex processes, but what they do is analyze claims based on a Diagnosis-Related Group (DRG).
The information system envisaged in this patent appears to be specifically designed to downgrade codes. It works by running a simulation that switches out billed codes with cheaper codes, and then measures if the resulting code configuration is within the statistical range averaged from other claims.
If it is, then the DRG can be down-coded so that the revenue for the hospital correspondingly is reduced. This same algorithm can be applied to hundreds of thousands of claims in only minutes. And the same algorithm can be adjusted to work with different DRGs. This is only one of many patents in this area.
When this happens, the hospital may face many thousands of down-graded claims. If it doesn’t like it, then it must appeal.
Medicare Audits as Asymmetric “Warfare”
Here, there is a severe danger for the hospital. The problem is that the cost of the RAC running the audit is thousands of time less expensive that what the hospital must spend to refute the DRG coding downgrade.
This is the nature of asymmetric warfare. In military terms, the cost of your enemy’s offense is always much smaller than the cost of your defense. That is why guerrilla warfare is successful against nation states. That is why the Soviet Union and United States decided to stop building Anti-Ballistic Missile (ABM) systems — the cost of defense is disproportionately greater than the cost of offense.
Hospitals face the same problem. Their claims data files are a giant forest in which these big data algorithms can wander around down-coding and picking up a substantial revenue stream for the auditor.
By using Artificial Intelligence (advanced statistical) methods of reviewing Medicare claims, the RACs can bombard hospitals with so many DRG downgrades (or other claim rejections) that it quickly will overwhelm the provider’s defenses.
We should note that the use of these algorithms is not really an “audit”. It is a statistical analysis, but not done by any doctor or health care professional. The algorithm could just as well be counting how many bags of potato chips are sold with cans of beer. It doesn’t care.
If the patient is not an average patient, and the disease is not an average disease, and the treatment is not an average treatment, and if everything else is not “average”, then the algorithm will try to throw out the claim for the hospital to defend. This has everything to do with statistics and correlation of variables and very little to do with understanding whether the patient was treated properly.
And that is the essence of the problem with Big Data audits. They are not what they say they are because they substitute mathematical algorithms for medical judgment.
In Part II we will examine the changing appeals landscape and what Big Data will mean for defense against these audits. In Part III we will look at future scenarios for the auditing industry and the corresponding Public Policy agenda that will face lawmakers.
So we thought we would reproduce the ruling here, but with only the portions that deal specifically with statistical sampling and extrapolation.
Hospital Insurance and Supplementary Medical Insurance Benefits (Parts A and B) Use of Statistical Sampling to Project Overpayments to Providers and Suppliers
Purpose: HCFA and its Medicare contractors may use statistical sampling to project overpayments to providers and suppliers when claims are voluminous and reflect a pattern of erroneous billing or overutilization and when a case-by-case review is not administratively feasible.
. . . As result of a subsequent audit of the provider’s Medicare claims, the intermediary discovered a large number of bills for medically unnecessary services. . . . The cost of identifying and calculating each individual overpayment itself would constitute a substantial portion of the amount the intermediary might reasonably be expected to recover. . . .
The intermediary notified the provider that, because of the volume of records and the costs of retrieving and reviewing all records for the period as discussed above, it intended to project the overpayment by reviewing a statistically valid sample of beneficiary records and that if it were determined that the provider had been overpaid for the sample cases, it would project the results (again using statistically valid methods) to the entire population of cases from which the sample had been drawn. This would result in a statistically accurate estimate of the total amount the provider had been overpaid for services to these beneficiaries.
[Next are the complaint items filed by the health care provider.]
The provider objected to the intermediary’s use of sampling to project the overpayment on the following grounds:
1. There is no legal authority in the Medicare statute or regulations for HCFA or its intermediaries to determine overpayments by projecting the findings of a sample of specific claims onto a universe of unspecified beneficiaries and claims.
2. Section 1879 of the Social Security Act, 42 U.S.C. 1395pp, contemplates that medical necessity and custodial care coverage determinations will be made only by means of a case-by-case review.
3. When sampling is used, providers are not able to bill individual beneficiaries not in the sample group for the services determined to be noncovered.
4. Use of a sampling procedure violates the rights of providers to appeal adverse determinations.
5. The use of sampling and extrapolation to determine overpayments deprives the provider of due process.
(The succeeding presentation of our decision and supporting facts is applicable also to the use of sampling to project overpayments to suppliers (including physicians) whose claims are processed by Medicare carriers when 100 percent readjudication would be excessively costly or impractical.)
The Supreme Court has long recognized that the Federal Government possesses an inherent right to recover monies illegally or erroneously paid out. . . . The Government’s common law right of recoupment, and its corollary power of recovery by offset, are based on strong considerations of public policy. . . . The common law right to recover Federal funds has been specifically recognized as being fully applicable to the Medicare program. . . . Congress has affirmed the Government’s right to recover Medicare Trust Funds by reasonable means from those who have no right to retain them. . . .
[Next, the ruling makes the “administrative burden” argument.]
Since HCFA’s contractors process vast numbers of Medicare claims . . . A case-by-case review could require a significant diversion of staff from the ongoing claims process, and the cost of determining the amount of an overpayment would be prohibitively high unless a sampling method were used. . . .
We also do not believe that the statutory provisions limiting provider or beneficiary liability preclude the use of sampling.. . .
The use of sampling to determine overpayments for medically unnecessary services or custodial care does not deprive a provider of its right to bill those beneficiaries who knew or should have known that they were receiving these services. . . .
[There are also “public policy” used to justify sampling.]
As between the provider and the Government, strong considerations of public policy favor recovery.. . .
[Next, the famous shifting of the burden of proof is explained.]
Sampling does not deprive a provider of its rights to challenge the sample, nor of its rights to procedural due process. Sampling only creates a presumption of validity as to the amount of an overpayment which may be used as the basis for recoupment. The burden then shifts to the provider to take the next step. The provider could attack the statistical validity of the sample, or it could challenge the correctness of the determination in specific cases identified by the sample (including waiver of liability where medical necessity or custodial care is at issue). . . . If certain individual cases within the sample are determined to be decided erroneously, the amount of overpayment projected to the universe of claims can be modified. If the statistical basis upon which the projection was based is successfully challenged, the overpayment determination can be corrected.
The provisions of the statutes and regulations provide a constitutionally sufficient means by which the provider may challenge an overpayment determination. In cases of denials made through sampling which are based on medical necessity or custodial care, section 1879 of the Act, 42 U.S.C. 1395pp, permits the provider to assert the same appeal rights that an individual has under the statute when the individual does not exercise his rights to appeal. Under Part A, these rights include an opportunity for reconsideration (42 CFR 405.710- 405.716), an oral evidentiary hearing by an administrative law judge (42 CFR 405.720-405.722), Appeals Council review (42 CFR 405.701(c) and 405.724), and finally judicial review if the amount in controversy is $1,000 or more (42 CFR 405.730; 42 U.S.C. 139 5ff (b)(2)). In cases that do not involve medical necessity or custodial care, 42 CFR 405.370, et seq. sets out the applicable procedures through which current payments may be suspended (offset) to recover an overpayment under the Medicare program. . . .
In summary, the use of sampling is a reasonable and cost effective method of projecting overpayments under Medicare. It is not unfair to a provider or supplier to hold it accountable for the receipt of Medicare funds to which it is not entitled under the statute. . . .
Ruling: Accordingly, it is held that the use of statistical sampling to project an overpayment is consistent with the Government’s common law right to recover overpayments, the Medicare statute, and the Department’s regulations, and does not deny a provider or supplier due process. Neither the statute nor regulations require that a case-by-case review be conducted in order to determine that a provider or supplier has been overpaid and to determine the amount of overpayment.
Effective date: This Ruling is effective February 20, 1986.