Texas: $16,000,000 Extrapolation Reduced to $39,000 Because of Faulty Extrapolation – OIG Employee Fired – Investigation Reveals Massive Falsification of Data and Invalid Statistical Methodology
According to the Texas Dentists for Medicaid Reform (TDMR), “the new Health and Human Services Commission Inspector General Stuart Bowen, Jr. has been taking on and overhauling the agency’s use of statistical sampling and extrapolation. This is the most controversial tool that the agency had been using to demand multi-million dollar settlements from Medicaid providers under investigation.”
The seed value in the statistical tool “actually did not generate the stratified sample embedded in that tool”.
Investigators found a hidden spreadsheet with embedded macros that would over-write any “incorrect sample”.
The OIG falsified a sheet that stated the sample was created by the software tool.
After a detailed investigation, the OIG employee “admitted . . . that [he] falsified the sample” and “had not reviewed the sample before sending it”.
Weeding out some bad apples in Medicaid Claims Extrapolation who have overcharged dentists for years, the Human Services Commission Inspector General has instituted new extrapolation rules, and is settling older cases as well.
In previous blogs we have explained the importance of using Statistical Extrapolation to win your RAC or MIC appeals.
Here are the top five things to avoid in order to overturn the statistical extrapolation.
DO NOT Base your extrapolation argument on a sample size that is too small
Although it is true that in most cases, the sample size used is too small, this argument alone generally will not prevail in the appeal.
What often happens is that the trier of fact will simply verify if the evidence that the statistical methodology used was generally consistent with the Medicare Program Integrity Manual (MPIM).
There is an unfortunate passage in the MPIM which states that any sample size can be valid as long as the underlying methodology is sound.
And the unfortunate result is that the widespread use of poor and inadequate samples in the extrapolation often leads to results not in your favor.
DO NOT Accept print-outs instead of real electronic spreadsheets
It’s common for contractors to send print-outs with tables of data to back up their statistical work. Don’t accept them for the extrapolation.
Try to get the original electronic spreadsheet because this allows you to verify the statistical work, and to see the details of how it was done.
It also will allow you to run various tests to determine the quality of the work.
Always use the “best business record” rule to argue for the original sheets.
DO NOT Neglect to obtain the full universe file
Audit Contractors generally select a “frame” from the larger universe of all of your claims. From this “frame”, they will select their sample for analysis.
Without the entire universe file containing all claims you have filed, it’s impossible for you to run several important statistical tests that will help uncover any flaws in the contractor’s statistical work.
DO NOT Accept the argument that poor precision works in your favor for the extrapolation
Poor precision in statistics is a sign of bad work. It is often argued that poor precision works in favor of the provider because the lower side of the confidence interval is chosen for the over payment demand number.
Using a confidence interval to adjust for poor precision is not good statistics practice.
Insist that the contractor meet the Federal precision standards that were published in the Federal Register.
DO NOT Ignore all aspects of the extrapolation’s statistical methodology
The statistical work is much more than simply the sample taking and calculation of the extrapolation. ALL of it has to be checked.
In addition, there are a number of PIM rules that must be complied with. Check what was done against each and every one of the PIM rules and that they were followed in every detail.
Breaking a single PIM rule is often is overlooked, but if there are a substantial number of violations, then it helps build the case that the statistical work is not to be trusted and the appeal will be decided in your favor.
Winning Medicare Audit Appeals often depends on the RAC Statistical Extrapolation which determines how much you will owe in claims.
In this Guide, Barraclough LLC explains one of the more important aspects of the RAC review process: the RAC Statistical Extrapolation, which based on the review of a small number of billing claims, is applied to all of your claims for a number of years. Barraclough wants to remind you that it’s the extrapolation of the error rate of the claims that pushes the amounts so high.
Winning Medicare Audit Appeals
Barraclough’s Litigation Strategy is to show that the RAC extrapolation is incorrect. We disprove the validity of the statistics in your favor, so the amount you owe is either nothing or significantly less than originally asked for. This can mean that Winning the Medicare Appeal is a matter of looking at the numbers.
Medicare Audit Process Background
Medicare billing is investigated by subcontracted professional auditors. The Recovery Audit Contractor (RAC) program began in 2005. Medicare can and does investigate the medical billings of any practitioner who bills Medicare for services, including but not limited to: solo physicians, chiropractors, physical therapists, small or large medical practices, pharmacists, clinics or hospitals. This is referred to as the RAC review process.
RACs receive payment which is a percentage of what’s recovered for alleged billing errors. The remainder of the amount goes back to the Medicare Trust Fund.
Part 1: RAC Statistical Extrapolation is a Key Determinant of Amounts
RACs use statistical sampling to calculate the overpayment demand following an audit. While the use of statistical sampling for overpayment estimation is limited by statute, the auditor will examine a small percentage of claims, and then extrapolation can range from the tens of thousands into the millions, depending on the size of the entity being audited.
Significant problems occur because RACs use faulty statistical methods. When this happens, health care professionals will be forced, unfairly, into paying large refunds that they really do not owe.
The remedy for this is your own independent audit done by Barraclough’s experts.
How We Work:
Barraclough’s Litigation Strategy for Medicare Audit Appeal
Part 2: The Audit Notification
You’ve just received a notification that you are under investigation for Medicare billing claims. This is the first that you, the doctor or health facility, knows of the audit. An analysis of billing has taken place behind the scenes.
It’s unclear why you are being investigated. Perhaps it was a whistle-blower or an anonymous tip. But for the most part, audit targeting appears to occur as large data mining programs sift through the billions of claims in order to uncover allegedly suspicious billing patterns.
The next step in the RAC review process is a demand to see some of your patient records. When these are sent in, a team of auditors examine each record. Medicare rules in the strictest possible manner.
Many of your billing claims which are being examined in the RAC review process may be rejected because they were “not medically necessary.” Others may simply be a case of minor clerical errors in paperwork. We have yet to see a true fraud case.
But it is the case that any error, no matter how trivial, will be highlighted. It is not uncommon in the RAC review process for some rules to be applied incorrectly or for other rules appear suspect.
The result is that the auditor will come up with an “error rate” based on this sample of claims. If one-third of the claims have problems, then your stated RAC review error rate is 33%.
What’s critical to understand is that then the auditor takes that error rate and applies it to all of your claims for a number of years. This is why winning an Medicare Audit Appeal can be so difficult.
The result is a letter to you demanding return of one-third of all Medicare payments you have received over this entire period.
So, it’s not just the Medicare audit, it’s the extrapolation of the error rate of the claims that pushes the amounts so high. For many small practices and medium sized health facilities, like clinics, this is enough to bankrupt the entire business.
Part 3: Barraclough Litigation Strategy
Show that the RAC Extrapolation is Incorrect
Examining the RAC statistical work is the key; the goal is to disprove the validity of the statistics in your favor, so the amount you owe is either nothing or significantly less than originally asked for, i.e., just the amount on the original small sample of cases.
Barraclough statistical and medical experts prove where the Medicare audit is incorrect.
Because there is a defined window of opportunity to object to the extrapolation, you need to pursue this immediately after you receive the judgement. After that, you lose the right to ever appeal anything you have not mentioned before, such as these statistics.
That’s why, getting correct statistical extrapolation soon as possible is critical to winning your case.
In Barraclough’s many cases, we have examined a number of these demand letters, and looked carefully at the underlying statistical work. Thus far, we have yet to find even a single demand (statistical extrapolation) that used flawless statistics.
Examples of the problems we have uncovered include:
The contractor may use the wrong formulas for basic calculations.
The contractor may skip entire parts of the statistical procedure and “wing it” by making up crucial numbers.
The contractor may make complete ludicrous claims, such as that a statistical sample with no stratification was “actually stratified, but with only one stratum”.
There are other problems as well. The “explanation” to the doctor may be useless even though it’s full of lengthy statistical boilerplate, complete with a number of impenetrable formulas. In one case, the auditor even supplied a photocopy of a software manual as part of their justification.
Part 4: Reverse the Medicare Audit
Barraclough’s clients have had success in Medicare audit reversal because they have pushed back against these kinds of Medicare audit results.
Here are a few things you can do:
As soon as you receive notice of an audit, contact an attorney who specializes in responding to Medicare Audits.
Check to make sure they have specific and successful experience handling Medicare refund audits.
Don’t expect the Medicare auditor to be forthcoming in providing you data.
From the very beginning, insist on a complete statistical review of how all samples and calculations were made.
No matter what you do, don’t settle for boilerplate.
Make the auditor shows their work including every single calculation from beginning to end.
Make them give you the spreadsheets.
Challenge every single stage of the audit process from the initial targeting of your practice to the extrapolated refund demand.
Don’t take at face value anything written in your audit letter, especially the interpretation of the rules. Don’t expect your attorney or even the Judge to be able to understand the formulas. Instead, use a qualified statistical expert to review all materials.
With a successful statistical challenge, the extrapolation can be thrown out completely.
The Congress continues to try to fix Medicare’s arduous healthcare audit procedures, as the RAC audit process and healthcare providers continue to be locked into a claims remediation nightmare. The Audit and Appeal Fairness, Integrity, and Reforms in Medicare, or AFIRM, Act of 2015, was introduced on June 3, 2015.
Senator’s Wyden statement about the Finance Committee Markup of this bipartisan effort is that it “will streamline the appeals and audits process so cases are resolved quickly and at the earliest possible step.” The legislation provides for:
More HHS personnel resources pick up the pace in order “to keep up with the enormous increase in appeals.” The Office of Medicare Hearings and Appeals can currently adjudicate 77,000 appeals in a year, far below the 474,000 appeals OMHA received in 2014.
HHS can use its resources more efficiently and process more appeals because of a new track for lower-cost, less-complex cases to be considered by a different set of hearing officers than other cases.
Requiring CMS to better coordinate provider audits “to ensure the entire process is more transparent and efficient, including the creation of an independent Ombudsman position at CMS” in order to assist those considering appeals. Providers who consistently bill correctly are exempted for burdensome audits, as a reward for their business practices.
Although this markup provides some improvement by separating high value from low value cases, Barraclough LLC is dubious about the additional number of people on the CMS payroll to deal with the appeals backlog and the overall impact of the Audit and Appeals Ombudsman which has yet to be fully explained. RAC Audit Appeals would be better served with more data transparency, a change in RAC auditors contingency fee payments, and the quality of initial determinations.
For the full text of Senator Wyden’s statement, click here.
As the AFIRM legislation progress, Barraclough LLC will continue to analyze the impacts and make recommendations for the best course of action.
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.
So the question that arises is this: Are contractors free to employ any accuracy they wish in their work, or are there standards that have been suggested or published by the Federal Government?
As it turns out, there appears to be some guidance from two sources.
In the May 5, 2010, report by the Acting Administrator and Chief Operating Officer of the Centers for Medicare & Medicaid Services (CMS) On page 3 of that report, the section titled “Precision-level requirements” states:
“[Office of Management and Budget] OMBCircular A-123, Appendix C, states that Federal agencies must produce a statistically valid error estimate that meets precision levels of plus or minus 2.5 percentage points with a 90-percent confidence interval or plus or minus 3 percentage points with a 95-percent confidence interval.”
There is a note in the document: Under these assumptions, the minimum sample size needed to meet the precision requirements can be approximated by the following formula, which is used in the examples:
Where n is the required minimum sample size and P is the estimated percentage of improper payments (Note: This sample size formula is derived from Sampling of Populations: Methods and Applications (3rd edition); Levy, P. S. & Lemeshow, S. (1999); New York: John Wiley & Sons; at page 74. The constant 2.706 is 1.645 squared.
In the CMS-issued Federal Register, 72 Fed. Reg. 50490, 50495 (Aug. 31, 2007), the error estimate should meet precision levels of plus or minus 2.5 percentage points with a 90-percent confidence interval, and the State error estimates should meet precision levels of plus or minus 3 percentage points with a 95-percent confidence interval.”
So it appears that these standards, which are fairly good, have been twice promulgated by the Federal Government.
This is a case in which the extrapolation was thrown out.
Here, the Medicare Appeals Council agreed with the “determination that the sampling was sufficiently flawed to preclude calculation of an overpayment by extrapolation”.
Although the appellant had made a number of arguments attacking the statistical extrapolation, the MAC relied on two errors in throwing out the extrapolation:
“The errors are: 1) the PSC provided the independent statistical expert with sample data which assigned some claims to the wrong stratum; and 2) the PSC provided the independent expert with a second CD containing an Excel set of sample data with significant discrepancies from the first set of data, and the PSC was unable to clarify the discrepancies, to identify which set of data was applicable, or to explain the significance of the second set of data.”
This provides at least three check points when providing litigation support to a health care provider:
First, always have the statistical expert carefully check that all claims in any strata strictly fit the definition of the strata;
Second, look for any instance in which inconsistent records have been handed over by the contractor; and
Third, demand detailed explanations from the contractor for each and every inconsistency found in the data.
Unfortunately, it has been our experience at Barraclough that these arguments do not always result in an extrapolation being thrown out. Rulings are inconsistent with each other – sometimes this argument works, sometimes it does not.
It has been our experience at Barraclough that contractors almost always skip the step of taking a probe sample when calculating the required sample size. Even though they do this, they frequently rely on RAT-STATS to make the sample size calculations. The inputs into RAT-STATS requires the variation in the variable being estimated, that is, RAT-STATS requires as one of its crucial inputs the variation (e.g., the mean and standard deviation) of the overpayments (which is the variable being estimated). Since the contractors skip taking a probe sample, they plug the wrong data into the RAT-STATS program, and then make their calculation of sample size by using the variation of the payments instead of the underpayments. This almost always results in RAT-STATS claiming that a smaller sample size is adequate. In the MPIM, Chapter 3, Section 3.10.2, we see a sketch of what a “properly executed” sample design is. In includes:
(1) defining the universe, (2) [defining] the frame, (3) [specifying] the sampling units, (4) using proper randomization, (5) accurately measuring the variables of interest, and (5) using the correct formulas for estimation
It can be argued that taking a probe sample so as to be able to plug the correct (and required) data into the RAT-STATS program falls under the fifth category “accurately measuring the variables of interest”. It follows that if the probe sample is not taken, then according to the MPIM, proper procedures have not been used. Note: RAT-STATS is a free statistical software package that providers can download to assist in a claims review. The package, created by OIG in the late 1970s, is also the primary statistical tool for OIG‘s Office of Audit Services.
“Failure by the [contractor] to follow one or more of the requirements contained herein does not necessarily affect the validity of the statistical sampling that was conducted or the projection of the overpayment.
An appeal challenging the validity of the sampling methodology must be predicated on the actual statistical validity of the sample as drawn and conducted.
Failure by the [contractor] to follow one or more requirements . . . should not be construed as
necessarily affecting the validity of the statistical
sampling and/or the projection of the overpayment.”
The language quoted from the MPIM seems to indicate that no appeal may be based on the sampling methodology.
No matter how the contractor arrives at their sample, it does not seem to be reviewable.