The Famous HCFA Ruling 86-1 — Hospital Insurance and Supplementary Medical Insurance Benefits (Parts A and B) Use of Statistical Sampling to Project Overpayments to Providers and Suppliers

The HCFA Ruling 86-1 is one of the most frequently-quoted pieces of law.  For example, it is one of the key rulings in Chaves County Home Health Service, Inc., et al., v. Louis W. Sullivan, M.D. 931 F.2d 914 (April 26, 1991).

So we thought we would reproduce the ruling here, but with only the portions that deal specifically with statistical sampling and extrapolation.

HCFAR 86-1-1

MEDICARE PROGRAM

Hospital Insurance and Supplementary Medical Insurance Benefits (Parts A and B) Use of Statistical Sampling to Project Overpayments to Providers and Suppliers

HCFAR 86-1

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.

Original Medicare (Parts A and B Fee-For-Service) Appeals Process

There are five levels to the Medicare Appeals Process, and the timing appears to be ample for what is required.  Here is the amount of delay involved if you wait until the last minute:

120+180+60+60+60=480 days or 16 months.  However, it appears that most if not all cases take much longer than that, particularly as higher levels of appeals are confronted.

Original Medicare (Parts A and B Fee-For-Service) Appeals Process

Original Medicare (Parts A and B Fee-For-Service) Appeals Process

There is a detailed write-up by Elissa K. Moore, R. Brent Rawlings, and Jessica L. Smith of McGuireWoods here.  Title:  “A Primer on RAC Appeals“. Moore also is associated with the Annals of Health Law published at Loyola University Chicago School of Law.

Federal Precision Standards for Medicare and Medicaid Statistical Sampling and Extrapolations

As we have seen from other entries to this blog, Recovery Audit Contractors (RACs) operating under the Centers for Medicare & Medicaid ServicesRecovery Audit Program who are involved in conducting Medicare and Medicaid audits of health care providers have been granted an incredible bit of leeway in acceptable standards for their work.   It is not uncommon to see precision that is far more than +/- 20%, and even when the precision is as poor as +/- 49%, the Medicare Appeals Council (MAC) as well as Federal Courts will not throw out the extrapolation.

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.

Source One:

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 BudgetOMB Circular 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:

BLOG_ACCURACY_FORMULA.001Where 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.

Source Two:

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.

The question is:  Why are they routinely ignored by Administrative Law Judges (ALJs), and the Medicare Appeals Council (MAC)?

 

John Balko & Associates d/b/a Senior Healthcare Associates v. Kathleen Sebelius Secretary U.S. Department of Health and Human Services

John Balko & Associates operates Senior Healthcare Associates (SHA)and is located in Hermitage, Pennsylvania.    The company was audited and received a demand letter for approximately $680,000 dollars.  The case went through a number of appeals and eventually the Medicare Appeals Council (MAC) ruling was appealed for review by a Federal District Court.

This is a case filed April 30, 2012 in the United States District Court for the Western District of Pennsylvania.  (The PACER number is Case 2:12-cv-00572-AJS)  The case went through several stages prior to being appealed.  (See figure.)

BALKO_CHRONOLOGY.001

Source: Memorandum Opinion re: Parties’ Cross-Motions for Summary Judgment, files 12/28/2012, and Barraclough analysis.

A number of arguments were made that established clearly that the statistical work was faulty, and from a scientific point of view was completely invalid.

BALKO_ARGUMENTS_1.001BALKO_ARGUMENTS_2.001Arthur J. Schwab the United States District Judge wrote in his opinion “Balko is not entitled to the best possible statistical sample of claims that it submitted . . . Instead, Balko is only entitled to a statistically valid random sample.”  (Memorandum Opinion, p. 23.)

Question:  Is a “statistical valid random sample” one that is so poor that it lacks any scientific credibility?

What has happened in this case does not bode well for health care providers.   Here, statistical work that is demonstrably faulty and inferior and definitely not scientifically valid has been signed off on by the Medicare Appeals Council (MAC), and by the Federal Court that reviewed the case.

This type of sloppy scientific work never would be accepted in any other type of case before a Federal Court in which scientific evidence is evaluated in conformity with Rule 702 “Testimony by Expert Witnesses” of the Federal Rules of Evidence.   The question is why is this type of poor and inadequate scientific work OK for audits of health care providers but not OK anywhere else?

Barraclough NY LLC supplies experts for litigation support in Medicare and Medicaid appeals cases.

Documents reviewed:

John Balko & Associates d/b/a Senior Healthcare Associates, Plaintiff, v. Kathleen Sebelius Secretary U.S. Department of Health and Human Services, defendant. United States District Court for the Western District of Pennsylvania.  Case 2:12-cv-00572-AJS.

  1. Complaint (Filed 04/30/12)
  2. Answer to Complaint (Filed 08/20/2012)
  3. Brief in Support of Motion [for Summary Judgment] (Filed 11/15/2012)
  4. Brief in Opposition to Motion (Filed 12/04/12)
  5. Concise Statement of Material Facts (filed 11/16/12)
  6. Memorandum Opinion re: Parties’ Cross-Motions for Summary Judgment (Filed 12/28/2012)
  7. Judgment (Filed 04/08/14)
  8. Opinion of the Court (Filed 02/12/2014)

Note: There is another write-up of this ruling by Paige Fillingame at King & Spalding LLP with a free link to the ruling.

 

In Statistical Extrapolations, “Precision Not Required” by Medicare Appeals Council (MAC)

The case of Michael King, M.D. and Kinston Medical Specialists, P.A. before the Department of Health and Human Services, Departmental Appeals Board, Medicare Appeals Council (MAC), Docket M-10-321 offers one of the most distressing cases of acceptance of an unreliable statistical extrapolation.

MAC_King_Case.001

 Of particular note in this case is how the precision changed as the case moved from the original sampling through the Qualified Independent Contractor QIC reconsideration until after the Administrative Law Judge (ALJ) decision.

MAC_KING_PRECISION.001Another way to see this is to examine the range of precision allowed by the MPIM and that accepted in this case by the MAC.

MAC_KING_PRECISION_RANGE.001At Barraclough, we have been involved in a number of Medicare appeals, and unfortunately, we must report to you that this case is not atypical.

In our view, the type of statistical work routinely accepted by the Medicare Appeals Council (MAC) does not meet Federal Evidence Standards Rule 702Testimony by Expert Witnesses“.

A witness who is qualified as an expert by knowledge, skill, experience, training, or education may testify in the form of an opinion or otherwise if:

(a) the expert’s scientific, technical, or other specialized knowledge will help the trier of fact to understand the evidence or to determine a fact in issue;

(b) the testimony is based on sufficient facts or data;

(c) the testimony is the product of reliable principles and methods; and

(d) the expert has reliably applied the principles and methods to the facts of the case.

So here is our question:  Is =/- 40% a case of “reliably applied”?

 

The Case of John Sanders, M.D. – Medicare Appeals Council (MAC) Throws Out Extrapolation

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.

The case is: In the case of John Sanders, M.D. (May 12, 2011). Medicare Appeals Council (MAC).

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.

Appeal on Statistical Sampling for Medicare Audits – “Measuring the Variables of Interest” and “Proper Procedures”

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.

PROPER STATISTICAL METHODOLOGY IS NOT REQUIRED?

Barraclough has been working in the area of statistical sampling for more than ten years.   Over time, it has seen a deterioration in the standards for statistical sampling.   In essence, the current rules indicate that the contractor is not required to follow any specific statistical methodology or even follow many of the guidelines in the Medicare Program Integrity Manual  (MPIM).   In the MPIM, Chapter 3, Section 3.10.1.1 it states that:

“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.

Note:  This was quoted In the Case of Maxxim Care, EMS (February 25, 2010)

AUDITED CLAIMS PER PHYSICIAN | AMOUNT RECOVERED PER PHYSICIAN

The Recovery Audit program from CMS used four companies in FY 2012.   These are HDI, CGI, Performant, and Connolly.   These companies each are responsible for a specific part of the United States.

CMS_RECOVERY_RATES.001

(Source: Barraclough analysis.)

One would assume that the audit patterns would be roughly similar, but they are not.

If we use as a basis the total number of active physicians practicing in each region(*) and compare this to the activities of the Recovery Auditors, then an uneven pattern emerges.

RAC_regions.001NOTE: (*) Source: The Henry J. Kaiser Family Foundation

FY 2012 RECOVERY AUDITORS DATA FROM CMS: A 49:1 RATIO OVERPAYMENTS/UNDERPAYMENTS

The Centers for Medicare & Medicaid Services released its report “Recovery Auditing in Medicare and Medicaid for Fiscal Year 2012: FY 2012 Report to Congress as Required by Section 1893(h) of the Social Security Act and Section 6411(c) of the Affordable Care Act.”

There were $2.3 billion claw-backs from health care providers.   Audits also identified $109.4 million in underpayments, and these were paid back to the health care providers.

In other words, out of 100% improper payments, the auditors found that 98% were overpayments, and 2% were underpayments – this is a 49:1 ratio.  For every $49 dollars clawed back, $1 dollar is returned.

49:1