Medicaid Overpayments: Challenging State Audit Allegations of - PowerPoint PPT Presentation

Presenting a live 90-minute webinar with interactive Q&A Medicaid Overpayments: Challenging State Audit Allegations of Overpayment and the Use of Statistical Sampling and Extrapolation TUESDAY, OCTOBER 11, 2016 1pm Eastern | 12pm Central | 11am Mountain | 10am Pacific Today’s faculty features: David R. Ross, Shareholder, O’Connell and Aronowitz , Albany, N.Y . Dr. Patricia L. Maykuth, Ph.D, President, Research Design Associates , Decatur, Ga. The audio portion of the conference may be accessed via the telephone or by using your computer's speakers. Please refer to the instructions emailed to registrants for additional information. If you have any questions, please contact Customer Service at 1-800-926-7926 ext. 10 .

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MEDICAID OVERPAYMENTS: Challenging State Audit Allegations of Overpayment and the Use of Statistical Sampling and Extrapolation Presented by: Pat Maykuth, Ph.D., President, Research Design Associates, Inc. David R. Ross, Esq., Shareholder, O’Connell & Aronowitz, P.C. Tuesday, October 11, 2016 1:00 p.m. to 2:30 p.m.

A Primer on Sampling and Extrapolation PART I OF THE PRESENTATION 6

Right Idea, Wrong Answer 7

There Are Three Kinds of Lies: Lies, Damned Lies, and Statistics So which is it? The outcome of any statistical study is determined by that characteristic that is sampled Why are so many polls in this election saying contradictory things? ◦ bias ◦ corrupted frame ◦ probability of selection unknown ◦ polling done for advocacy not to answer the question ◦ sampling error ◦ response bias 8

Dewey Wins the Election!! Pollsters surveyed via telephone 9

Ultimately, It Comes Down to Two Basic Questions 1. What is the ‘it’ that is being measured? 2. Is ‘it’ being measured correctly? 10

What is Statistics? Statistics is a branch of mathematics dealing with: ◦ the collection, ◦ analysis, ◦ interpretation, and ◦ presentation of masses of quantitative data 11

Terms Universe – dollar amount of claims paid to a Provider in a specific timeframe Sampling Frame – subset of the universe defined as variables of interest from which the sample will be randomly selected and over which the sample will be extrapolated Sample – a randomly selected subset of a sampling frame to be audited for overpayments Unit of Analysis (Sampling Unit) – what is measured in the audit: claim line, claim, beneficiary, provider (must be invariant throughout the audit) (Please see the List of Terms provided with presentation) 12

Frame (All claims for a particular time frame and code) Universe (Provider and all claims) 01/01/2010 Code: 12743 Sampl e (50 claims per sample) Sampling Unit (Individual claim: must be within frame) 13

Corrupted Frame Universe Fra Sampling Frame SAMPLE Outside Definition 14

Characteristics of a Valid Medicaid Overpayment Study 15

Define the Inferential who, what, Statistics Prior history of time and how Method: overpayment universe frame overpayment following error is measured rules required Select seed Calculate Applied to Sample & random sample file that is definition number size unbiased table Simple Stratified Independent observations Select Audit claims Randomly selected probability in the field Normally distributed sample Representative 16

Statistics Is Different from Numbers Statistical analysis that uses probability theory to generate and properly interpret inferences Probability statistics uses probability distributions for decision making. Probability theory is the mathematical basis of those distributions tested repeatedly Use subsets of data (sample) to estimate variables in a larger data set (frame/universe) 17

What is Statistical Sampling? For the purpose of today’s discussion: A Statistically Valid Random Sample (“SVRS”) from a universe of paid Medicaid claims ◦ Guards against cherry picking or any bias A sample has to: ◦ meet the requirements the methodology, ◦ meet chosen sampling error, ◦ be of sufficient size to accurately measure the variable, ◦ be random, and ◦ be representative (without bias) 18

Probability Statistics and SVRS  To know the number of samples of the chosen size that can be created from the frame  Known likelihood of selection of each sampling unit  Proper randomization  Proper execution of sample methodology  Use correct formulae  Accurate measurement of the variable of interest (overpayment) Medicare reference: MPIM 8.4.2; Cochran Sampling Methodology 19

What is Extrapolation? Extrapolation takes the results of an audited sample of claims and projects the dollar amount of the overpayment from the sample over the universe of paid claims The audited sample has a known amount of dollars in error so that amount is projected to the universe for a repayment amount 20

Medicare and Statistical Sampling Medicare Program Integrity Manual (MPIM) Chapter 8 1 provides nineteen pages of guidance “to provide instructions for [auditors] for the use of statistical sampling in their reviews to calculate and project (i.e., extrapolate) overpayment amounts to be recovered” 1 https://www.cms.gov/Regulations-and- Guidance/Guidance/Manuals/Downloads/pim83c08.pdf 21

Valid Outcomes Require Proper Execution  Defined universe  Defined frame  Defined sampling units  Use proper randomization  Accurately measure overpayments  Use the correct formulas for estimation  Test key assumptions of method  Accurately report actual findings 22

How to Properly Execute the Audit Methodology  Choose appropriate sampling unit, methodology and definition for the audit data  Meet the criteria of that statistical model  Exercise knowledgeable statistical oversight and quality control throughout  Document the process so that it can be replicated  Evaluate non-sampling errors and their impact  Calculate the results correctly  Report findings accurately and ethically 23

Random Samples A simple random sample is a sequence of independent, identically distributed (IID) random variables. The term random sample is ubiquitous in mathematical statistics while the abbreviation IID is just as common in basic probability. Much of basic probability and mathematical statistics deal with random parameters constructed from random samples (sample mean, sample variance, sample covariance, and order statistics). The point estimate (CMS’s common overpayment estimator) is a type of mean making these fundamental concepts critical to the prediction. 24

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Representative Samples A small yet complete and accurate picture of the data in the frame. A subset of a statistical universe that accurately reflects the numerical membership of the entire universe and its distribution. A representative sample is an unbiased indication of what the frame is like. Representativeness is tested mathematically. When a sample is not representative, the result is known as a sampling error. 26

Representative Sample Frame Sample 27

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Key Requirements for Use of Parametric Statistics Use a sample that is: ◦ Made up of independent observations ◦ Randomly selected ◦ Normally distributed ◦ Representative of the frame from which it was chosen and over which it will be extrapolated 29

Sample Size Determination Based on Chosen Precision and Confidence 30

RAT-STATS Results Confidence Level 80% 90% 95% 99% 1% 75 77 78 79 Precision 2% 63 68 71 75 Level 5% 29* 39 46 56 10% 10* 15* 20* 29* 15% 5* 8* 10* 16* * Sample sizes less than 30 31

Normal Distribution 32