Understanding Random Sampling and RAT-Stats in Statistical Analysis

 
 
 
Random
Sampling
+
 RAT-Stats
 
Agenda
 
Part I – Sampling
 
Part II – RAT-Stats
 
Part III – Application
Objectives
 
Sampling
Population
Sampling
 is the process by which a subset
(sample) of a population is obtained.
 
Sample
 
Common Terms
 
Population
 - The entire pool from which a statistical sample is
drawn
 
Sample
 - A subset of the population
 
Sampling Unit 
– What is measured in the audit
 
Sample Frame 
– Subset of the population defined as variables of
interest from which the sample will be randomly selected and over
which the sample will be extrapolated
 
Confidence Interval 
– The probability that the value of a
parameter falls within a specified range of values
 
Common Terms
 
Stratification 
The process of dividing the population into
different sub-groups or strata
 
Precision Point 
– A measure of the closeness of the sample
estimate and the corresponding population value
 
Simple random sampling
*
 – The probability of being selected
into the sample is known and equal for all members of the
population.
 
Stratified sampling
*
 
separates the population into different
subgroups and then samples all of these subgroups
When Can It Be Used?
Probe Audit
Self Audit
Monitoring tool to assess risk within your agency
Following a probe audit or to investigate an allegation
According to OIG Self Disclosure Protocol:
 
(1)
Review all the claims affected
(2)
Review a statistically valid random sample of the
claims
OR
The
 
Process
 
1 – Define the population
 
2 – Identify the sampling frame
 
3 – Select a sampling design or procedure
 
4 – Determine sample size
 
5 – Draw the sample
 
Trust the Process!
 
If a particular probability sample design is properly
executed, i.e., defining the universe, the frame, the sampling
units, using proper randomization, accurately measuring the
variables of interest, and using the correct formulas for
estimation, then assertions that the sample and its resulting
estimates are “not statistically valid” cannot legitimately be
made. In other words, a probability sample and its results
are always “valid.”
CMS Medicare guidelines
CMS Pub.100-08 Chapter 3 Section 10.2
 
RAT-Stats
What Does It Mean?
 
R
egional
 
A
dvanced
 
T
echniques
 
Stat
istic
s
What Can It Do?
 
Determines statistically valid sample size
 
Generates replicable random number sets
through seed numbers*
 
Determines a range of financial impacts based
on the sample reviewed
*-Always document the seed number, so that your work is able to be
replicated either by another person in your agency or an outside source
 
The Magic
Illustrated
 
^Example of a Random Number
Set
 
^Formula to determine
Confidence
 
Application
 
Let’s Practice!
 
The step-by-step walkthrough takes you through the
entire sampling process, 
down to the very key stroke
 
A web-based walkthrough is being developed and will
be released in early 2019
 
Walkthrough guide is available on the CBH website*
 
*-Worksheets containing fabricated data which can be used for practice developing a
sample, in combination with the walkthrough, are available upon request. Please
contact Nicole Beaufort via email at 
Nicole.Beaufort@phila.gov
 to request the
worksheet.
 
Takeaways
 
Sampling with RAT-Stats is both efficient and
accurate
 
Strengthens agency’s ability to monitor for issues
related to Fraud, Waste, and Abuse
 
RAT-Stats software used by both OIG and CMS
– Also used by CBH to develop samples in both probe audits and targeted
audits
 
Not just for use in audits involving
extrapolation 
– Can also be used for internal audits and
sample creation for self audits
 
References
 
Center for Medicare and Medicaid Services. 2018. 
Publication 100-08 -
Medicare Program Integrity Manual
. 
https://www.cms.gov/Regulations-
and-Guidance/Guidance/Manuals/Internet-Only-Manuals-IOMs-
Items/CMS019033.html
.
Office of Inspector General - U.S. Department of Health & Human
Services. 2013. 
Provider Self-Disclosure
Protocol
https://oig.hhs.gov/compliance/self-disclosure-
info/protocol.asp
.
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Explore the concepts of random sampling, RAT-Stats, and their application in statistical analysis. Learn about sampling processes, common terms, precision points, and when to use these methods. Discover the steps involved in the sampling process and how it can be utilized in various audit and monitoring scenarios.


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  1. Random Sampling + RAT-Stats

  2. Agenda Part I Sampling Part II RAT-Stats Part III Application

  3. Objectives What? Why? How?

  4. Sampling

  5. Sampling is the process by which a subset (sample) of a population is obtained. Sample Population

  6. Common Terms Population - The entire pool from which a statistical sample is drawn Sample - A subset of the population Sample Frame Subset of the population defined as variables of interest from which the sample will be randomly selected and over which the sample will be extrapolated Sampling Unit What is measured in the audit Confidence Interval The probability that the value of a parameter falls within a specified range of values

  7. Common Terms Precision Point A measure of the closeness of the sample estimate and the corresponding population value Simple random sampling* The probability of being selected into the sample is known and equal for all members of the population. Stratification The process of dividing the population into different sub-groups or strata Stratified sampling* separates the population into different subgroups and then samples all of these subgroups

  8. When Can It Be Used? Probe Audit Monitoring tool to assess risk within your agency Self Audit Following a probe audit or to investigate an allegation According to OIG Self Disclosure Protocol: (1)Review all the claims affected (2)Review a statistically valid random sample of the claims OR

  9. The Process 1 Define the population 2 Identify the sampling frame 3 Select a sampling design or procedure 4 Determine sample size 5 Draw the sample

  10. Trust the Process! If a particular probability sample design is properly executed, i.e., defining the universe, the frame, the sampling units, using proper randomization, accurately measuring the variables of interest, and using the correct formulas for estimation, then assertions that the sample and its resulting estimates are not statistically valid cannot legitimately be made. In other words, a probability sample and its results are always valid. CMS Medicare guidelines CMS Pub.100-08 Chapter 3 Section 10.2

  11. RAT-Stats

  12. What Does It Mean? Regional Advanced Techniques Statistics

  13. What Can It Do? Determines statistically valid sample size Generates replicable random number sets through seed numbers* Determines a range of financial impacts based on the sample reviewed *-Always document the seed number, so that your work is able to be replicated either by another person in your agency or an outside source

  14. The Magic Illustrated ^Example of a Random Number Set ^Formula to determine Confidence

  15. Application

  16. Lets Practice! Walkthrough guide is available on the CBH website* The step-by-step walkthrough takes you through the entire sampling process, down to the very key stroke A web-based walkthrough is being developed and will be released in early 2019 *-Worksheets containing fabricated data which can be used for practice developing a sample, in combination with the walkthrough, are available upon request. Please contact Nicole Beaufort via email at Nicole.Beaufort@phila.gov to request the worksheet.

  17. Takeaways RAT-Stats software used by both OIG and CMS Also used by CBH to develop samples in both probe audits and targeted audits Strengthens agency s ability to monitor for issues related to Fraud, Waste, and Abuse Not just for use in audits involving extrapolation Can also be used for internal audits and sample creation for self audits Sampling with RAT-Stats is both efficient and accurate

  18. References Center for Medicare and Medicaid Services. 2018. Publication 100-08 - Medicare Program Integrity Manual. https://www.cms.gov/Regulations- and-Guidance/Guidance/Manuals/Internet-Only-Manuals-IOMs- Items/CMS019033.html. Office of Inspector General - U.S. Department of Health & Human Services. 2013. Provider Self-Disclosure Protocol. https://oig.hhs.gov/compliance/self-disclosure- info/protocol.asp.

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