CMS-10501_Supporting_Statement_Part_A

SUPPORTING STATEMENT Healthcare Fraud Prevention Partnership HFPP Data Sharing and Information Exchange

_BACKGROUND

The Healthcare Fraud Prevention Partnership (HFPP) is a joint initiative established by the Department of Health and Human Services (HHS) and Department of Justice (DOJ) to detect and prevent the prevalence of healthcare fraud through data and information-sharing and applying analytic capabilities by the public and private sectors. The HFPP creates a permanent structure where skills, assets and data to address fraud issues of mutual concern can be shared in accordance with applicable laws by its partners. Current HFPP partners include private insurance carriers (“payers”) and antifraud associations, state Medicaid agencies, CMS, and other federal agencies such as the Health and Human Services (HHS) Office of Inspector General (OIG), the Department of Justice (DOJ) and the Federal Bureau of Investigation (FBI).

The HFPP collaboration provides a unique opportunity to transition from traditional “pay and chase” approaches for fraud detection and recovery towards a data-driven model for identifying and predicting aberrant activity. A central goal of the HFPP is to identify the optimal way to coordinate nationwide sharing of health care claims information, including aggregating claims and payment information from large public healthcare programs and private insurance payers. In addition to sharing data and information, the HFPP is focused

on advancing analytics, training, outreach, education to support anti-fraud efforts and achieving its objectives, primarily through goal-oriented, well-designed fraud studies.

The HFPP’s organizational structure is made up of an Executive Board, the Data Analysis and Review Committee (DARC), and the Information Sharing Committee (ISC). The HFPP will also include a Trusted Third Party (TTP) that CMS will engage to provide the technical and operational platform to support the partnerships’ data sharing, collaboration and study outreach activities. Enabling data sharing and providing analytical computing capabilities of the TTP is central to the success of the HFPP.

_{A. JUSTIFICATION}

_{1. Need and Legal Basis}

Section 1128C(a)(2) of the Social Security Act (42 U.S.C. § 1320a-7c(a)(2)) authorizes the Secretary and the Attorney General to consult with, and arrange for the sharing of data with representatives of health plans to establish a Fraud and Abuse Control Program as specified in Section 1128(C)(a)(1) of the Social Security Act. This is known as the Healthcare Fraud Prevention Partnership (HFPP). It was officially established by a Charter in fall 2012 and signed by HHS Secretary Sibelius and US Attorney General Holder.

of combatting waste, fraud and abuse. These studies are intended to target specific vulnerabilities within the payment systems in both the public and private sectors. The HFPP and its committees will design and develop studies in coordination with the TTP. The core function of the TTP is to manage and execute the HFPP studies within the HFPP. Specifically, the TTP will collect and consolidate partner (both public and private) study-related data in order to share information among the HFPP pertaining to

analytical tools and techniques; study analysis; successful anti-fraud practices, trends and vulnerabilities; and reports that maintain the confidentiality of its source data. The data and information collected by the TTP may be categorized as follows:

 Process and Procedure Data and Information

The TTP is responsible for the lifecycle of HFPP activities, which spans from initial partner engagement/on-boarding through the completion of HFPP studies and potentially closing out relationships with organizations that may no longer be involved with the HFPP for various reasons. The TTP must collect all pertinent HFPP partner-specific documentation necessary for successful interaction with the HFPP; this may include information associated with the breadth of health care payer services provides, lives covered, etc. Additionally, the TTP will collect information describing potential studies that the HFPP may endeavor to include definitions of vulnerabilities identified, timelines of exchange, level of monetary exposure to potential fraud schemes, and other areas that provide context and description that further information or data exchange could bolster the anti-fraud, waste and abuse activities currently underway at partner organizations; these data may include market surveillance research intended to enhance the quality and effectiveness of fraud studies.

 Study Specific Data and Information

Based on a specific study’s design, the TTP will create a plan that outlines the goal of the study, the method for achieving that goal, the data required to execute that

method, and the analytic tools envisioned to analyze the data. Each study may require different types of data, participation from different partners of the HFPP and different models of execution. Studies will be designed to have clear and measurable performance metrics and will therefore be designed with a defined goal in mind.

The TTP will collect and analyze data on a study-by-study basis, at least initially, and HFPP participating entities will voluntarily share a subset of health insurance claims data in a standard format (derived by the TTP). The analysis phase of the study process will always contain: a data acquisition phase, harmonization and merging, analysis, quality assurance, documentation and reporting steps. Depending on the

type of question answered by a study, this analysis phase might contain quantitative data analysis, qualitative data analysis, outlier analysis, clustering\grouping, entity resolution , trend analysis, time series analysis, networking analysis, trending, statistical summarization and more. Examples of study data may include specific

provider types. Personally identifiable provider data may be provided. Finally, after conducting the analyses, the TTP will generate reports and communicate study results to study participating entities. For this phase, the TTP must collect and synthesize outcomes and performance metrics, including data and information to document processes, best practices, and results. Reports will summarize TTP performance, key accomplishments, planned activities, lessons learned, and any other relevant information.

 Results, Outcomes, and Performance Data and Information

The TTP will produce several possible outputs: a general summary and lessons learned of the analysis meant for the HFPP as a whole; a partner-specific summary report for those participating in a study; and a partner-specific detailed report for those participating in a study. While some of the data and information that generates the reports will be generated from the specific data provided, the TTP also must collect additional information generated by the HFPP partner use of the results and outcomes of the study. For example, in some cases, the TTP may reach out to HFPP partners to understand the steps taken by each partner as a result of the information/data exchange. The TTP may also collect information regarding the number of referrals made to law enforcement agencies, and other administrative actions taken resulting from the information provided through the study.

_{2. Information Users}

HFPP partners are responsible for data sharing and information exchange to address fraud issues of mutual concern. Current HFPP partners include private insurance carriers (“payers”) and anti- fraud associations, state Medicaid agencies, CMS and other federal agencies. The partners electing to participate in particular studies are responsible able to submit data for conducting studies to detect and deter fraud. The HFPP partners will also be able to share results pertaining to their internal anti-fraud initiatives.

_{3. Improved Information Technology}

All data will be collected in electronic format.

_{4. Duplication}

This collection and sharing of data does not duplicate any other effort and the information cannot be obtained from any other source.

_{5. Small Business}

There is no burden on small businesses.

6. Less Frequent Collection

There are no consequences to less frequent collection.

_{7. Special Circumstances}

None

_{8. Federal Register Notice/Prior Consultation}

The 60-day Federal Register notice published on October 23, 2013.

The HFPP was officially established by a Charter in fall 2012 and signed by HHS Secretary Sibelius and US Attorney General Holder.

_{9. Payment/Gift to Respondents}

There are no payments or gifts to partners providing data specific to the studies conducted by the HFPP

_{10. Confidentiality}

We pledge privacy to the extent allowed by law. CMS intends to seek a System of Records for the data systems involved in the program. Information will be safeguarded in accordance with Departmental standards and National Institute of Standards and Technology (NIST) Special Publication 800-53, Recommended Security Controls for Federal Information Systems and Organizations which limits access to only authorized personnel. The safeguards shall provide a level of security as required by Office of Management and Budget (OMB) Circular No. A-130 (revised), Appendix III – Security of Federal Automated Information Systems.

_{11. Sensitive Questions}

This data collection does not contain information pertaining to sex, behavior, attitude, religious beliefs or any other matters that are considered private or sensitive in nature.

_{12. Burden Estimate}

CMS expects to implement various studies for the Healthcare Fraud Prevention Program (HFPP) that may vary greatly in complexity. Over the course of the 3-year approval, each HFPP partner would voluntarily participate in the studies that are pertinent and effective in detecting fraud within its organization.

For simple studies, CMS estimates a burden of 80 hours of partner engagement and support per study. This includes burden hours necessary for study design, data extract, quality assurance, definition resolution, and information/data transmission.

More complex studies may require summary data, data-subsets, or submission of data in a specifically defined manner with a specific data dictionary. These types of studies may require additional data manipulation, transformation and possibly simple summary

calculations. CMS estimates a burden of 120 to 160 hours for a custom data extraction, this time includes time for software development, QA, analysis and transmission.

We are unable to accurately predict how many information exchanges may be instituted under this approach.

_{Table 1 outlines the burden estimates that we foresee partners potentially experiencing:}

Table 1: Annual Burden Estimate
	Estimated Average Processing Time for On Partner (in hours)	Estimated Annual Processing Time Per Partner (in hours)	Estimated Participating Partners per Study	Estimated Total Annual Processing Time (in hours)	Per Hour Rate of Claim Investigator or Special Investigations Unit (SIU) Staff	Estimated Total Hourly Rate Per Study
Simple Data Extraction and Submission	80	80	15*	1,200	$43.00	$51,600
Complex and Custom Data Extraction and Submission	160	160	15*	2,400	$43.00	$103,200
Estimated Annual Total Hours and Cost Burden**	1,200	1,200	15	180,000	$43.00	$774,000

*Assumes 15 HFPP Partners participating in each study.

**Assumes 5 Studies conducted per year of each level of complexity.

_{13. Capital Costs}

CMS is responsible for all costs to create a CMS Enterprise Portal for HFPP and for creating a data repository for data collection and data analysis.

_{14. Costs to Federal Government}

Costs to CMS to implement this program include administrative costs as well as costs to procure contractor support in various functional areas including technical and business services and products. Actual expenditures will depend on results from an active procurement based on proposals received from prospective implementing contractors.

_{15. Program/Burden Changes}

None, this is a new information collection.

16. Publication and Tabulation Dates

Data will not be made available to the general public.

_{17. Expiration Date}

CMS does not seek an exemption from the requirement to display the expiration date for this collection.

_{18. Certification Statement}

There are no exceptions to the certification statement.

_{B. COLLECTION OF INFORMATION EMPLOYING STATISTICAL METHODS}

Statistical analysis refers to a variety of methods used to collect data, describe data, explore and understand new patterns and relationships in data, test hypotheses, make inferences about a population, and predict future behavior based on sample datasets.

Illustrative Scenario

Process data collected.

Use Case

Using tools, TTP collaborates with HFPP partners to: quickly explore data sets, identify

missing or anomalous data, prepare data for analysis, and produce statistically significant findings that are relevant to business needs.

Technical Aspects

_{ Design of experiments}

 Forecasting, regression analysis, and time series analysis

 Factor analysis, principal component analysis, and structural equations modeling

 Classification, discriminate analysis, and clustering

 Sensitivity/uncertainty Analysis

 Common methods include time series analysis, regression and ANOVA providing a mathematical representation for exploration and prediction, sampling methods, and hypothesis testing.

Example Tools

SAS, R, SPSS, Strata

Data sharing within the HFPP will primarily focus on conducting studies for the purpose