CMS Pub. 100-08, ch. 2, § 2.2

A. Contractors To Which This Section Applies

This section applies to MACs, UPICs, SMRC. This section does not apply to the

Recovery Auditors. Recovery Auditors should follow the data analysis instructions listed

in their Statement of Work.

B. General

Data analysis is a tool for identifying actual or potential claim payment errors. Data

analysis applies well-established statistical methods to claim information and other

related data to identify potential errors and potential fraud by claim characteristics (e.g.,

diagnoses, procedures, providers, or beneficiaries) individually or at an aggregate level.

Data analysis is an integrated, on-going component of MR and benefit integrity (BI)

activity.

The MACs and UPICs ability to make use of available data and apply innovative

analytical methodologies is critical to the success of the MR and BI programs. They

should use research and experience in the field to develop new approaches and

techniques of data analysis. The MACs and UPICs should have ongoing communication

with other government organizations (e.g., QIOs and the State Medicaid agencies)

concerning new methods and techniques.

Analysis of data should:

• Identify those areas of potential errors (e.g., services which may be non-covered or not correctly coded) that pose the greatest risk;

• Establish baseline data to enable the recognition of unusual trends, changes

in utilization over time, or schemes to inappropriately maximize

reimbursement;

• Identify where there is a need for an LCD;

• Identify where there is a need for targeted education efforts;

• Suggest claim review strategies that efficiently prevent or address potential

errors (e.g., prepayment edit specifications or parameters);

• Produce innovative views of utilization or billing patterns that illuminate

potential errors;

• Identify high volume or high cost services that are being widely overutilized.

This is important because these services do not appear as an outlier and may be

overlooked when, in fact, they pose the greatest financial risk;

• Identify program areas and specific providers for possible fraud

investigations; and

• Determine if major findings identified by Recovery Auditors, CERT, and

CMS represent significant problem areas in the MAC’s jurisdiction.

This data analysis program shall involve an analysis of national data furnished by CMS

as well as review of internal billing utilization and payment data to identify potential

errors.

The goals of the data analysis program are to identify provider billing practices and

services that pose the greatest financial risk to the Medicare program.

The MACs and UPICs shall document the processes used to implement their data

analysis program and provide the documentation upon request.

In order to implement a data analysis program, the MACs and UPICs shall:

• Collect data from sources such as:

o Historical data, e.g., review experience, denial data, provider billing

problems, provider cost report data, provider statistical and reimbursement

(PS&R) data, billing data, payment data, utilization data, data from other

Federal sources (e.g., QIO, other MACs, Medicaid); and

o Common Working File (CWF)

• Referrals from internal or external sources (e.g., 1-800 Medicare Call

Center, provider audit, beneficiary, State Senior Medicare Patrol, or other

complaints).

The shared system maintainer shall allow MACs the ability to select claims using the NPI

or the legacy number (OSCAR or UPIN) as a criterion for medical review.

C. Resources Needed for Data Analysis

The MACs and UPICs shall have available sufficient hardware, software, and personnel

with analytical skills to meet requirements for identifying problems efficiently, and

effectively developing and implementing corrective actions. If MACs are unable to

employ staff with the qualifications necessary for effective data analysis, evaluation and

reporting, they shall use other entities (e.g., universities, consultants, other contractors)

who can provide the technical expertise needed. The following are minimum resource

requirements for conducting data analysis, evaluation, and reporting.

1. Data Processing Hardware

Adequate equipment for data analysis includes facilities to process data

(e.g., mainframes and personal computers) and to store data (e.g., tape

drive, disk drives, etc.). Upgrading current resources (e.g., mainframe

computers, shared systems, etc.) or the purchase of new capabilities (e.g.,

microcomputer workstations or subcontracts for computer services) may

provide additional processing capabilities. In addition, MACs and UPICs

shall have secure telecommunication capabilities to interact with the CMS

Data Center.

2. Data Processing Software

The CMS provides MACs and UPICs with software to allow communication

with the CMS Data Center. At their discretion, MACs and UPICs that wish to

develop or acquire additional software that allows for analysis of internal data

or other data obtained from the CMS Data Center may do so. The MACs and

UPICs should have internal software to support the analyses of data to meet

program goals.

3. Personnel

The MACs and UPICs shall have staff with appropriate training, expertise and

skills to support the application of software and conduct systematic analyses

and clinical evaluation of claims data. CMS strongly encourages MACs and

UPICs to have staff with clinical expertise (e.g., registered nurses) and a mix of

skills in programming, statistics, and data mining analysis (e.g., trending and

profiling of providers/codes).

The MACs and UPICs shall also employ a staff that has training in developing analytical

and sampling strategies for overpayment projections.

D. Frequency of Analysis

The MACs shall have a minimum of 18 months of data but are encouraged to have 36

months. The MACs shall, at a minimum, compare the current 6-month period to the

previous 6-month period to detect changes in providers’ current billing patterns and to

identify trends in new services. Summary data or statistically representative samples can

be used when dealing with very large volumes of data.

E. Determine Indicators to Identify Norms and Deviations

The MACs and UPICs shall develop indicators that will be used to identify norms,

abnormalities, and individual variables that describe statistically significant time-series

trends and the most significant abnormalities or trends. Examples of indicators or

variables are:

• Standard deviations from the mean;

• Percent above the mean or median;

• Percent change in billing activity, payment charges, and number of

visits/services from one period to another.

• Rate of change over specified periods in time.

F. Document Data Strategy

While the CMS is deliberately not prescriptive in terms of the technical details of how to

reach data analysis goals, MACs and UPICs are expected to develop the most

sophisticated and effective methods and procedures to meet these goals and will be held

accountable for accurate, effective reports, procedures, and quality outcomes.