Medicare claims data contains valuable information that can be used for healthcare innovation and cost savings. The data includes procedures, diagnoses, and costs for over 38 million Medicare beneficiaries. When organized and analyzed, insights from the claims data can help reduce costs, improve quality of care, and validate new healthcare programs. However, working with Medicare data also has pitfalls like dealing with duplicate claims and ensuring privacy. Overall, harnessing Medicare claims data offers opportunities to innovate the healthcare system through observational studies, risk adjustment, and evaluation of new initiatives and treatments.

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Harnessing the power of Medicare Claims Data
Abstract: Medicare is the largest health insurance provider in United States. It provides health
insurance to over 38 million people. The purpose of this paper is to provide an understanding as
to how Medicare claims data can be mined and analyzed to provide valuable information. The
claims records are generated by Medicare operational processes and are primarily used to pay
providers. The claims records besides containing reimbursement information also contain other
important data elements– such as procedures performed and diagnosis codes - that are
maintained for informational purposes. As Medicare is faced with a growing patient base and
increasing costs, it is pressed to innovate by initiating new programs to reduce costs as well as
maintain quality. Information extracted from Medicare claims data can be used to identify new
cost saving opportunities and validate the business case for new public health initiatives.
About the Author: Protik Sandell, PMP, MBA is a Project Manager with Z-Tech Corporation, an
ICF International Company. He has over seventeen years of experience in leading information
technology initiatives. For the last four years he has been involved with a number of projects at
Center of Medicare and Medicaid Services, including the Chronic Care Improvement Program.
He is based at Rockville, Md. and can be reached at psandell@z-techcorp.com.
Medicare is administered by Center of Medicare and Medicaid Services (CMS), which is part of
the part of the United States Department of Health and Human Services. Medicare is the health
insurance program for people age 65 or older, people under age 65 with certain disabilities and
people of all ages with End Stage Renal Disease (permanent kidney failure requiring dialysis or
kidney transplant). Medicare was established in 1965, has a budget of over 400 billion dollar and
represents over 12 percent of the Federal Budget1, 2.
The Medicare program consists primarily of three parts, Medicare Part A (hospital insurance),
Medicare Part B (supplemental medical insurance) and Part D (Prescription Drug Coverage).
Part A covers hospital, skilled nursing facility, home health, out patient facilities and hospices
care. Part B covers doctors' services, durable medical equipment and a number of other medical
services and supplies. Part D provides coverage for prescription drugs to Medicare beneficiaries.
Over the past few years the enrollment to Medicare has been increasing. This is because of
changing demographics, as more people are entering into the 65 years age group. The average
cost of healthcare over the past few years have increased by 6.9 percent annually, twice the rate
of inflation3
. Increasing costs, compounded with increasing enrollment has created budgetary
issues for Medicare. Challenges to Medicare are abundantly clear in the 2004 report by the
Medicare Trustees, which indicates that the Part A Hospital Insurance trust fund will be
exhausted by 2019—seven years earlier than indicated by the 2003 Trustees Report.

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Healthcare Innovation using Medicare Claims Data
Due to the rising costs of Healthcare and the impending Medicare crisis, CMS, Congress and the
healthcare community is continually exploring opportunities to test new approaches to improve
quality, lessen costs, reduce medical errors and increase beneficiary satisfaction.
The Medicare Modernization Act 2003 contains provisions for a number of innovative pilot
projects. Some of the projects, introduced by MMA act, where harnessing information from
Medicare claims is critical to its success are
• Section 306, Use of Recovery Audit Contractors
• Section 646, Medicare Health Care Quality Demonstration Program
• Section 649, Medicare Care Management Performance Demonstration
• Section 648(a), Demonstration Project for Consumer-Directed Chronic Outpatient Services.
• Section 721, Voluntary chronic care improvement under traditional fee-for-service
Apart from pilots initiated by MMA, other uses of Medicare claims data for Healthcare
innovation are:
• Medicare claims data is used to populate Personal Health Record (PHR). A PHR enables
an individual to view and store medical history information. A PHR is an application that
enables individuals to be more active partners in his/her health care. Medicare claims
records provide critical information such as Diagnosis, Procedures, and encounter
information. CMS is currently piloting PHR for 230.000 beneficiaries4
.
• Medicare Claims data allow tracking the performance of a drug or medical product and
it’s effects on those who use it to treat or to recover from an illness or condition. FDA's
Center for Devices and Radiological Health (CDRH) is currently collaborating with CMS
and the Dartmouth Center for the Evaluative Clinical Sciences in a pilot study examining
the potential utility of Medicare data (Part A and B) for post market surveillance.
Comparative short- and long-term morbidity and mortality of open surgical versus
endovascular stent-graft repair of abdominal aortic aneurysms is being examined.5
• Medicare Claims data has also found usage in litigation. In 1999, the United States
Department of Justice filed a suit against tobacco industry, seeking reimbursement of
smoking-attributable Medicare. Medicare claims data was used to calculate past
smoking-attributable expenditures. Specifically Medicare Claims were used to obtain
total program expenditures by age, gender; Total annual expenditures for medical
encounters to treat specific smoking-related diseases; Number of beneficiaries being
treated for smoking-related diseases, by calendar year; Total annual cost of treating
beneficiaries with smoking-related disease.6

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Benefits of working with Medicare Claims Data
Medicare claims data offer a number of advantages. Firstly, the datasets are large and collected
over a number of years. Also, the information contained in the claims data is reasonably
accurate. Secondly, the data has been collected in a consistent manner, and thirdly, the data is
expected to continue to be collected, in the same manner. Longitudinal studies using the data can
follow patients after treatment for months or years. The data can be linked to hospital and
clinical data to evaluate changes in outcomes and to develop risk adjusters. Comparison groups
can be developed using claims data using a number of statistical techniques allowing controlled
observational studies.
Medicare Claims Data Flow
Medicare Claims data originate from Part A and Part B activities. Medicare Claims data contain
information of bills submitted by physicians, hospitals, home health agencies, nursing facilities,
hospices or other medical providers for office visits, hospital stays, or other encounters, or for
sales of supplies.
The first step in the Medicare Claims data flow is when a beneficiary receives service.
Beneficiary receives service from either Part A Institutional providers which include Hospitals,
Skilled Nursing Homes, Home Health Agencies, Hospices, Outpatient Facilities or Part B Non
Institutional providers such as Physicians and DME suppliers. The next step is that the provider
of the service or the clearinghouse sends a claim to a Medicare Fiscal Intermediary (FI) or
Carrier. The Carriers and FIs, are referred to as Medicare contractors. The Medicare Contractors,
using CMS “Shared Systems” perform traditional claims processing services to determine which
services are covered and the amounts payable. Then the Medicare Contractors send claims to
another system, known as the Common Working File (CWF) System for verification, validation,
and payment authorization. Responses are returned from the CWF concerning payments to the FI
or carrier, who subsequently pays for the service, if appropriate. CWF transmits the processed
claims to CMS. CMS loads the transmitted claims data into the National Claims History (NCH)
Repository and the National Medicare Utilization Database (NMUD)7
.The figure below
provides a high level overview of Medicare Claims Data Flow.

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Figure – Medicare Claims Data Flow
The National Claims History (NCH) database is an integral part of CMS’s database
infrastructure. It is an historical, tape-based system comprised of Medicare claims data from
1991 through the present. It houses approximately 1.1 billion claims per year. NCH is the single
storehouse for both Part A & Part B claims. Claims can be extracted from NCH by using Data
Extract System (DESY). Extracts are available for both Part A and Part B Claims. There are
seven different claim types – Inpatient (IP), Skilled Nursing Facility (SNF), Outpatient (OUT),
Home Health Agency (HHA), Carrier (CARR) and Durable Medical Equipment (DME). Each
claims type has its specific format and layout.
Key Data Elements in Medicare Claims Extract Files
Medicare Claims data file contain extensive information on each claim. The data dictionary for
each of the claim files are obtained at Research Data Assistance Center (ResDAC)’s website -
http://www.resdac.umn.edu. The list below provides key data elements for each claim type. The
key data elements are used for analyzing and researching Medicare Claims.
Table – Key Data Elements
Data Element Description8,9
Claim Types
Beneficiary Claim Account
Number
Number identifying the primary beneficiary IP, SNF, HOSP, HHA,
OUT, CARR, DME
Beneficiary Identification
Codes
Code identifying the type of relationship between an
individual and a primary
IP, SNF, HOSP, HHA,
OUT, CARR, DME
Demographic Information The claims extract files contain demographic
information relating to Race, Date of birth, and sex.
IP, SNF, HOSP, HHA,
OUT, CARR, DME

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Data Element Description8,9
Claim Types
Geographic Information The claims extract files contain geographic
information relating to state, county and zip code
IP, SNF, HOSP, HHA,
OUT, CARR, DME
Actual and Administrative
Dates
The claims extract files contain dates relating to date
of service, claim from date and claim thru date.
IP, SNF, HOSP, HHA,
OUT, CARR, DME
Administrative Claim
Processing Information
Administrative claim processing information refers to
Control Number, Claim Accretion Number, Accretion
Date, Query code fields
IP, SNF, HOSP, HHA,
OUT, CARR, DME
Claim Amounts Claim Amounts refers to Claims Charges/ Payments/
Deductibles/ Coinsurance/ Non-payment.
IP, SNF, HOSP, HHA,
OUT, CARR, DME
Disposition of the Claim Code indicating the disposition or outcome of the
processing of the claim record
IP, SNF, HOSP, HHA,
OUT, CARR, DME
Diagnosis Information The ICD-9-CM diagnosis code identifying the
diagnosis, condition, problem or other reason for the
admission/encounter/visit.
IP, SNF, HOSP, HHA,
OUT, CARR, DME
Primary Payer Information Federal non-Medicare program or other source that
has primary responsibility for the payment of the
Medicare beneficiary's medical bills
IP, SNF, HOSP, HHA,
OUT, CARR, DME
Physician Information Physician Information refers to Physician NPI, UPIN
and physician name.
IP, SNF, HOSP, HHA,
OUT, CARR, DME
Provider Information Unique identification number assigned to each
provider
IP, SNF, HOSP, HHA,
OUT, CARR, DME
Discharge Information IP, SNF
HCPCS Code The Healthcare Common Procedure Coding System
(HCPCS) codes that represent procedures, supplies
products and services.
IP, SNF, HOSP, HHA,
OUT, CARR, DME
Procedure Codes and Dates The ICD-9-CM code that indicates the principal or
other procedure performed.
IP, SNF, HOSP, OUT
Revenue Center
Information
The provider-assigned revenue code for each cost
center for which a separate charge is billed (type of
accommodation or ancillary). A cost center is a
division or unit within a hospital (e.g., radiology,
emergency room, and pathology).
IP, SNF
Admission and Discharge
Information
Admission information includes admission type,
initial diagnosis, date, priority, and means by which
the beneficiary was admitted. Discharge Information
includes the discharge date and the code used to
identify the status of the patient as of the last day of
the billing statement.
IP, SNF, , HOSP, HHA,
OUT
Patient Status Indicator
Code
Code indicating whether the beneficiary was
discharged, died or still a patient
IP, SNF. HOSP
Deductible and Liability
Amounts
The amount of the deductible the beneficiary paid / is
liable for / is submitted on the claim.
IP, SNF, CARR, DME
Utilization Day Counts The number of covered days of care that are
chargeable to Medicare facility utilization that
includes full days, coinsurance days, and lifetime
reserve days.
IP, SNF, HOSP
Diagnosis Related Group
Code
The diagnostic related group to which a hospital claim
belongs for prospective payment purposes
IP, SNF
Outlier Stay Code The code that an unusually long length (day outlier) or
exceptionally high cost (cost outlier).
IP, SNF
Blood Pints Furnished
Quantity
Number of whole pints of blood furnished to the
beneficiary.
IP, SNF, OUTP, CARR

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Standardized Coding System
For Medicare and other health insurance programs to ensure that these claims are processed in an
orderly and consistent manner, standardized coding systems are essential. Medicare claims uses
International Classification of Diseases, Clinical Modification, ninth revision (ICD-9-CM), and
Healthcare Common Procedure Classification System (HCPCS) to describe diagnosis,
procedures and services. The fields used to identify codes are Claim Principal Diagnosis Code,
Claim Procedure Code and HCPCS Code.
The HCPCS is divided into two principal subsystems, referred to as level I and level II of the
HCPCS. Level I of the HCPCS is comprised of CPT (Current Procedural Terminology), a
numeric coding system maintained by the American Medical Association (AMA). The CPT is a
uniform coding system consisting of descriptive terms and identifying codes that are used
primarily to identify medical services and procedures furnished by physicians and other health
care professionals. Level II of the HCPCS is a standardized coding system that is used primarily
to identify products, supplies, and services not included in the CPT codes, such as ambulance
services and durable medical equipment, prosthetics, orthotics, and supplies (DMEPOS) when
used outside a physician's office.
By looking at appropriate ICD-9-CM codes it can be determined whether the beneficiary has a
specific disease. For example, a beneficiary can be said to have Coronary Artery Disease if it has
have at least one inpatient claim or two separate outpatient claims on different dates with an ICD
9 CM codes 410.00 – 414.07, 414.8x, 414.9x, v45.81, v45.82. Also, HCPCS code can be
examined to determine specific service has been provided to beneficiary. Example – HCPCS
code of 82947, 82950, 82951 identify that a diabetes screening test has occurred.
Data Warehousing using Medicare Claims Data
Using data warehousing tools, Medicare data can be organized into facts and dimensions,
thereby allowing users to “drill down" for more detailed information, "drill up" to see a broader,
more summarized view, and "slice and dice" to dynamically change the combinations of
dimensions that are being viewed. Analysts can comprehend a far greater amount of information
if that information is organized into dimensions.
A number of facts can be derived from Medicare Claims. Some of these facts are
o Reimbursement Amount
o Hospital admissions / Hospital re-admissions
o Average Length of Stay
o Diabetes Screening Count
o Depression Screening Count

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o Emergency Room Visits Count
o Hospice Admissions
o Mortality Count
o Ambulatory care visits
o Total Expenditure
The facts can be viewed at various levels using different dimensions. For example –
Reimbursement Amount can be viewed for beneficiaries over the age of 70 with a specific
disease condition, or Diabetes Screening Count can be viewed by Provider by a specific zip code
and within a specific time frame. Some of the dimensions by which facts can be viewed are -
o Demographic levels (such as beneficiary, age, sex, marital status)
o Claims Type (IP, SNF, Hospice, HHA, Outpatient, DME, carrier)
o Provider
o Diagnosis condition
o Disease
o Procedure
o Geography (such as zip code, county, state)
o HCPCS Code
o Time (Year, Quarter, Month)
Pitfalls in working with Medicare Data
Working with Medicare data has a number of pitfalls. Some of them are:
• Medicare data is typically made available in mainframe variable length EBCDIC formats.
Most business analysis and database tools require additional effort for converting the data
to ASCII format.
• Also, the Medicare claims data obtained from CMS have duplicate claims that represent
debits, credits and adjustments. Prior to analyzing Medicare claims, Final Action
Algorithm needs to be used to identify and remove duplicate.
• As Medicare claims contain personal identifiable information they need to be stored and
exchanged securely.

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Conclusion
Medicare data is a gold mine of information. Medicare claims contain a wealth of information,
which include diagnosis code, procedure code, diagnosis-related group, reimbursement amount,
hospital provider, and beneficiary demographic information. With proper knowledge of
Medicare claims data, it can be used to perform research on a variety of topics such as provider
performance, effectiveness of treatment and pilot initiatives.
References
1 - Bush's Budget Proposal Would Cut Medicare Spending -
http://www.washingtonpost.com/wp-dyn/content/article/2008/02/04/AR2008020402490.html
2 – The federal budget crisis explained - http://www.smartchristian.com/?p=5538
3. Facts on the Cost of Health Care - http://www.nchc.org/facts/cost.shtml
4. Registration Summary & Medication History - A Personal Health Record (PHR) Pilot for
Medicare Beneficiaries -
http://www.hhs.gov/healthit/ahic/materials/12_07/ce/doo_files/textonly/slide6.html
5. The Sentinel Initiative - A National Strategy for Monitoring Medical Product Safety -
http://www.fda.gov/oc/initiatives/advance/reports/report0508.html
6. Use of Medicaid and Medicare Administrative Claims Data in Litigation and Regulation -
http://www.fcsm.gov/03papers/Wyant.pdf
7. Exhibit 300 (BY2009) - Centers for Medicare and Medicaid Services (CMS) Data
Management Operations - Claims -
http://www.hhs.gov/ocio/capitalplanning/exhibit300/FY09Exhibit300/cmsdatamanagementopera
tionsclaims.html
8. Medicare Institutional Data Dictionary - http://www.resdac.umn.edu/ddvib/dd_via2.asp
9. Medicare Non-Institutional Data Dictionary - http://www.resdac.umn.edu/ddvib/dd_vib.asp