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Rehabilitation Dataset Directory: Dataset Profile

Dataset: Medicare Beneficiary Summary File ()

Basic Information
Dataset Full Name Medicare Beneficiary Summary File
Dataset Acronym
Summary

** NOTE: As of 03/2012 the Beneficiary Summary File is no longer available. The information found in this file is now found in the Master Beneficiary Summary File (MBSF) Base (a/b/c/d) segment.** 



The Beneficiary Summary File contains demographic (e.g., age, gender, race, and type of residence) and enrollment (e.g., original reason for enrollment under Medicare, current reason for enrollment under Medicare, and monthly entitlement indicators) information about each Medicare beneficiary enrollee during a calendar year. Prior to 2006, these files were known collectively as the Denominator File. As of 2006, the file also includes variables specific to enrollment in Medicare Part D benefits. They also include a derived race/ethnicity code from the Research Triangle Institute’s developed algorithm, monthly indicators for Medicare Advantage plan enrollment, and State Reported Dual Eligibility Status (a State Buy-In indicator).

Key Terms Medicare, Demographic and Enrollment Information
Study Design Longitudinal
Data Type(s) Administrative
Sponsoring Agency/Entity Department of Health and Human Services (HHS): Centers for Medicare and Medicaid Services (CMS)
Health Conditions/Disability Measures
Health Condition(s)

ADD/ADHD, Alzheimer's/dementia, Anxiety disorders, Autism spectrum disorders,Cardiovascular conditions, Bipolar disorder, Body mass index (BMI)/obesity, Cancer, Cerebral palsy, Depression, Diabetes, Epilepsy or seizure disorder, Heart attack, Kidney/renal condition, Migraine or frequent headaches, Muscular dystrophy, Orthopedic conditions, PTSD, Pulmonary disorders, Schizophrenia, Spinal cord injury (SCI), Stroke, Thyroid disease, Traumatic brain injury (TBI)
Disability Measures

Ambulatory disability, Cognitive disability, Hearing disability, Visual disability
Measures/Outcomes of Interest
Topics Demographic (e.g., Age, Gender, Race, and Residential), Enrollment information
Sample
Sample Population Medicare beneficiaries (fee-for-service and Medicare Advantage Program)
Sample Size/Notes 35,000,000 (±) Medicare beneficiaries
Unit of Observation Patient
Continent(s) North America
Countries

United States
Geographic Coverage National
Geographic Specificity Zip Code (of beneficiary’s mailing address)
Special Population(s)

Medicare beneficiaries
Data Collection
Data Collection Mode Administrative
Years Collected 1999 - 2012
Data Collection Frequency Annual
Strengths and Limitations
Strengths Very large sample size, and contains cross-sectional and longitudinal components. Can be linked with Medpar and other clinical data. Useful for health policy research
Limitations Clinical and intervention information is limited. Requires high computational, and data analytical capabilities.
Data Details
Primary Website

** NOTE: As of 03/2012 the Beneficiary Summary File is no longer available. The information found in this file is now found in the Master Beneficiary Summary File (MBSF) Base (a/b/c/d) segment.**
See: https://www.resdac.org/cms-data/files/mbsf-base
Data Access

** NOTE: As of 03/2012 the Beneficiary Summary File is no longer available. The information found in this file is now found in the Master Beneficiary Summary File (MBSF), Base (a/b/d) segment.**
See: https://www.resdac.org/cms-data/files/mbsf-base
Data Access Requirements Data Use agreement, $ Cost
Summary Tables/Reports NA
Data Components 5% and 100%
Similar/Related Dataset(s)

Master Beneficiary Summary File (MBSF) Base
Selected Papers
Other Papers
Technical Center for Medicare and Medicaid Services, 2010. Dictionary For SAS and CSV Datasets
https://www.cms.gov/LimitedDataSets/downloads/SAFldsDenomNov2009.pdf

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The Rehabilitation Research Cross-dataset Variable Catalog has been developed through the Center for Large Data Research & Data Sharing in Rehabilitation (CLDR). The Center for Large Data Research and Data Sharing in Rehabilitation involves a consortium of investigators from the University of Texas Medical Branch, Cornell University's Yang Tan Institute (YTI), and the University of Michigan. The CLDR is funded by NIH - National Institute of Child Health and Human Development, through the National Center for Medical Rehabilitation Research, the National Institute for Neurological Disorders and Stroke, and the National Institute of Biomedical Imaging and Bioengineering. (P2CHD065702).

Other CLDR supported resources and collaborative opportunities:

Acknowledgements: This tool was developed through the efforts of William Erickson and Arun Karpur, and web designers Jason Criss and Jeff Trondsen at Cornell University. Many thanks to graduate students Kyoung Jo Oh and Yeong Joon Yoon who developed much of the content used in this tool.

For questions or comments please contact disabilitystatistics@cornell.edu



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