FIND Disability Statistics
American Community Survey (ACS)
- Prevalence
- Employment Rate
- Not Working but Actively Looking for Work
- Full-Time / Full-Year Employment
- Annual Earnings
- Annual Household Income
- Poverty
- Supplemental Security Income (SSI)
- Educational Attainment
- Veterans Service-Connected Disability
- Health Insurance Coverage (and Type)
Current Population Survey (CPS)
EEOC Charge Data
Report Dashboard
ACCESS Research
Tools
Rehabilitation Dataset Directory: Dataset Profile
Dataset: Medicare Current Beneficiary Survey (MCBS)
Basic Information | |
---|---|
Dataset Full Name | Medicare Current Beneficiary Survey |
Dataset Acronym | MCBS |
Summary | The MCBS is a longitudinal survey that selects a nationally-representative sample of Medicare beneficiaries and longitudinally tracks their health status, health expenditures, and utilization of services. It uses a rotating panel design with each survey participant interviewed three times a year over four years, regardless of their residential settings (community or institutions). There are two types of data files in the MCBS: from 1991-2013, these were the Access to Care file and Cost and Use file; from 2015 and beyond, these are the Survey file and the Cost Supplement file. 1991-2013: The Access to Care file contains information on beneficiaries' access to health care (including rehabilitation services), satisfaction with care, and usual source of care. The MCBS Cost and Use file links Medicare financial claims to survey-reported events. 2015-present: The Survey file contains information about demographics (household characteristics, information on income and assets), health care (access, satisfaction, usual source of care, preventative service), health status (medical conditions and health behaviors), timeline data (health insurance and residence), and facility characteristics (if applicable). The Cost Supplement file contains details about health care cost (expenditure and payment, source of payment, supplementary insurance costs), health care utilization (services received), and fee-for-service claims data. The Cost Supplement file must be merged with the Survey file to perform analyses; the MCBS file containing cost information is no longer an independent module. Public Use Files (PUF) are available based on the 2013 and 2015 data (includes community sample only and more limited variables - see limitations section) Note that the data for 2014 were not released due to the 2015 redesign of the MCBS. |
Key Terms | Health Status, Health and Rehabilitation Services Use and Expenditures, Health Insurance Coverage, and Socioeconomic and Demographic Characteristics |
Study Design | Longitudinal |
Data Type(s) |
Survey |
Sponsoring Agency/Entity | Department of Health and Human Services (HHS): Centers for Medicare and Medicaid Services (CMS) - Office of Strategic Planning |
Health Conditions/Disability Measures |
Health Condition(s) | Allergies, Alzheimer's/dementia, Anxiety disorders, Arthritis, Bipolar disorder, Blood disorder, Body mass index (BMI)/obesity, Cancer, Cardiovascular conditions, Cerebral palsy, Depression, Diabetes, Down syndrome, Epilepsy or seizure disorder, Eye diseases, Heart attack, Infectious diseases, Kidney/renal condition, Missing limbs/hand/finger/feet, Multiple sclerosis, Orthopedic conditions, Osteoporosis, Parkinson's disease, Partial or total paralysis, Pulmonary disorders, Schizophrenia, Stroke, Thyroid disease, Traumatic brain injury (TBI) |
Disability Measures | Ambulatory disability, Cognitive disability, Communication impairment, Functional limitations (ADLs and/or IADLs), Hearing disability, Independent living disability, Intellectual disability, Mental health disability, Self-care disability, Special equipment use/assistive technology, Veteran service-related disability, Visual disability | Measures/Outcomes of Interest |
Topics | Health status, Health and rehabilitation services use and expenditures, Health insurance coverage, and Socioeconomic and Demographic characteristics | Sample |
Sample Population | Medicare beneficiaries |
Sample Size/Notes | Approximately 13,000 Medicare beneficiaries (oversampling of individuals age 85+ and those with disabilities) |
Unit of Observation | Individual |
Continent(s) | North America |
Countries | United States |
Geographic Coverage | National |
Geographic Specificity | NA |
Special Population(s) | Medicare beneficiaries |
Data Collection |
Data Collection Mode | Survey |
Years Collected | 1991-present (2014 data NA) |
Data Collection Frequency | Three times a year: Respondents (or appropriate proxy respondent) are interviewed every four months until they have completed four years of participation (total of 12 interviews over a 4 year period) |
Strengths and Limitations |
Strengths | Longitudinal design allows researchers to determine trajectories of health status and associated health/rehabilitation services utilization. It uses a combination of data collection strategies (administrative and survey). Can determine health expenditures for Medicare and other types of insurance coverage. As of 6/2018 Public Use Files (PUF) are available for 2013 and 2015.A text file with SAS programming code to create formats and to apply SAS labels is available for PUF users. |
Limitations | A redesign in 2015; 2014 data not released. The 2013 & 2015 Public Use Files (PUF) were evaluated for disclosure risk and additional steps were taken to protect respondent confidentiality. For this reason they contain less detail than the Limited Data Set (LDS) files. The 2015 PUF contains fewer variables than the LDS: 413 variables compared to the 4,041 variables in the LDS. The PUF only includes beneficiaries interviewed in the community (n=12,311 in 2015), excluding all beneficiaries who were in a health care facility part or all of the year (n=1,288). The PUF also does not contain Medicare claims data in individual form (available in the LDS data). |
Data Details |
Primary Website | https://www.cms.gov/Research-Statistics-Data-and-Systems/Research/MCBS/ |
Data Access |
Public Use File (PUF) 2013 & 2015:
Limited Data Set (LDS): https://www.cms.gov/Research-Statistics-Data-and-Systems/Files-for-Order/LimitedDataSets/index.html |
Data Access Requirements |
|
Summary Tables/Reports | Data Tables: https://www.cms.gov/Research-Statistics-Data-and-Systems/Research/MCBS/Data-Tables.html Data Briefs: https://www.cms.gov/Research-Statistics-Data-and-Systems/Research/MCBS/Data-Briefs.html |
Data Components |
|
Selected Papers |
Other Papers | Bibliography: https://www.cms.gov/Research-Statistics-Data-and-Systems/Research/MCBS/Bibliography.html |
Technical | Data Documentation and Codebooks: https://www.cms.gov/Research-Statistics-Data-and-Systems/Research/MCBS/Codebooks.html PUF Documentation: Questionnaires: https://www.cms.gov/Research-Statistics-Data-and-Systems/Research/MCBS/Questionnaires.html Data Briefs and Tutorials: https://www.cms.gov/Research-Statistics-Data-and-Systems/Research/MCBS/Data-Briefs.html |
Related Repositories |
Repositories |
Ask Our Researchers
Have a question about disability data or datasets?
E-mail your question to our researchers at disabilitystatistics@cornell.edu
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:
- Archive of Data on Disability to Enable Policy and research (ADDEP)
- Data Sharing & Archiving at CLDR
- Pilot Project Program
- Visiting Scholars Program
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