FIND Disability Statistics
American Community Survey (ACS)
- Employment Rate
- Not Working but Actively Looking for Work
- Full-Time / Full-Year Employment
- Annual Earnings
- Annual Household Income
- Supplemental Security Income (SSI)
- Educational Attainment
- Veterans Service-Connected Disability
- Health Insurance Coverage (and Type)
Current Population Survey (CPS)
EEOC Charge Data
Rehabilitation Dataset Directory: Dataset Profile
Dataset: Nursing Home Compare ()
|Dataset Full Name
|Nursing Home Compare
|The Centers for Medicare and Medicaid Services (CMS) launched a quality rating system for Medicare and Medicaid certified nursing homes (skilled nursing and long-term care facilities) on December 2008. This ongoing data collection aims to assist consumers (including patients) in selecting nursing homes by evaluating outcomes and deficiencies. The Nursing Home Compare uses a “five star rating” system, which is a composite measure derived from health inspection findings of these facilities, staffing (e.g., availability of nursing staff per resident per day), and quality measures (e.g., falls, pain, functional status, hospital readmissions).
Note that no patient level data is available. All data is aggregated at the national, state and individual Nursing Home level.
|Skilled Nursing care, swing beds, nursing home quality of care, nursing home staffing information, regulatory compliance, long-stay quality outcomes, short-stay quality outcomes, MDS dataset
|Centers for Medicare & Medicaid Services (CMS), Department of Health and Human Services (HHS)
|Health Conditions/Disability Measures
|Measures/Outcomes of Interest
|State and regional variations in nursing home quality outcomes. Nursing home quality measures
Longitudinal assessment of nursing homes’ improvement in quality outcomes
Short-stay resident measures: Proportion with: Functional status, hospital readmissions, emergency room visits, discharge to community, new or worsened pressure ulcers.
Long-stay residents measures: Proportion reporting: Falls, urinary tract infections, moderate to severe pain, pressure ulcers, functional status independence/improvement, weight loss, need for help with daily activities increased, depressive symptoms
Health and fire inspection deficiencies at nursing homes, staffing numbers per resident and association with quality care, short and long stay outcomes.
Hospitals and health care facilities/providers, All Medicare and Medicaid-certified nursing homes
|15,652 (January 2017) Medicare and Medicaid participating nursing homes included
Number of Nursing homes varies year to year
|Unit of Observation
|Individual Nursing home facilities
|Data Collection Mode
|Administrative claims data
Inspection reports / observational assessment
Observational assessment and medical records review of patients (MDS data)
|Data Collection Frequency
|Strengths and Limitations
|Data includes all Medicare and Medicaid-certified nursing homes and are ideal for doing research on regional and state variation on quality outcomes.
Data can be linked with other CMS datasets.
Risk-adjusted composite measures for quality outcomes allow for meaningful comparisons.
Comparisons can be made on national/state/facility level for different time periods.
|Patient-level data not available, only summaries at the nursing home level.
Potential bias could be introduced in staffing data and MDS quality outcomes since they are self-reported by nursing homes.
In 2016 and 2017 several changes made to the quality measure (QM) domain of the Five Star Nursing Home Quality Rating System including five new measures and methodological changes which may raise issues when comparing across years of data.
Current period data:
|Data Access Requirements
|Public Use Dataset
National and State averages:
Data available as Microsoft access database or csv files
Nursing home quality: a comparative analysis using CMS Nursing Home Compare data to examine differences between rural and non-rural facilities.:
Design for Nursing Home Compare Five-Star Quality Rating System: Technical Users’ Guide January 2017:
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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:
- Archive of Data on Disability to Enable Policy and research (ADDEP)
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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.
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