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Rehabilitation Dataset Directory: Dataset Profile

Dataset: Basic Stand Alone Home Health Agency Beneficiary Public Use Files (BSA HHA Beneficiary PUF)

Basic Information
Dataset Full Name Basic Stand Alone Home Health Agency Beneficiary Public Use Files
Dataset Acronym BSA HHA Beneficiary PUF
Summary The Basic Stand Alone (BSA) Home Health Agency (HHA) Beneficiary Public Use Files (PUF) was released from CMS for 2008 and 2010. Contains information for a random 5% of Medicare beneficiaries that had at least one Home Health Agency (HHA) claim in the reference year. Note that the sample included in this file is deliberately disjoint (no overlap) from the samples in the CMS research file and other Public Use Files (PUF) and cannot be linked.
Key Terms Home Health care, Home Health Agencies, Utilization, Cost
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) N/A
Disability Measures N/A
Measures/Outcomes of Interest
Topics HHA use and expenditures, Distribution of therapy visits in HHA, Gender and Age differences in HHA utilization, Trends in HHA utilization and cost
Sample
Sample Population Medicare beneficiaries
Sample Size/Notes 124,829 (2008) Medicare beneficiaries 136,269 (2010) Medicare Beneficiaries
Unit of Observation Patient
Continent(s) North America
Countries

United States
Geographic Coverage National
Geographic Specificity National
Special Population(s)

Medicare beneficiaries
Data Collection
Data Collection Mode Administrative claims data
Years Collected 2008 and 2010
Data Collection Frequency N/A
Strengths and Limitations
Strengths
  • Large sample size - adequate to detect age or gender differences in home health utilization and costs.
  • Comparisons can be made between the 2 waves of data (2008 and 2010).
  • Well documented measures and data.
  • SAS program code available to create dataset.
Limitations
  • Data cannot be linked with other CMS datasets
  • No regional or state level data.
  • No patient diagnosis or reason for HHA admission
  • Some variables are rounded or categorized to preserve confidentiality
Data Details
Primary Website https://www.cms.gov/Research-Statistics-Data-and-Systems/Downloadable-Public-Use-Files/BSAPUFS/HHA_PUF
Data Access

https://www.cms.gov/Research-Statistics-Data-and-Systems/Downloadable-Public-Use-Files/BSAPUFS/HHA_PUF 
Data Access Requirements Public Use Dataset
Summary Tables/Reports

2008 Data documentation and frequency tables:

https://www.cms.gov/Research-Statistics-Data-and-Systems/Downloadable-Public-Use-Files/BSAPUFS/Downloads/2008_BSA_HHA_Bene_PUF_DataDic_CB.pdf


 2010 Data documentation and frequency tables:

https://www.cms.gov/Research-Statistics-Data-and-Systems/Downloadable-Public-Use-Files/BSAPUFS/Downloads/2010_BSA_HHA_Bene_PUF_DataDic_CB.pdf
Data Components N/A
Selected Papers
Other Papers

Data Users Document for the 2008 BSA HHA Beneficiary PUF (PDF)

Data Users Document for the 2010 BSA HHA Beneficiary PUF (PDF)
Technical

Data dictionary, codebooks, SAS data user guides, etc.

Access here:

https://www.cms.gov/Research-Statistics-Data-and-Systems/Downloadable-Public-Use-Files/BSAPUFS/HHA_PUF 

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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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