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Center for Large Data Research & Data Sharing in Rehabilitation

Rehabilitation Dataset Directory: Dataset Profile


Dataset: Provider of Services Files (POS)

Basic Information
Dataset full name: Provider of Services Files
Dataset acronym POS
Summary The POS files are created from the Online Survey and Certification Reporting System (OSCAR) database. The files contain an individual record for each Medicare-approved provider that is updated quarterly. These files include the following information related to participating institutional providers: Medicare provider number, name of facilities, geographical information (address), ownership structure, physical environment (size, bed numbers), physician and specialists information, other health professionals information, non-clinical staffing information, clinical services, accreditation information, and reimbursement information.
Key Terms Medicare, Health Provider Characteristics
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) NA
Disability Measures NA
Measures/outcomes of interest
Topics Hospitals, Nursing Facilities (NF), Skilled Nursing Facilities (SNF), SNF/NF (dually), Home Health Agencies (HHA), Portable X-rays, Physical Therapy/Speech Pathology, End Stage Renal Disease (ESRD), Nursing Facilities (NF), Intermediate Care Facility-Mentally Retarded (ICF/MR), Rural health clinics, Physical Therapy - Independent Practices, Comprehensive Outpatient Rehab Facilities (CORF), Ambulatory Surgical Centers (ASC), Hospices, Organ procurement organizations, Community Mental Health Centers (CMHC), Federally qualified health centers, CLIA88 laboratories added: effective 1997
Sample
Sample Population Medicare-approved health providers
Sample Size/Notes 100,000(±) Health Providers
Unit of Observation Service Provider
Geographic Coverage National
Geographic specificity Mailing Address
Data Collection
Data Collection Mode Administrative
Years Collected 1991 - present
Data Collection Frequency Quarterly
Strengths and limitations
Strengths Contains comprehensive information about providers. Ideal for building nested and hierarchical models. Data can be linked with other CMS/non-CMS datasets.
Limitations Documentation and variable information is limited. Reasons for changes in structure of a facility (provider) are unknown. Information on non-Medicare-approved facilities is unknown
Data details
Primary Website https://www.cms.gov/Research-Statistics-Data-and-Systems/Downloadable-Public-Use-Files/Provider-of-Services/index.html
Data Access CMS: https://www.cms.gov/Research-Statistics-Data-and-Systems/Downloadable-Public-Use-Files/Provider-of-Services/index.html Interactive POS files: https://data.cms.gov/browse?tags=pos&sortBy=newest NBER (SAS, STATA, CSV files): http://www.nber.org/data/provider-of-services.html NBER (data formats: CSV, SAS, STATA, COBOL): http://www.nber.org/data/provider-of-services.html
Data Access Requirements Data Use agreement, $ Cost
Summary Tables/reports NA
Dataset components (where applicable) NA
Selected papers
Technical Data Dictionary & Various data formats: CSV, SAS, STATA, COBOL (NBER): http://www.nber.org/data/provider-of-services.html
Other Papers



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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).

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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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