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Rehabilitation Dataset Directory: Dataset Profile
Dataset: Hospital Service Area (HSA) and Hospital Referral Regions (HRR) (HSA & HRR)
Basic Information | |
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Dataset Full Name | Hospital Service Area (HSA) and Hospital Referral Regions (HRR) |
Dataset Acronym | HSA & HRR |
Summary | A hospital service area (HSA) is a collection of ZIP codes whose residents receive most of their institutional care from the hospitals in that area. The HSA were defined by assigning ZIP codes to the hospital area where the greatest proportion of their Medicare residents were hospitalized. Hospital referral regions (HRR) represent regional health care markets for tertiary medical care. HRR were defined by assigning HSA to the region where the greatest proportion of major cardiovascular procedures and neurosurgeries were performed. The following data sources are used for computing HAS/HRR: the Centers for Medicare and Medicaid Services (CMS), U.S. Census Bureau, American Hospital Association, American Medical Association, and the National Center for Health Statistics. |
Key Terms | Geographical and Regional Variation, Quality of Care, Centers for Medicare and Medicaid Services, Medicare Spending, Racial Disparities |
Study Design | Longitudinal |
Data Type(s) |
Administrative |
Sponsoring Agency/Entity | Dartmouth Institute for Health Policy and Clinical Practice | Health Conditions/Disability Measures |
Health Condition(s) | NA |
Disability Measures | NA | Measures/Outcomes of Interest |
Topics | Geographical and regional variation, Quality of care, Centers for Medicare and Medicaid Services, Medicare spending, Racial disparities | Sample |
Sample Population | Hospital Service Area (HSA) and Hospital Referral Regions (HRR) |
Sample Size/Notes | HSA: 3,436 HRR: 306 |
Unit of Observation | Hospital Service Area (HSA) and Hospital Referral Regions (HRR): State and Region |
Continent(s) | North America |
Countries | United States |
Geographic Coverage | National |
Geographic Specificity | Zip Code | Data Collection |
Data Collection Mode | Administrative |
Years Collected | 1995-present |
Data Collection Frequency | Annual | Strengths and Limitations |
Strengths | Data ideal for doing health-policy research, on regional variation, and services utilization. Data can be linked with other CMS/non-CMS datasets. |
Limitations | Data files have limited or no usability as stand alone files (must be linked with other survey or administrative data). | Data Details |
Primary Website | http://www.dartmouthatlas.org/ |
Data Access | http://www.dartmouthatlas.org/tools/downloads.aspx |
Data Access Requirements | Data Use agreement, No cost |
Summary Tables/Reports | http://www.dartmouthatlas.org/publications/reports.aspx |
Data Components | NA | Selected Papers |
Other Papers | NA |
Technical | Bynum JPW, Meara ER, Chang CH, Rhoads JM, Bronner KK. Our Parents, Ourselves: Health Care for an Aging Population. Lebanon, NH: The Dartmouth Institute of Health Policy & Clinical Practice, 2016. http://www.dartmouthatlas.org/downloads/reports/Our_Parents_Ourselves_021716.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:
- 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