Home  /   Data Sources  /   Rehabilitation Dataset Directory: Search  /   Dataset Profile Center for Large Data Research & Data Sharing in Rehabilitation

Rehabilitation Dataset Directory: Dataset Profile

Dataset: Hospital Service Area (HSA) and Hospital Referral Regions (HRR) (HSA & HRR)

Basic Information
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


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:

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