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Rehabilitation Dataset Directory: Dataset Profile

Dataset: Area Health Resource File (AHRF)

Basic Information
Dataset Full Name Area Health Resource File
Dataset Acronym AHRF
Summary The Area Health Resource File (AHRF), formally the Area Resource Files (ARF), is a database of information regarding the U.S. health care system and factors that may impact health care and health status in the U.S. The data contains nearly 6,000 variables and is available at the national, state and county levels. It is maintained and annually released by the U.S. Health and Human Services (HHS) Health Resources and Services Administration (HRSA). It includes information in eight different general topical areas: Health Care Professions, Health Facilities, Population Characteristics, Economics, Health Professions Training, Hospital Utilization, Hospital Expenditures, and Environment. The AHRF data integrates data from over 50 sources from a number of agencies including the American Medical Association, American Hospital Association, U.S. Census Bureau, CMS, Bureau of Labor Statistics, National Center for Health Statistics, and Veteran’s Administration.
Key Terms Health Care Professions, Hospitals and Health Care Facilities, and Census, Population Data and Environment Characteristics
Study Design Longitudinal
Data Type(s) Administrative
Sponsoring Agency/Entity Department of Health and Human Services (HHS):
Health Resources and Services Administration and Quality Resource System (QRS)
Health Conditions/Disability Measures
Health Condition(s) NA
Disability Measures NA
Measures/Outcomes of Interest
Topics Health Care Professions (e.g., Physicians, Nurse, and Rehabilitation professionals), Health Professions Training (e.g., Number of schools to train health professions and graduation rate), Health Facilities (e.g., Acute hospitals, Skilled nursing facilities, Inpatient rehabilitation facilities, and Home Health Agencies); Hospital Utilization (e.g., Length of stay, outpatient visits, procedures, and discharge destination); Hospital Expenditures (e.g., Facilities expenses and Payroll expenditures); County-level demographics (e.g., age, gender, and employment status); Environment and Geographical Codes
Sample
Sample Population Hospitals and health care facilities, Health care professions, Census: environment and population data
Sample Size/Notes NA
Unit of Observation Geographic Area (county, state and national levels)
Continent(s) North America
Countries

United States
Geographic Coverage National
Geographic Specificity County Level
Data Collection
Data Collection Mode Administrative
Years Collected 2000-present (historical data can be obtained with limited variables information)
Data Collection Frequency Annual
Strengths and Limitations
Strengths Comprehensive information about health providers, training. Ideal for building nested and hierarchical models. Data can be linked with other CMS/non-CMS datasets,
Limitations Documentation and variable information is limited. Aggregated information at county level. Limited usefulness as a stand-alone dataset.
Data Details
Primary Website https://datawarehouse.hrsa.gov/data/datadownload.aspx#MainContent_ctl00_gvDD_lbl_dd_topic_ttl_0
Data Access https://datawarehouse.hrsa.gov/data/datadownload.aspx#MainContent_ctl00_gvDD_lbl_dd_topic_ttl_0
Data Access Requirements Public Use Dataset
Summary Tables/Reports NA
Data Components NA
Selected Papers
Other Papers
Technical

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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.

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