The Area Health Resources Files (AHRF) provide current as well as historic data for more than 6,000 variables for each of the nation's counties, as well as state and national data. They contain information on health facilities, health professions, measures of resource scarcity, health status, economic activity, health training programs, and socioeconomic and environmental characteristics. In addition, the basic file contains geographic codes and other metadata which enable it to be linked to other files.

The Bureau of Health Professions Area Resource File is a county-based data file summarizing secondary data from a wide variety of sources into a single file to facilitate health analysis. The file contains over 6,000 data elements for all counties in the United States with the exception of Alaska, for which there is a state total, and certain independent cities that have been combined into their appropriate counties. The data elements include: (1) County descriptor codes (name, FIPS, HSA, PSRO, SMSA, SEA, BEA, city size, P/MSA, Census Contiguous County, shortage area designation, etc.), (2) Health professions data (number of professionals registered as M.D., D.O., DDS, R.N., L.P.N., veterinarian, pharmacist, optometrist, podiatrist, and dental hygienist), (3) Health facility data (hospital size, type, utilization, staffing and services, and nursing home data), (4) Population data (size, composition, employment, housing, morbidity, natality, mortality by cause, by sex and race, and by age, and crime data), (5) Health Professions Training data (training programs, enrollments, and graduates by type), (6) Expenditure data (hospital expenditures, Medicare enrollments and reimbursements, and Medicare prevailing charge data), (7) Economic data (total, per capita, and median income, income distribution, and AFDC recipients), and (8) Environment data (land area, large animal population, elevation, latitude and longitude of population centroid, water hardness index, and climate data). (ICPSR 3/16/2015)

A database containing more than 6,000 variables for U.S. counties. ARF contains information on health facilities, health professions, measures of resource scarcity, health status, economic activity, health training programs, and socioeconomic and environmental characteristics. In addition, the basic file contains geographic codes and descriptors which enable it to be linked to many other files and to aggregate counties into various geographic groupings.

Database containing more than 6,000 variables for each of the nation's counties. Contains information on health facilities, health professions, measures of resource scarcity, health status, economic activity, health training programs, and socioeconomic and environmental characteristics. Contains geographic codes and descriptors which enable it to be linked to many other files and to aggregate counties into various geographic groupings. ICPSR contains 1940-1990. Also know as Bureau of Health Professions Area Resource File.***Microdata: YesLevel of Analysis: Local - countyVariables Present: Yes - Separate DocumentFile Layout: .asc (.sas for 209-2023)Codebook: Yes Methods: YesWeights (with appropriate documentation): YesPublications: NoAggregate Data: No

This submission includes publicly available data extracted in its original form. Please reference the Related Publication listed here for source and citation information If you have questions about the underlying data stored here, please contact [Health Resources & Services Administration (HRSA) at NCHWAInquiries@hrsa.gov]. If you have questions or recommendations related to this metadata entry and extracted data, please contact the CAFE Data Management team at: climatecafe@bu.edu. "This dataset provides current as well as historic data for more than 6,000 variables for each of the nation’s counties, as well as state and national data. It contains information on health facilities, health professions, measures of resource scarcity, health status, economic activity, health training programs, and socioeconomic and environmental characteristics. In addition, the basic file contains geographic codes and descriptors which enable it to be linked to many other files and to aggregate counties into various geographic groupings. The Area Health Resources Files (AHRF) data are designed to be used by planners, policymakers, researchers, and others interested in the nation’s health care delivery system and factors that may impact health status and health care in the United States. The AHRF data includes county, state, and national-level files in eight broad areas: Health Care Professions, Health Facilities, Population Characteristics, Economics, Health Professions Training, Hospital Utilization, Hospital Expenditures, and Environment. The AHRF data are obtained from more than 60 sources. The AHRF has county, state, and national level files from the HRSA, Bureau of Health Workforce (BHW), National Center for Health Workforce Analysis (NCHWA) available for download." [Quote from https://data.hrsa.gov/data/download]

The Area Resource File is made available by the Bureau of Health Professions. The basic county-specific Area Resource File (ARF) is the nucleus of the overall ARF System. It is a database containing more than 6,000 variables for each of the nation's counties. ARF contains information on health facilities, health professions, measures of resource scarcity, health status, economic activity, health training programs, and socioeconomic and environmental characteristics. In addition, the basic file contains geographic codes and descriptors which enable it to be linked to many other files and to aggregate counties into various geographic groupings.

From the codebook: The Area Resource File (ARF) is a county-based data file, summarizing secondary data from a wide variety of sources, which are useful to health analysts and others conducting research on the nation's health care delivery system. It contains over 6000 data elements for all counties in the U.S., with the exception of Alaska. Data elements include county descriptor codes, health data, and limited data on vital statistics, industry, housing, expenditure and environmental factors.

DATA.HRSA.GOV is the go-to source for data, dashboards, maps, reports, locators, APIs and downloadable data files on HRSA's public health programs, including: HRSA-funded Health Center grants, grantees, sites, and related primary care programs Health Professional Shortage Areas (HPSA) and Medically Underserved Areas/Populations (MUA/P) Ryan White HIV/AIDS services, grantees, and providers Maternal and Child Health grants (Title V, Home Visiting, Healthy Start) National Health Service Corps (NHSC), Nurse Corps, and other workforce loan repayment/scholarship programs Grants for workforce training programs in medicine, nursing, dentistry, and public health Grants for rural health programs Organ donation DATA.HRSA.GOV allows you to search by topic area, by geography, and by tool.

The Area Resource File (ARF) is a compilation from more than 200 sources of the most useful data for assessing the nation's health care resources. The data are merged and summarized at a county level, combined into one computer file.

Distributions of 3-year age-adjusted cancer incidence rates, by SES and HSS, in 611 SEERa counties.

This repository includes data from the Health Resources & Services Administration's Area Health Resources Files (years 2000, 2004-2019), CDC Wonder, National Conference of State Legislatures, and the Drug Enforcement Agency's Automation of Reports and Consolidated Orders System (ARCOS).

Please cite the following publication when using this dataset:

KN Griffith, Y Feyman, SG Auty, EL Crable, TW Levengood. (in press). County-level data on U.S. opioid distributions, demographics, healthcare supply, and healthcare access, Data in Brief.

These data were originally collected for the following research article:

Griffith, KN, Feyman, Y, Crable, EL, & Levengood, TW. (in press). “Implications of county-level variation in U.S. opioid distribution.” Drug and Alcohol Dependence.

Factor loadings and fit statistics of the new county-level composite SES and HSS indices.

Context

Health workforce shortage areas are geographic areas, populations, and facilities that have a shortage of outpatient primary care, dental, and mental health providers and services. These areas are designated by the Health Resources and Services Administration (HRSA), a federal agency in the United States Department of Health and Human Services.

There are several types of shortage designations including: - Health Professional Shortage Areas (HPSAs) - Medically Underserved Areas and Populations (MUAPs) - Exceptional Medically Underserved Population (Exceptional MUPs) - Governor's-Designated Secretary-Certified Shortage Areas for Rural Health Clinics

HRSA's Bureau of Health Workforce operates a cooperative agreement and evaluates applications submitted by the Primary Care Office (PCO) of each U.S. state and territory as part of the process to designate some types of shortage areas. These applications are reviewed by HRSA to determine if they meet specific designation criteria which differs by the type of shortage area. Other shortage area types are automatically designated by federal statute or at the request of a state governor. Once HPSAs are designated, score is calculated which represents a relative measure of need for health care services for that discipline. Both HPSAs and MUAPs can be designated to indicate a shortage of primary care services while only HPSAs can be designated to indicate a shortage of dental or mental health services. Shortage area designations and scores are used by various federal programs for distributing resources. Some shortage area designations may also be used by state programs.

See the shortage designation website for more information.

Content

The health workforce shortage area data in the included files represent the HPSA and MUAP (including Exceptional MUP) designation information at a single point in time. The dataset is refreshed weekly from the source data files on data.hrsa.gov.

HPSAs All three file contain the same columns but represent only a single healthcare discipline. Each record represents either a "component" (county, county subdivision or census tract) of a Geographic/Population HPSA service area or represents the physical location of facility HPSA.

Files: - BCD_HPSA_FCT_DET_PC.csv: Primary Care HPSAs - BCD_HPSA_FCT_DET_DH.csv: Dental Health HPSAs - BCD_HPSA_FCT_DET_MH.csv: Mental Health HPSAs

Fields of interest: - [HPSA ID]: Unique identifier for each HPSA designation - [Designation Type]: Type of HPSA Designation. Types for areas designated for a geographic area include "Geographic HPSA", "High Needs Geographic HPSA" and "HPSA Population" - [HPSA Discipline Class]

MUAPs Each record in this file represents a "component" (county, county subdivision or census tract) of a Medically Underserved Area or Medically Underserved Population Group service area

Files: - MUA/_DET.csv: Medically Underserved Areas/Populations

Fields of interest:

Acknowledgements

Inspiration

The Health Resources and Services Administration (HRSA) monitors and creates the geographic Health Professional Shortage Area (HPSA) federal designations for Primary Care, Mental Health, and Dental Health and can update those designations at any time. To avoid outdated information, static HPSA files have been removed from this site. Please visit https://data.hrsa.gov/data/download, select "Health Workforce" from the dropdown, and click "Shortage Areas" to find the updated HPSA files. If you have any questions, please use the contact email below to reach out to HCAI's Workforce Data Inbox.

BackgroundArea-level indices are widely used to assess the impact of socio-environmental characteristics on cancer outcomes. While area-level measures of socioeconomic status (SES) have been previously used in cancer settings, fewer studies have focused on evaluating the impact of area-level health services supply (HSS) characteristics on cancer outcomes. Moreover, there is significant variation in the methods and constructs used to create area-level indices.MethodsIn this study, we introduced a psychometrically-induced, reproducible approach to develop area-level HSS and SES indices. We assessed the utility of these indices in detecting the effects of area-level characteristics on prostate, breast, and lung cancer incidence and stage at diagnosis in the US. The information on county-level SES and HSS characteristics were extracted from US Census, County Business Patterns data and Area Health Resource Files. The Surveillance, Epidemiology, and End Results database was used to identify individuals diagnosed with cancer from 2010 to 2012. SES and HSS indices were developed and linked to 3-year age-adjusted cancer incidence rates. SES and HSS indices empirically summarized the level of employment, education, poverty and income, and the availability of health care facilities and health professionals within counties.ResultsSES and HSS models demonstrated good fit (TLI = 0.98 and 0.96, respectively) and internal consistency (alpha = 0.85 and 0.95, respectively). Increasing SES and HSS were associated with increasing prostate and breast cancer and decreasing lung cancer incidence rates. The results varied by stage at diagnosis and race.ConclusionComposite county-level measures of SES and HSS were effective in ranking counties and detecting gradients in cancer incidence and stage at diagnosis. Thus, these measures provide valuable tools for monitoring geographic disparities in cancer outcomes.

Distribution of county characteristics by SES and HSS classes, 2010–2012 SEER 17 combined (N = 611).

The goal is to predict the rate of heart disease (per 100,000 individuals) across the United States at the county-level from other socioeconomic indicators. The data is compiled from a wide range of sources and made publicly available by the United States Department of Agriculture Economic Research Service (USDA ERS).

There are 33 variables in this dataset. Each row in the dataset represents a United States county, and the dataset we are working with covers two particular years, denoted a, and b We don't provide a unique identifier for an individual county, just a row_id for each row.

The variables in the dataset have names that of the form category_variable, where category is the high level category of the variable (e.g. econ or health). variable is what the specific column contains.

We're trying to predict the variable heart_disease_mortality_per_100k (a positive integer) for each row of the test data set.

Columns

area — information about the county

area_rucc — Rural-Urban Continuum Codes "form a classification scheme that distinguishes metropolitan counties by the population size of their metro area, and nonmetropolitan counties by degree of urbanization and adjacency to a metro area. The official Office of Management and Budget (OMB) metro and nonmetro categories have been subdivided into three metro and six nonmetro categories. Each county in the U.S. is assigned one of the 9 codes." (USDA Economic Research Service, https://www.ers.usda.gov/data-products/rural-urban-continuum-codes/)

area_urban_influence — Urban Influence Codes "form a classification scheme that distinguishes metropolitan counties by population size of their metro area, and nonmetropolitan counties by size of the largest city or town and proximity to metro and micropolitan areas." (USDA Economic Research Service, https://www.ers.usda.gov/data-products/urban-influence-codes/)

econ — economic indicators

econ_economic_typology — County Typology Codes "classify all U.S. counties according to six mutually exclusive categories of economic dependence and six overlapping categories of policy-relevant themes. The economic dependence types include farming, mining, manufacturing, Federal/State government, recreation, and nonspecialized counties. The policy-relevant types include low education, low employment, persistent poverty, persistent child poverty, population loss, and retirement destination." (USDA Economic Research Service, https://www.ers.usda.gov/data-products/county-typology-codes.aspx)

econ_pct_civilian_labor — Civilian labor force, annual average, as percent of population (Bureau of Labor Statistics, http://www.bls.gov/lau/)

econ_pct_unemployment — Unemployment, annual average, as percent of population (Bureau of Labor Statistics, http://www.bls.gov/lau/)

econ_pct_uninsured_adults — Percent of adults without health insurance (Bureau of Labor Statistics, http://www.bls.gov/lau/) econ_pct_uninsured_children — Percent of children without health insurance (Bureau of Labor Statistics, http://www.bls.gov/lau/)

health — health indicators

health_pct_adult_obesity — Percent of adults who meet clinical definition of obese (National Center for Chronic Disease Prevention and Health Promotion)

health_pct_adult_smoking — Percent of adults who smoke (Behavioral Risk Factor Surveillance System)

health_pct_diabetes — Percent of population with diabetes (National Center for Chronic Disease Prevention and Health Promotion, Division of Diabetes Translation)

health_pct_low_birthweight — Percent of babies born with low birth weight (National Center for Health Statistics)

health_pct_excessive_drinking — Percent of adult population that engages in excessive consumption of alcohol (Behavioral Risk Factor Surveillance System, )

health_pct_physical_inacticity — Percent of adult population that is physically inactive (National Center for Chronic Disease Prevention and Health Promotion)

health_air_pollution_particulate_matter — Fine particulate matter in µg/m³ (CDC WONDER, https://wonder.cdc.gov/wonder/help/pm.html)

health_homicides_per_100k — Deaths by homicide per 100,000 population (National Center for Health Statistics)

health_motor_vehicle_crash_deaths_per_100k — Deaths by motor vehicle crash per 100,000 population (National Center for Health Statistics)

health_pop_per_dentist — Population per dentist (HRSA Area Resource File)

health_pop_per_primary_care_physician — Population per Primary Care Physician (HRSA Area Resource File)

demo — demographics information

demo_pct_female — Percent of population that is female (US Census Population Estimates)

demo_pct_below_18_years_of_age — Percent of population that is below 18 years of age (US Census Population Estimates)

demo_pct_aged_65_years_and_older — Percent of population that is aged 65 years or older (US Census Population Estimates)

dem...

The Healthcare Cost and Utilization Project (HCUP) State Emergency Department Databases (SEDD) contain the universe of emergency department visits in participating States. The data are translated into a uniform format to facilitate multi-State comparisons and analyses. The SEDD consist of data from hospital-based emergency department visits that do not result in an admission. The SEDD include all patients, regardless of the expected payer including but not limited to Medicare, Medicaid, private insurance, self-pay, or those billed as ‘no charge’. Developed through a Federal-State-Industry partnership sponsored by the Agency for Healthcare Research and Quality (AHRQ), HCUP data inform decision making at the national, State, and community levels.

The SEDD contain clinical and resource use information included in a typical discharge abstract, with safeguards to protect the privacy of individual patients, physicians, and facilities (as required by data sources). Data elements include but are not limited to: diagnoses, procedures, admission and discharge status, patient demographics (e.g., sex, age, race), total charges, length of stay, and expected payment source, including but not limited to Medicare, Medicaid, private insurance, self-pay, or those billed as ‘no charge’. In addition to the core set of uniform data elements common to all SEDD, some include State-specific data elements. The SEDD exclude data elements that could directly or indirectly identify individuals. For some States, hospital and county identifiers are included that permit linkage to the American Hospital Association Annual Survey File and the Bureau of Health Professions' Area Resource File except in States that do not allow the release of hospital identifiers.

Restricted access data files are available with a data use agreement and brief online security training.

The Healthcare Cost and Utilization Project (HCUP) State Inpatient Databases (SID) are a set of hospital databases that contain the universe of hospital inpatient discharge abstracts from data organizations in participating States. The data are translated into a uniform format to facilitate multi-State comparisons and analyses. The SID are based on data from short term, acute care, nonfederal hospitals. Some States include discharges from specialty facilities, such as acute psychiatric hospitals. The SID include all patients, regardless of payer and contain clinical and resource use information included in a typical discharge abstract, with safeguards to protect the privacy of individual patients, physicians, and hospitals (as required by data sources). Developed through a Federal-State-Industry partnership sponsored by the Agency for Healthcare Research and Quality (AHRQ), HCUP data inform decision making at the national, State, and community levels. The SID contain clinical and resource-use information that is included in a typical discharge abstract, with safeguards to protect the privacy of individual patients, physicians, and hospitals (as required by data sources). Data elements include but are not limited to: diagnoses, procedures, admission and discharge status, patient demographics (e.g., sex, age), total charges, length of stay, and expected payment source, including but not limited to Medicare, Medicaid, private insurance, self-pay, or those billed as ‘no charge’. In addition to the core set of uniform data elements common to all SID, some include State-specific data elements. The SID exclude data elements that could directly or indirectly identify individuals. For some States, hospital and county identifiers are included that permit linkage to the American Hospital Association Annual Survey File and county-level data from the Bureau of Health Professions' Area Resource File except in States that do not allow the release of hospital identifiers. Restricted access data files are available with a data use agreement and brief online security training.