Category Archives: Healthcare

Tools to Analyze County Demographic-Economic Characteristics

.. demographic-economic characteristics of counties are essential for business development, market analysis, planning, economic development, program management and general awareness of patterns and trends. This section provides access to data and tools to examine these data for all counties in the U.S. This annual update includes geographic area characteristics based on ACS 2015 data.  The tools/data are organized into four related sections summarized below.

1. General Demographics
View interactive table at http://proximityone.com/us155dp1.htm
Patterns of School Age Population by County
Use GIS tools to visually examine county general demographics as illustrated below. The following view shows patterns of percent population ages 5 to 17 years of age by county — item D001-D004-D018 in the interactive table. Create your own views.

… view developed using the CV XE GIS software.

2. Social Characteristics
View interactive table at http://proximityone.com/us155dp2.htm 
Patterns of Educational Attainment by County
– percent college graduate
Use GIS tools to visually examine county social characteristics as illustrated below. The following view shows patterns of percent college graduate by county — item S067 in the interactive table. Create your own views.

… view developed using the CV XE GIS software.

3. Economic Characteristics
View interactive table at http://proximityone.com/us155dp3.htm 
Patterns of Median Household Income by County
Use GIS tools to visually examine county economic characteristics as illustrated below. The following view shows patterns median household income by county — item E062 in the interactive table. Create your own views.

… view developed using the CV XE GIS software.

4. Housing Characteristics
View interactive table at http://proximityone.com/us155dp4.htm 
Patterns of Median Housing Value by County
Use GIS tools to visually examine county housing characteristics as illustrated below. The following view shows patterns median housing value by county — item E062 in the interactive table. Create your own views.

… view developed using the CV XE GIS software.

Join me in a Data Analytics Lab session to discuss more details about accessing and using wide-ranging demographic-economic data and data analytics. Learn more about using these data for areas and applications of interest.

About the Author
— Warren Glimpse is former senior Census Bureau statistician responsible for innovative data access and use operations. He is also the former associate director of the U.S. Office of Federal Statistical Policy and Standards for data access and use. He has more than 20 years of experience in the private sector developing data resources and tools for integration and analysis of geographic, demographic, economic and business data. Contact Warren. Join Warren on LinkedIn.

Examining Health Characteristics by Census Tract

.. new data, new ways to examine health characteristics at the city and census tract/subcounty level.  For example, among the 500 largest U.S. cities in 2014, the incidence of high blood pressure ranged from 22.5% (Longmont, CO) to 47.8% (Gary, IN). Use the interactive table to view, rank, compare this and other new wide-ranging health statistics for the 500 largest U.S. cities and associated census tracts. See the related Web section for more detail.

At the census tract/neighborhood level, 937 tracts have more than 10% of the population ages 18 years and over with coronary heart disease. What are characteristics of health-related factors in your city, neighborhood and census tracts of interest? Use tools reviewed in this section to access/analyze a wide range of health-related characteristics (see items list below) — not available at the city or census tract level before.

Patterns of High Blood Pressure: Honolulu, HI by Census Tract
This graphic illustrates visual analysis and analytical potential for tracts in cities covered.

– Click graphic for larger view with high blood pressure %population label
– View developed with CV XE GIS software and related GIS project/fileset.

Accsss/analyze these data for approximately 28,000 tracts (of a total approximate 74,000) on topics including chronic disease risk factors, health outcomes and clinical preventive service use for the largest 500 cities in the U.S. These small area data enable stakeholders in cities, local health departments, neighborhoods and study areas to better understand the characteristics and geographic distribution of health-related measures and how they might impact health-related programs and other demographic-economic issues.

Scope of 500 Cities
The following graphic shows the 500 cities (green areas) included in project. Data for these cities and intersecting tracts are available. Click graphic for larger view providing county visibility and city name labels. Expand browser to full window for best quality view.

– View developed with CV XE GIS software and related GIS project/fileset.

The 500 Cities data have been developed as a part of the CDC 500 Cities project, a collaboration between the Centers for Disease Control (CDC), the Robert Wood Johnson Foundation and the CDC Foundation. These data are being integrated into the Situation & Outlook (S&O) database and included in the S&O metro reports. Examine health-related characteristics of metro cities and drill-down areas in combination with other demographic-economic measures.

Analytical Potential
These data provide only the health characteristics attributes. They are a small, but important, subset of a larger set of key health metrics. These data are estimates subject to errors of estimation and provide a snapshot view of one point in time.

The value of these data can be leveraged by linking them with other demographic-economic data from the American Community Survey (ACS 2015) tract and city data. Integrate and analyze these data with related data and alternative geography. See related health data analytics section.

Patterns of Heart Disease; Charlotte, NC-SC Area by Tract
This graphic illustrates coronary heart disease patterns by census tract for cities included in the database. Gray areas are census tracts not included in the 500 cities database. Click graphic for larger view.
– View developed with CV XE GIS software and related GIS project/fileset.

Using the Interactive Table
Use the interactive table to view, rank, compare, query these health measures by city. The following graphic illustrates how the table can be used to examine patterns of Texas cities. Table operations are used to selected Texas cities then rank the cities based on the “Access” column — “Current lack of health insurance among adults aged 18-64 Years”.

Try it yourself. Use the table to examine a set of cities in a state of interest.

Join me in a Data Analytics Lab session to discuss more details about accessing and using wide-ranging demographic-economic data and data analytics. Learn more about using these data for areas and applications of interest.

About the Author
— Warren Glimpse is former senior Census Bureau statistician responsible for innovative data access and use operations. He is also the former associate director of the U.S. Office of Federal Statistical Policy and Standards for data access and use. He has more than 20 years of experience in the private sector developing data resources and tools for integration and analysis of geographic, demographic, economic and business data. Contact Warren. Join Warren on LinkedIn.

Metro Situation & Outlook Reports Updated

Regional Demographic-Economic Modeling System (RDEMS) county table links are now embedded in Metro Situation & Outlook (S&O) Reports. Easily access the RDEMS county demographic-economic tables for metros of interest.

Use this link to access the Metro S&O Reports:
http://proximityone.com/metro_reports.htm
… click link in the “Code” column to access a specific metro.

… selected metros …
Atlanta .. Boston .. Charlotte .. Chicago .. Dallas .. Denver .. Los Angeles .. Honolulu .. Houston .. Miami .. Minneapolis .. New York .. Philadelphia .. Phoenix .. San Diego .. San Francisco .. Seattle .. Washington

All metros are available.

Join in … join us in the Data Analytics Lab sessions to discuss more details about accessing and using wide-ranging demographic-economic data and data analytics. Learn more about using these data for areas and applications of interest.

Analyzing County Health Patterns

.. as the population ages, migrates and otherwise changes, health status and healthcare needs change by location, type and in other ways. Data on health status, characteristics and trends continue to become more available, particularly at the county geographic level … but these data are often difficult to locate, integrate and use in a combined manner.

VA Hospitals/Facilities in Context of Urban/Rural Areas
The following graphic illustrates how Veterans Administration hospitals and facilities (red markers) can be viewed in context of urban/rural patterns. Urban areas are shown with orange fill pattern. The Appalachia 405 county area is shown with black bold boundary. Use (GIS) resources to examine additional patterns such as the distribution of veterans by census tract based on the American Community Survey (ACS) data.

— view created using CV XE GIS and associated county health GIS Project
— click graphic for larger view showing details.

County Health Analytics
This section provides an overview of accessing, integrating and analyzing demographic, economic and health data with a focus on county and sub-county geography. Geographic information system (GIS) tools are used to visually and geospatially analyze health-related patterns and characteristics. Applications reviewed here are developed using the CV XE GIS software and associated U.S. national scale health GIS Project. See more detail in the related Web section.

The County Health Patterns GIS project includes data from:
• ProximityOne CountyTrends and Situation & Outlook
… view individual county population & components of change trends
… click county link in this interactive table
• Robert Wood Johnson Foundation County Health Rankings
Appalachian Regional Commission economic status
• Other sources. See additional information

Additional ProximityOne ready-to-use shapefiles could be added containing all data from the American Community Survey demographic-economic profiles. The same scope of subject matter, annually updated, is available at the ZIP code, census tract, county and other geography. See related interactive tables (four related web sections) for subject matter details.

The CV XE GIS software is used with the County Health Patterns GIS project to develop views/applications shown below. These views/applications illustrate how the health analytics resources can be used. Select from wide ranging alternative measures.

Patterns of Population Change — %Change 2010-2014 — U.S. by County
The following view shows patterns of %population change 2010-2014 using the CountyTrends layer/dataset.

— view created using CV XE GIS and associated county health GIS Project
— click graphic for larger view showing details.

Site Analysis & Patterns of Population Change
— %Change 2010-2014 — Houston Metro Area
The following view shows patterns of %population change 2010-2014 using the CountyTrends layer/dataset. This view also illustrates use of the Site Analysis tool to aggregate and display population by year 2010 through 2014.

— click graphic for larger view showing details.

Patterns of Population Change
— %Change 2010-2014 — Missouri Area Counties
The following view shows patterns of %population change 2010-2014 using the CountyTrends layer/dataset. This view also illustrates use of the Metros layer to show outlines of Missouri metropolitan statistical areas (bold red/brown boundary). Counties are labeled with the 2014 population estimate.

— click graphic for larger view showing details.

Patterns of Percent Smokers — U.S. by County
The following view shows patterns of percent smokers by county using the County Health Rankings RMD layer/dataset. Choose from a list of wide-ranging health-related subject matter items.

— click graphic for larger view showing details.

Patterns of Food Insecurity — U.S. by County
The following view shows patterns of food insecurity by county using the County Health Rankings AMD layer/dataset. Choose from a list of wide-ranging health-related subject matter items.

— view created using CV XE GIS and associated county health GIS Project
— click graphic for larger view showing details.

Patterns of Food Insecurity — Appalachia Region
The following view shows a zoom-in of the above view.

— click graphic for larger view showing details.

Patterns of Economic Distress — Appalachia Region
The following view shows patterns of economic distress based on an index developed by the Appalachian Regional Commission. Economic characteristics of an area can have a direct impact on health and well-being and access to healthcare resources.

— click graphic for larger view showing details.

An upcoming section will review more detail about analyzing regional health and healthcare issues with drill-down to census tract and other sub-county geography.

Join us in a Data Analytics Web Session where we review and discuss use of tools and resources like those covered in this section.

About the Author
— Warren Glimpse is former senior Census Bureau statistician responsible for innovative data access and use operations. He is also the former associate director of the U.S. Office of Federal Statistical Policy and Standards for data access and use. He has more than 20 years of experience in the private sector developing data resources and tools for integration and analysis of geographic, demographic, economic and business data.

Healthcare Demographic Economic Analytics

Healthcare providers and the healthcare delivery system are challenged to determine what resources to make available at what locations and when. Assessing supply-side characteristics of the healthcare market is difficult at best. Current data on locations and capabilities of hospitals, ambulatory health care services (physicians, dentists, other healthcare practitioners, etc.), nursing and residential care facilities, and social assistance are multi-sourced and challenging to integrate.

As the population ages, migrates and otherwise changes, healthcare needs change by location, type and in other ways. Current small area demographics of these demand measures are not readily available — when knowing about changes in demand over the next several years is even more important. Changing economic circumstances and issues with insurance coverage affect the ability to pay and the demand for various healthcare resources.

Healthcare Analytics
This section provides an overview of the healthcare analytics focused on California. Resources and applications reviewed here can be emulated for other states and regions. The purpose of this section is to illustrate how a set of diverse, multi-sourced, healthcare supply and demand attributes can be organized for visual and geospatial analysis. See more details in related Web section.

Visual Analysis of Facilities, Characteristics and Patterns
Geographic Information System (GIS) resources can help decision-makers and stakeholders more easily understand and collaborate on healthcare issues that are difficult to analyze using spreadsheets and tables. A few examples:
• Relating Medically Underserved Areas (about MUAs/MUPs) to neighborhoods by economic prosperity.
• Relating locations of healthcare facilities (hospitals, clinics) to MUAs?
• Relating MUAs relate to Health Professional Shortage Areas (about HPSAs).
• Determining neighborhoods with highest need for healthcare services.
Get answers to these types of questions using multiple layers in a GIS project.

The following view of the San Diego area and shows a mix of healthcare related demographic-economic characteristics. The cross-hatched pattern areas have been designated as Medically Underserved Areas (MUAs). Patterns of economic prosperity (median household income by block group) are shown by color patterns as highlighted in the legend at left of map view. It is easy to see where the MUAs are located. Many MUAs are located in areas with medium to higher economic prosperity. Locations of primary care facilities, shown by square markers, can be viewed contextually.


Click graphic for larger view.
View developed using CV XE GIS and California DMI GIS Project.

Using GIS resources, the map views can be displayed in different ways to accomodate the needs of geographic and/or subject matter focus. Zoom-in or out for a broader or more focused view. Label features of interest (e.g., hospital names). Click layers on or off (in legend panel at left of map panel) to view geographies or locations of specific interest. Add other data such as geocoded patient or incident data.

Additional views shown below, from the same GIS project, illustrate some of these application views. Map views are just one part of the GIS resource benefits. Query tools can be used to highlight only locations of geographies that meet certain criteria, such as hospital bed capacity.

Statewide Hospitals and Primary Care Facilities

Hospitals and Primary Care Facilities: Zoom to Southern California

San Diego Area: Medically Underserved Areas

San Diego Area: Healthcare Professional Shortage Areas

Developing Your Healthcare Analyses
GIS tools and selected demographic-economic shapefiles shown above are available at no fee to ProximityOne User Group members. Join now, there is no fee. Add your data. Examine different geographies. Extend healthcare analytical and collaborative decision-making.

Examining Life Expectancy by County

Life expectancy in the United States in 2007 ranged from 65.9 to 81.1 years for men and 73.5 to 86.0 years for women. When compared against a time series of life expectancy in the 10 nations with the lowest mortality, U.S. counties range from being 15 calendar years ahead to over 50 calendar years behind for men and 16 calendar years ahead to over 50 calendar years behind for women. Between 2000 and 2007, 80% (men) and 91% (women) of U.S. counties fell in standing against this international life expectancy standard. These are among the findings reported in Population Health Metrics.

This section reviews interactive tools and resources that you can use to examine county life expectancy and related data.

Male Life Expectancy by County, 2007

County Life Expectancy Interactive Table
Use the Web interactive table to view, compare, analyze the U.S. by county level data from the above study in combination with related demographic-economic measures.

The following graphic illustrates how the table can be used to examine life expectancy patterns by county. A query is used to select only Charlotte NC-SC metro counties, Each row shows data for a county. The 2000 and 2007 life expectancy data are shown at right in the graphic,

Visual Analysis using GIS Resources
Use GIS tools to visually examine life expectancy patterns. Create thematic pattern maps such as the male life expectancy by county pattern map shown above or corresponding female pattern map shown below. Members of the ProximityOne User Group may download and use the county life expectancy GIS project to develop maps like these. Zoom into regions of interest. Add other layers. Label the maps as desired. Use other subject matter to develop related pattern views. Modify the legend defining life expectancy intervals.

Female Life Expectancy by County, 2007

Healthcare Analysis and Situation & Outlook
The ProximityOne Situation & Outlook (S&O) Program is a combined database and interpretive resource that you can use to better understand the existing healthcare situation, find out how area demographic-economic conditions are changing, and assess how changing conditions might impact various components of the healthcare infrastructure.

Support Using these Resources
Learn more about healthcare geographic-demographic-economic data, patterns and related analytical tools. Join us in a Decision-Making Information Web session. There is no fee for these one-hour Web sessions. Each informal session is focused on a specific topic. The open structure also provides for Q&A and discussion of application issues of interest to participants.

Healthcare Sector Demographic-Economic Characteristics

As of the first quarter 2013, private sector healthcare and social assistance sector (NAICS 62) accounted for approximately 13.3 percent of total U.S. payroll and 15.8 percent of total U.S. employment.  The average weekly wages were $836 in this sector compared to $995 for all industries (based on BLS/CEW data). About NAICS. About NAICS 62.

Much of the healthcare marketplace is now dominated by confusion with exceptional uncertainty and risk.  Businesses and stakeholders seeking to understand the what, when and where of change might impact their markets and affect them, their clientele and the marketplace.  This section reviews selected geographic, demographic and economic data, mainly from  the Federal statistical system, that can help reduce uncertainty and risk through data-driven decision-making.

Selected U.S. National Scope Data Resources
Quarterly Census of Employment and Wages (CEW)
Data about healthcare sector business activity by NAICS
Strengths
… quarterly time series; most recent data available; county level data;
… 6-digit NAICS detail; based on employer reported data
Limitations
… difficult to access and use; extensive suppression
… suppression: data withheld to avoid release of confidential information
Access
Bureau of Labor Statistics
County Business Patterns (CBP)
Data about healthcare sector business activity by NAICS
Strengths
… annual; county and ZIP code data; based on employer reported data
Limitations
… most recent data are too dated; suppression
… suppression: data withheld to avoid release of confidential information
Access
Census County Business Patterns
Metro Gross Domestic Product (GDP)
Metro data on the characteristics of healthcare sector as GDP component
Strengths
… annual; per capita real GDP time series; data for each metro;
Limitations
… suppression
… suppression: data withheld to avoid release of confidential information
Access
Metro GDP
Area Health Resources Files (AHRF)
HRSA integrated source of health-related data
Strengths
… annual; county; multi-sourced; wide ranging subject matter
Limitations
… limitations on use and redistribution
Access
HRSA ARF
American Community Survey (ACS) Summary Data
Data about the population: employment by industry; disabilities; insurance
Strengths
… annual; county to block group data;
Limitations
… smaller areas: data are dated
Access
American Community SurveyACS 2012
ACS Public Use Microdata Samples
Data about the population: user develops custom estimates
Strengths
… annual; enables custom demographic estimates
Limitations
… smallest area of estimation: PUMA; 100,000 population or more
Access
Public Use Microdata Samples
Health Insurance
Health insurance data based on
Current Population Surveys Annual Social and Economic Supplement (CPS ASEC)
Survey of Income and Program Participation (SIPP).
Strengths
… annual; enables custom demographic estimates
Limitations
… larger geographic areas
Access
Census Bureau Health Insurance Data
Demographic-Economic Projections
Projected data about the population and businesses
Insights into how age-gender-race groups will change in future
Strengths
… annual projections of population by single year of age to 2060
… county level data
Limitations
… estimates based on assumptions and models
Access
5 year estimates & projections2060 projections
Clinic and Hospital Facilities
Establishments/locations of healthcare provider facilities
Strengths
… establishment location data
Limitations
… incomplete universe; limited subject matter
Access
HHS Medicare
TIGER/Line Geographic Shapefiles
Shapefiles to link/associate many subject matter data listed here.
Strengths
… most national scope statistical and political geography
… enables visual and geospatial analysis
Limitations
… no subject matter data
Access
2013 TIGER/Line Shapefiles
About NAICS
The North American Industry Classification System (NAICS) is the statistical standard used in classifying business establishments for the purpose of collecting, analyzing, and publishing statistical data related to the U.S. business economy. NAICS was developed under the auspices of the Office of Management and Budget (OMB), and adopted in 1997 to replace the Standard Industrial Classification (SIC) system.
About the Healthcare and Social Assistance Sector
The Health Care and Social Assistance sector includes both health care and social assistance because it is sometimes difficult to distinguish between the boundaries of these two activities. Industries in this sector are on a continuum starting with those establishments providing medical care exclusively, those providing health care and social assistance, and those providing only social assistance. Services provided by establishments in this sector are delivered by trained professionals. Industries in the sector share commonality of labor inputs of health practitioners or social workers with requisite expertise. Many industries in the sector are defined based on the educational degree held by the practitioners included in the industry.
Ambulatory Health Care Services: NAICS 621
– Offices of Physicians: NAICS 6211
– Offices of Dentists: NAICS 6212
– Offices of Other Health Practitioners: NAICS 6213
– Outpatient Care Centers: NAICS 6214
– Medical and Diagnostic Laboratories: NAICS 6215
– Home Health Care Services: NAICS 6216
– Other Ambulatory Health Care Services: NAICS 6219Hospitals: NAICS 622
– General Medical and Surgical Hospitals: NAICS 6221
– Psychiatric and Substance Abuse Hospitals: NAICS 6222
– Specialty (except Psychiatric and Substance Abuse) Hospitals: NAICS 6223
Nursing and Residential Care Facilities: NAICS 623
– Nursing Care Facilities: NAICS 6231
– Residential Mental Retardation, Mental Health/Substance Abuse Facilities: NAICS 6232
– Community Care Facilities for the Elderly: NAICS 6233
– Other Residential Care Facilities: NAICS 6239Social Assistance: NAICS 624
– Individual and Family Services: NAICS 6241
– Community Food/Housing, and Emergency/Other Relief Services: NAICS 6242
– Vocational Rehabilitation Services: NAICS 6243
– Child Day Care Services: NAICS 6244

An upcoming section will review tools and methods to integrate and use these data.