Tuesday, June 27, 2017

HealthLandscape Tip: Isolating a Geography

One of our most frequent questions from users is, “Can I make a map that shows only my state or only my county?”  While there is not an official way to isolate an area like this, we did come up with one way you might do it.  Keep in mind that we do not recommend isolating geography in this manner because state and county boundaries, while they have implications for health policy and health spending, are just imaginary lines.  Things occur just on the other side of those lines that may affect the health of the area you are highlighting.  This includes providers from whom people in your area of interest may be seeking health care services, environmental effects, etc.  That said today, I'd like to share a technique for isolating a geography in our Population Health Mapper using the QuickThemes tool.  The same steps can be taken in any HealthLandscape tool.

The QuickThemes tool in the HealthLandscape platform allows users to color in states, counties, ZCTAs, etc. based on data in a table.  Each area that is included in your table will be colored in based on the value in the column you choose to map.  For example, if I had a data table like this that has a list of areas at least one column of data that has a number, percent or qualitative data in it:

Qualitative Information
District of Columbia
West Virginia

With this table, I can add color to the map for these six states based on the information in either the number, percent or qualitative information columns.  The process I describe below takes advantage of this by instructing you to add a column of data with identical values for all the areas you want to mask.  Let’s get started.

The Population Health Mapper first prompts you to select a state; for the purposes of this demonstration I will choose Maryland. When you do this, the Mapper will zoom you to the area you have selected and automatically center the map for you, as it did for me.

Next, I need a list of states with their respective FIPS codes. FIPS stand for Federal Information Processing Series. The US Census Bureau maintains several pages related to FIPS codes, including an explanation of the codes and tables with state FIPS codes and county FIPS codes.


Using the state table provided by the Census Bureau, I will cut and paste the data into an Excel spreadsheet and delete the row for Maryland. By deleting Maryland from the list, it will create a “hole” in my map layer that I am adding.  In order to have the other states colored in, I have to add a column and insert an identical value to each state. For the purposes of this blog, I will name my column "Value for Monochrome" and will insert the numeral 5 for each state, but keep in mind that these values will appear on your map, so you may want to name them things and select values that blend in with the theme of your map better.


Back in the Population Health Mapper, I will start the QuickThemes tool by going to the top right "Tools" button (gray), clicking it and selecting "QuickThemes".  The QuickThemes tool will open and be added to the Tools Accordion on the right. Read the instructions and then go back to the spreadsheet to highlight and copy the rows and columns that have the information you want to include on the map; this will include your header row.  When ready, in the QuickThemes tool click the "Click here to begin" button to get to the screen where you will paste your data.

Click anywhere in the white area and then hit Ctrl+v or Command+v to paste your data.


You will have to give the QuickThemes tool some information.  First , tell it the type of geographic code you are using; I will select "State by FIPS".  You will also have to tell it which column in your dataset has the geographic identifiers in the ID selection box.  In my case, I will select FIPS Code. Last, under Group/Category selection box, select the column that has the single value in it for all states, in my case, "Value for Monochrome". Finally, hit the blue "Load" button.  Hint: If you forget to do the Group/ Category selection before you hit load, you can always do it later.

Using the Zoom Bar at the top left I will zoom to a good level to view states and grab the map with my mouse (left click and hold) and drag the map so that Maryland will be centered. The resulting map has my state of focus, Maryland, uncolored (and ready for the application of points, labels, and other data) and the surrounding states are visible but monochromatic in the background. Note this method can be applied within a state at the county level using the county FIPS codes.

I hope this is helpful in your work. You can contact me for assistance using the chat feature on this tool or the "Contact Us" feature if you are working in the UDS Mapper.

Keith Gardner
User Engagement Specialist


Wednesday, June 7, 2017

The Census Counts: Notes on the critical importance of the Census

Earlier this month, the Director of the Census Bureau abruptly retired after many decades of service to the Bureau.  There is much speculation and concern due to the suddenness of the Director's departure, which, combined with expected shortfalls in funding required for the coming 2020 Census, raises real concerns for the agency’s ability to meet its Constitutionally required obligations.  While it will be some time before we learn the full impact of this sudden leadership upheaval, it would do us well to remind ourselves why we care about the Decennial Census and all the related activities of the Census Bureau.

The Census has been conducted every ten years since 1790, becoming increasingly complex and expensive with each decade.  In 2010, the Census cost a record $13 billion dollars and employed over 600,000 temporary workers.  The Decennial Census is routinely referred to as the largest peacetime activity of the United States Government.  There are shelves full of books explaining the importance and utility of the Census (and the related annual American Community Survey), and I want to focus on what I consider to be the most critical.

Geospatial analysis depends on an accurate Census. HealthLandscape is a web-based platform that allows users to visualize and analyze their data spatially.  To aid in that analysis, we provide a comprehensive library of demographic, social, behavioral, economic, and health-rated data.  Two rich sources of data for the data library are the decennial Census and American Community Survey, to name just a few of the incredible data programs from the Census Bureau.  Geospatial analysis would be far less valuable and provide fewer insights without the ability to compare users’ data to related Census data.

Business and Commerce rely on an accurate Census.  It’s been said that “What gets measured gets managed”.  Census data, and projections derived from these data, are core components of business planning in the United States. Retail outlets use the data to inform decisions for opening (or closing) brick-and-mortar locations.  Transportation planners use the information to plan new roads and highways.  The location of regional and larger airline network hubs is driven by the size of the population and changes that can be anticipated.  School districts use the information to determine whether to build new buildings or combine grades across multiple buildings to best meet the growing (or shrinking) student populations.  

Federal Expenditures require an accurate Census.  The allocation and redistribution of Federal tax revenue is based on Census counts for states, counties, cities, tracts and school districts, to name a few.  As such, Census counts equate to economic power.  Local, state, and national government organizations recognize this and work hard to make sure the decennial Census and related annual surveys are complete and accurate.  A recent Brookings Institution report shows that under-representation in the Census (people not completing the decennial Census form) costs states between $382 (Utah) and $2,564 (Vermont) PER PERSON in annual tax revenue redistribution.  For example, the State of Ohio, with a population of 11.6 million people has an expected $814 potential per capita loss for each person missed in the Census.  A one percent undercount would mean nearly 95 million dollars in lost federal expenditures (money returning to the State) EACH YEAR.  

Democracy and political franchise demands an accurate Census.   At a basic level, completing a Census form and being counted is every bit as important as fulfilling your obligation to vote.  The distributions of representatives at the state and national level are driven by Census counts.  As a result of the 2010 Census, the State of Ohio lost two seats in the US House of Representatives, while Texas gained four, with other states gaining and losing as well.  At the end of all the work, completing the Census form and being counted represents YOUR most basic level of political power.

Since the original 1790 Census directed by Thomas Jefferson, the United States has been fortunate to have a high-quality, apolitical snapshot of the US population.  As we move into the planning and testing phases for the 2020 Census, it's important that we remind ourselves of the critical value of this decennial effort.

Remember: If you aren’t counted, you don’t count.

Mark A. Carrozza, MA


Tuesday, May 23, 2017

The American Community Survey

The third American Community Survey (ACS) Data Users Conference took place May 11th and 12th, 2017, at the United States Patent and Trademark Office in Alexandria, Virginia. The meeting, organized by the Population Reference Bureau, brought the ACS data users together to discuss research, trends, resources, and analysis. Sent to 3.5 million addresses each year, the ACS is an ongoing survey designed to produce detailed, small area estimates on population and housing and disseminated in one-year and five-year estimates. This is in contrast to the decennial census, taken every 10 years, which provides official counts and reflects only a single point in time. The ACS covers four main topics areas; social variables such as citizenship status, place of birth, and veteran status; demographic variables like age, race, sex; economic variables like commuting and place of work, health insurance coverage, and poverty status; and housing variables, including occupancy/vacancy status, vehicles available, and computer and internet use. These examples are only a subset of the 35+ topics that comprise 1,000 tables and 11 billion estimates. The ACS data are available at a number of geographic levels from the national level down to the block group level, to cover a total of 930,000 geographic areas.
These are some of the highlights of the conference as I saw them:
  • My session on our Social Determinants of Health Mapper;
  • Learning about the American Community Survey Office (ACSO) which publishes papers and has about 300 reports on the research that they conduct using ACS data;
  • The ACS is continuously re-evaluated and retested and to improve response rate and respondent experience, including removing questions and potentially moving to a more laid back tone; and
  • They are considering adding an open-ended question that allows the respondent to share anything else they think is important.
For people like me, who regularly consume these data to put into the HealthLandscape tools, I was most interested to learn is that there is an effort underway to improve the way Census products are delivered.  Also present, was a representative from the Center for Enterprise Dissemination Services and Consumer Innovation (CEDSCI), which looks at transforming and improving the way Census products are delivered. One of the key takeaways from their talk was that they’re aiming at making the data experience much like shopping with Amazon.  Users will add data to a shopping cart and based on the search and selection, recommendations for other datasets and products will be provided. We also saw a beta version of a new Census site (data.census.gov), which will help them to transition from many dissemination platforms to a single site.
HealthLandscape has been using ACS 5-year estimates since the first set of data was released. These data are used in various tools including Community HealthView, the Social Determinants of Health Mapper, the Population Health Mapper, and the UDS Mapper. With each new ACS release, HealthLandscape processes a selection of tables for inclusion in these mapping tools at the state, county, census tract, ZCTA, and block group levels.
These tools can be accessed at:
For more about our mapping tools we invite you to attend one of our free webinars where you can learn how to use them. You can find an upcoming webinar and register to attend here:
We cover the data included and we welcome your questions in these interactive forums.
Dave Grolling
GIS Strategist


Wednesday, May 10, 2017

We were SDOH before SDOH was cool

Here at HealthLandscape, we have been developing online geospatial analytic tools for more than 10 years and that entire time, we have focused on the Social Determinants of Health (SDOH).  Our inter-disciplinary team of sociologists, informaticians, geographers and training specialists regularly work side-by-side with providers, researchers and social service organizations to synthesize data and build custom tools to meet their analytic needs.  Most of our mapping tools incorporate social determinants of health and other community, contextual information ensuring that workforce, utilization or other client-provided data can be viewed with potentially explanatory details and resources.

Our first ever (and continually updated) tool, Community HealthView, contains a comprehensive library of data one can use to predict health outcomes based on poverty status, crime, education levels and much, much more.  Data are available via map and data table and can be exported by the user.  The user can change the visualization of the data as well.  Community HealthView can be found at www.healthlandscape.org and as an add-on tool in most of our mapping tools.

More recently we have built tools that allow users to “cold spot” areas based on SDOH.  Proposed by Jack Westfall, cold spotting is identifying areas that have poor values for multiple or overlapping SDOH.  Our tools that allow this type of analysis are the UDS Mapper’s Population Indicators Tool, the Social Determinants of Health Mapper, Population Health Mapper and our newest SDOH tool, the 500 Cities Project Mapper.  You’ve read about these in our recent blogs.  These tools can be found at:

Our experience developing geospatial tools and our continued collaboration with primary care researchers have opened new avenues for research and development as well.  As health system transformation is occurring, more and more people are embracing the idea of SDOH and looking for ways to incorporate these data into patient records.  The determinants data that we have been collecting over the past 10 years form the basis of a community profile for patients that will help health care teams, researchers and administrators understand the factors that may influence success and failure of treatment plans; see the factors that may be contributing to poor outcomes and high costs; and address these non-clinical factors either at the patient, practice or community level (with partners who focus on these issues) will improve health outcomes and improve population health.

For more about our mapping tools we invite you to attend one of our free webinars where you can learn how to use them. We cover the data included and we welcome your questions in these interactive forums.

  • For the UDS Mapper

Jennifer Rankin
Senior Manager for Research and Product Services

Monday, May 1, 2017

Your User Engagement Specialist: Keith Gardner

In March of this year I joined HealthLandscape as the new User Engagement Specialist. I help the users (you) with use of the HealthLandscape mapping sites, including the UDS Mapper. Aside from providing technical assistance, I am a main trainer for these resources and create support materials like user guides and tutorials. I am responsible for social media outreach; I tweet, post to Facebook and LinkedIn, and also publish blogs, like this one, written by members of the HealthLandscape team.
A bit about myself: I have a customer service background having worked for several data-intensive software firms in the DC Metro area. I gravitated to training, over the phone, via chat, web-sharing tools, and in person. My training track led me to producing live and on-demand webcasts for firms like DHL and Visa. Later, I became a project manager and continue to use project management principles in my day-to-day work. My role at HealthLandscape is a return to training that I really missed.
In past lives I served in the US Army Infantry and as a Trader Joe’s Crew Member. I have a Bachelor of Arts degree from the University of Southern Maine with a major in Philosophy.
Weekends will find me enjoying my family. My three sons keep my wife and me busy. I volunteer as a Cub Scout leader (mine and other boys!) and enjoy most outdoor activities.
So what does this mean for you? Well, I’m here to help you with the HealthLandscape suite of mapping tools and hope that, if you haven’t already, you will attend one of our free webinars.
For the UDS Mapper (www.udsmapper.org) you can register for a webinar here:
For other HealthLandscape tools (like the HealthLandscape Project 500 Cities Mapping Tool) register here:
Questions? Comments? Suggestions? You can contact us by emailing support@healthlandscape.org
You can also contact me directly at kgardner@healthlandscape.org and if you are willing will share a little about that project you are working on with our tools, I’d love to know more. I look forward to working with you and hope you make use of your User Engagement Specialist!

Wednesday, April 12, 2017

HealthLandscape population data tools: Now featuring RWJF 2017 County Health Rankings and more

The Robert Wood Johnson Foundation recently released their 2017 County Health Rankings (CHR), which provide a wealth of health outcome and social determinants of health data for the majority of US counties. These data are now available in HealthLandscape’s Community HealthView data library, where you can create thematic and threshold maps to visualize the geographic distribution of each of these measures.  To access the CHR data in Community HealthView, type “RWJ” into the search box and explore the data by the various categories, which include Demographics, Health Behaviors, Health Outcomes, HealthCare, and the Social & Economic Environment.
Be sure to also explore our other interactive population health mapping tools, which include the following:
The HealthLandscape Project 500 Cities Mapping Tool –allows users to layer health outcome, behavior, and prevention measures at the census tract level for the largest 500 cities across the US. The data come from the 500 Cities Project, which is a collaboration between the CDC, the Robert Wood Johnson Foundation, and the CDC Foundation to create small area estimates for health outcomes, risk factors, and preventive care. For more information about the Project 500 Cities data, see https://www.cdc.gov/500cities/.
The Population Health Mapper – allows users to layer health outcomes and social determinants for the majority US counties based on the CDC’s Community Health Assessment for Population Health Improvement guide, which lists the most frequently recommended health outcome and determinant measures. To access the CDC’s guide, see https://wwwn.cdc.gov/CommunityHealth/PDF/Final_CHAforPHI_508.pdf.
The Social Determinants of Health Mapper – allows you to layer education, language, poverty, and income census measures at the census tract level for US counties and metropolitan areas.
To learn more about these tools visit www.healthlandscape.org.  HealthLandscape provides regular webinars to train users on our tools.  The list of upcoming webinars including registration links can be found here:  http://www.healthlandscape.org/webinar-training.cfm.

Wednesday, January 25, 2017

500 Cities Mapping Tool

HealthLandscape Launches a New Mapping Tool
Using Census Tract-Level Data from the CDC 500 Cities

Small area estimates of health and health outcomes are difficult and prohibitively expensive to acquire.  National data systems such as the National Health Interview Survey and the Behavioral Risk Factor Surveillance System do not collect samples large enough to produce detailed small area data.  And while state and local efforts like the California Health Interview Survey and the Greater Cincinnati Community Health Status Survey are important efforts, most communities find these projects to be cost prohibitive.

The ambitious 500 Cities Project was launched by the Centers for Disease Control and Prevention (CDC), along with the Robert Wood Johnson Foundation, and the CDC Foundation. Its purpose is to allow cities and local health departments gain a better understanding of the health issues and geographic distribution of health measures in their municipal boundaries.

Washington, DC
With the Project 500 Cities Mapping Tool, users can map synthetic small area estimates for chronic disease risk factors, health outcomes, and clinical preventive services at the Census Tract level for the largest 500 cities across the U.S. (To ensure inclusion of all states, 3 cities from Vermont, West Virginia, and Wyoming were included in the 500 list).

The Project 500 Cities Mapper allows users to select 27 metrics from three major categories (Unhealthy Behaviors, Health Outcomes, and Prevention) and use a slider bar to set thresholds. By default, thresholds are set at values that represent national benchmarks.

The tool will highlight those counties that are outside of the national benchmark, or will incrementally shade or remove counties depending on how the user modifies the thresholds for selected indicators.  Darker gradations of color will indicate which counties are outside of the established thresholds for multiple indicators.  Users can also view a histogram that shows the number of counties outside of thresholds by the number of indicators, allowing users to quickly filter by the number of indicators that are outside of the established thresholds.

In these two examples, we compare the combined distributions of Binge Drinking, Smoking, and lacking Leisure Time Physical Activity as markers of health risk for Chicago and Seattle.

Join us for a a detailed webinar to learn more about
the Project 500 Cities Mapping Tool