National Provider Data Revealed - A Choropleth Map Analysis

At PokitDok, our guiding principle is to create products and services that enable The Business Of Health. To enable our customer facing products, like the PokitDok Marketplace, as well as our enterprise APIs, the PokitDok Platform, our data science team gathers data from numerous sources and turns it into valuable insight. Our newest data science hire, Alec Macrae, put together a series of analysis tools almost immediately after he started with us. Specifically, his tools allow the generation of choropleth maps from our data. What's a choropleth? To the Internet!

"choropleth map: A map that uses graded differences in shading or color (...) inside defined areas on the map in order to indicate the average values of some property or quantity in those areas."

--The Free Dictionary

These sort of visualizations have worked their way into the public consciousness recently - if you've seen a "red state/blue state" map of political views per geographic region, you were looking at a choropleth! This post will only serve as a quick introduction to the sorts of analysis possible. We'll be exploring this topic further in future posts.

Provider Credentials

Let's start with a simple example. What percentage of healthcare providers in each state are MDs? It turns out that we can answer this question quickly and intuitively with a choropleth.

Percentage MDs grouped by state
(click to enlarge)

The legend at the top right shows that darker colors indicate a higher percentage. So we see that Maryland has the highest percentage of MDs, followed closely by Virginia, Texas, Louisiana, and Alabama. Next, the same graph, but showing the percentage of dental surgeons - DDSes.

Percentage DDS grouped by state
(click to enlarge)

California is clearly a good place to maintain your smile. Let's move on to demographics about the providers themselves.

Provider Gender

In this next set of maps, we show percentages of male and female providers per state. Here's the men:

Male Doctors grouped by current state of practice
(click to enlarge)

And the women:

Female Doctors grouped by current state of practice
(click to enlarge)

Female providers seem to have a majority in Northeast and Midwest states, and, curiously, Alaska, while males dominate Utah and Idaho.


The first two examples graphed demographic information about providers. PokitDok is dedicated to price transparency, and the pricing data we've collected and curated can be inspected, much as the provider data above. For example, how much can you expect to pay for a chest CT scan across the country?

Average price for chest CT scan grouped by state
(click to enlarge)

And the following is for a more significant procedure - a hip replacement.

hip replacement cash price grouped by state
(click to enlarge)

These sample maps only scratch the surface of the sort of analysis and visualization that can be performed. If you had access to this sort of information, what kind of questions would you like to ask? Would analysis tools like this help you as a consumer, or a business? Let us know in the comments.

About Alec Macrae

Alec is a member of the data science team at PokitDok, based out of the company's San Mateo office. He enjoys using data, machine learning, and AI to solve problems, reveal insights, and build cool software.

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    • Lisa on October 9, 2014 at 11:53 am


    Cool maps - Just for my curiosity, I'd like to see if there is possible correlation between physician years of experience and cost.
    I'd also be curious to see which states would be hardest hit in 5-10 years with physician retirements due to age.
    And one more, I'd be interested in a possible correlation between hospital costs for a procedure and the amount of free or federally-subsidized care provided.

    1. Reply

      Superb questions. Stay tuned.

    • Michael Bolcerek on October 10, 2014 at 3:46 pm


    Would love to be able to drill down and see what are the cheapest counties or cities for CT scan or hip replacement. While I might drive to a different city, or even county, I likely would not drive to another state. I probably would continue to drill down to the specific clinic or doctor, and then look to see what insurance they accept, ratings on the health provider, etc.

      • Lolly on July 18, 2016 at 1:17 am


      Wow! Great to find a post with such a clear meegass!