The following visualization demonstates some simple and powerful capabilities of Tableau 5.1. It was published on Tableau's blog using the new free Tableau Public application, by Ross Perez. His entire blog entry is available here.
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Wednesday, February 03, 2010
Monday, February 01, 2010
Veterans Health Administration Inpatient Satisfaction by Race
The Veterans' Health Administration health system is known for the consistent and high-level of care it is able to provide to American military veterans. Like any exemplary organization, it routinely monitors its performance in order to maintain very high standards for health outomes and patient satisfaction. Summary data on many of these recent efforts is available on Data.gov. Much of this information is summarized measures by VHA facility, which are organizaed in what the VHA calls VISNs. Each VISN may have one or more facilities under its umbrella.
The data is available in .csv format, making it easy to use in many analytical tools. For the following visualization we used the VHA_Facility_Quality_and_Safety_Report_Patient_Satisfaction.csv, which reports on overall inpatient satisfaction, stratified by race.
The Tableau visualization presents a dot plot of average satisfaction score reported for each facility in the dataset, with separate dots for each race. The facilities are listed in descending order by the average score reported for inpatient satisfaction among surveyed African-American patients. This relates to the major findings of the source survey, which found significantly different satisfaction ratings among African-Americans when compared to White patients and others. African-American patients were found to be generally less satisfied with their inpatient experience. The ordered list includes the state and VISN dimensions and for filtering on them as a way of drilling down to ask further questions, such as what is the distribution of satisfaction ratings within a state where more than one facility exists. The visualization makes it possible to quickly focus on one or more VISNs and to see whether satisfaction varied by state within a VISN.
The visualization also marks the average, and 2nd throiugh 3rd quartile ranges for the faciltiies included. Therefore, when the facilities list is filtered these measures change as well.
The accompanying report includes a detailed discussion of the findings on patient satisfaction, starting on page 15. It should help explain the context for the wide range of average patient satisfaction ratings and differences by race that this visualization highlights. The context includes the complexity of care offered at each facility, regional, cultural, and even faith-based norms and expectations of the served populations.
The data is available in .csv format, making it easy to use in many analytical tools. For the following visualization we used the VHA_Facility_Quality_and_Safety_Report_Patient_Satisfaction.csv, which reports on overall inpatient satisfaction, stratified by race.
The Tableau visualization presents a dot plot of average satisfaction score reported for each facility in the dataset, with separate dots for each race. The facilities are listed in descending order by the average score reported for inpatient satisfaction among surveyed African-American patients. This relates to the major findings of the source survey, which found significantly different satisfaction ratings among African-Americans when compared to White patients and others. African-American patients were found to be generally less satisfied with their inpatient experience. The ordered list includes the state and VISN dimensions and for filtering on them as a way of drilling down to ask further questions, such as what is the distribution of satisfaction ratings within a state where more than one facility exists. The visualization makes it possible to quickly focus on one or more VISNs and to see whether satisfaction varied by state within a VISN.
The visualization also marks the average, and 2nd throiugh 3rd quartile ranges for the faciltiies included. Therefore, when the facilities list is filtered these measures change as well.
The accompanying report includes a detailed discussion of the findings on patient satisfaction, starting on page 15. It should help explain the context for the wide range of average patient satisfaction ratings and differences by race that this visualization highlights. The context includes the complexity of care offered at each facility, regional, cultural, and even faith-based norms and expectations of the served populations.
Saturday, January 30, 2010
Testing dashboard image embedding
This example is provided by the Financial Research Station (FRS). It illustrates how live, interactive Tableau Server views can be served up on a public web site for persons logged into a Tableau Server with a valid user name and password. If you are not logged into the FRS Tableau Server, you will see a Tableau Server login screen below. The user name is frsbeta and the password is mkt2010. Contact FRS at 212-981-2529 x13 for assistance, or visit their web site for more details.
Friday, January 22, 2010
Employment and Payroll Data Example from Tableau Public
In an effort to explore the possibilities for using visual data analysis software to make public data transparent, exploratory, and understandable, we are testing the use of Tableau Software. One excellent and award-winning source of examples of public data is the Data Center of the Hamilton County Regional Planning Commission (HCRPC) web site. The resources there include data from local and national sourdes, including county departments; state governments in Ohio, Kentucky, and Indiana; and many federal agencies like the US Bureau of the Census and the Department of Labor (Bureau of Labor Statistics). The breadth of subjects include physical and policy planning, population change, school performance, economic indicators, and much more.
The following example takes data from the County Business Patterns, that was published in the County Business Patterns 2006-2007 .pdf by the HCRPC.
The map in the upper left quadrant of the faceted analytic display (Stephen Few, Dashboard Confusion Revisited, March 2007) shows the number of employees encoded as the size of each bubble, and the number of employees per establishment (color) for each county within the CMSA. Hovering over any bubble reveals the overall average number of employees per establishment along with the name of the county and the URL for the official county presence on the internet. Clicking on any bubble in the map causes the associated data in each of the other panels of the display to highlight.
The following example takes data from the County Business Patterns, that was published in the County Business Patterns 2006-2007 .pdf by the HCRPC.
The map in the upper left quadrant of the faceted analytic display (Stephen Few, Dashboard Confusion Revisited, March 2007) shows the number of employees encoded as the size of each bubble, and the number of employees per establishment (color) for each county within the CMSA. Hovering over any bubble reveals the overall average number of employees per establishment along with the name of the county and the URL for the official county presence on the internet. Clicking on any bubble in the map causes the associated data in each of the other panels of the display to highlight.
Wednesday, January 13, 2010
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