Graphical Representations of Mortality Data With Confidence Intervals
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Mortality data are the most complete, standardized, and easily available—if not the only—data set for the epidemiological assessment of the health problems of a state or a county. Specific health problems of a state can be identified by comparing the cause-specific mortality rate of the state with a benchmark, such as the average mortality rate of the United States or of a state with similar geographic or sociodemographic characteristics. With the help of data visualization tools, stakeholders in health policy decision making can easily customize the required information.1,2
The use of a sequential color scheme (color ramp) to differentiate mortality rates between states in a choropleth map is common. However, this approach might result in the misinterpretation of differences in mortality rates between states. Two states with different color shades might not actually have a significant difference in mortality rates. The mortality rates estimated for a state with a small population would be less stable and have higher 95% confidence intervals (CIs). Studies have suggested calculating 95% CIs when comparing the mortality rates of states or counties for assessing needs or ranking.3,4 Therefore, we used Tableau, a widely used self-service business intelligence software, to create a data visualization dashboard of US states’ coronary heart disease mortality rates with 95% CIs (https://public.tableau.com/profile/robert.lu#!/vizhome/USACHDJun32016/Dashboard). …