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I have updated the graph to include the 2016 numbers. These estimates of health insurance coverage come from Table 1 of Health Insurance Coverage in the United States: 2016, Current Population Reports, a U.S. Census Bureau Report. The previous numbers were from Table 1 of the previous report.
Adding nine numbers to a graph does not seem like a big deal. But it is worth discussing the process. The most important part is to decide whether to incrementally add the nine numbers, or replace everything. Sometimes data is updated for previous time periods so it is important to check. As there were no changes in the new table for 2013, 2014 and 2015, I chose to append the new numbers. I created a new R data frame from the original data with the new data. I then reran the plot_ly code with the new data source to make the interactive graph.
The report cites the Current Population Survey Annual Social and Economic Supplement (CPS ASEC) as the source of this table. Other tables such as break-outs by state in the report use the American Community Survey (ACS), a larger on-going survey. The report states that “The key purpose of the CPS ASEC is to provide timely and detailed estimates of economic well-being, of which health insurance coverage is an important part.” The ACS in contrast “is an ongoing survey that collects comprehensive information on social, economic, and housing topics.” The Census Bureau has extensive documentation of the methodology for these studies available on-line.
Because one study is an annual study and the other an annual summary of an on-going study, the definition of uninsured is slightly different. The CPS ASEC defines uninsured as no insurance at any time in 2016. The ACS asks about current insurance status. If someone lost their insurance in November, they would still be counted as insured for the CPS ASEC because the interview took place in early 2017. If they were interviewed in November 2016 for the ACW they are considered uninsured.
Georgette Asherman, March 21, 2018
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