NAMCShiny

An interactive web application to explore health trends based on 2003-2010 National Ambulatory Medical Care Survey data

Big medical datasets are rapidly being generated and made publicly available, providing numerous opportunities for computational analysis and bioinformatics in health policy. Visual inspection and exploration of the data are useful for hypothesis generation and trend identification, though generating such visualizations is often time-consuming and cumbersome. Here, we present NAMCShiny, an interactive web application that allows users to visually inspect for trends in the reasons for medical visits from 2003 to 2010 while stratifying on patient demographic information such as sex, race, and age using data from the National Ambulatory Medical Care Survey. Big medical datasets are necessary to guide the development of future evidence-based health policies. However, forming meaningful interpretations of this data requires understanding and controlling for several key challenges and limitations including, but not limited to, biases, non-random sampling, confounders, and missing data.

We encourage further exploration of the NAMCS data to identify potential trends in public health and guide the development of future evidence-based health policies.

Usage

The NAMCShiny application is available online at https://jefworks.shinyapps.io/NAMCShiny/

The NAMCShiny application can also be launched on your computer within the R environment using the command shiny::runGitHub("NAMCShiny", "JEFworks")

We provide additional NAMCS datasets converted into ready-to-use RData files on github: https://github.com/JEFworks/NAMCShiny