MEPS

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Stata tutorial: Adding the 95% Confidence Interval to a Two-way Line Plot

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I created a tutorial on how to add the 95% CI to a two-way line plot in Stata. I use the “connected” command to generate a line plot in Stata, and then I added the 95% CI to each value. Surprisingly, Stata does not have a native feature to allow users to generate these 95% CI on a two-way line plot.

I used the AHRQ Medical Expenditure Panel Survey (MEPS) database for the motivating example. In this tutorial, we plotted the average total healthcare expenditure from 2008 to 2019.

I build this tutorial on Stata, but I used R Markdown to write the tutorial. The R Markdown code is located in my GitHub site (Stata - Line plot with 95% CI tutorial).

You can find the tutorial on my Github site and RPubs page.

I used Stata SE 17 to build this.

Medical Expenditure Panel Survey (MEPS) Guide - Part 1

INTRODUCTION

Medical Expenditure Panel Survey (MEPS) is a publicly available dataset on healthcare expenditures that is representative of the US population.

The MEPS homepage contains vital information about the methods used to validate household responses and guides on how to properly use these data for research or exploration. You can learn about MEPS in its background section.  

MEPS data files are available for download here. The most important file is the Full Year Consolidated Data Files, which contains the data for unique household responses on their characteristics and expenditures. These data are great practice for those interested in learning more about MEPS. Each of the Full Year Consolidated Data Files contain information about the data in the form of Documentation and Code Books. For example, the 2017 Full Year Consolidated Data Files Documentation and Code Book are located here.

If you area a Stata user, there are Stata programming statements available to copy and paste into a Stata *.do file. These programming statements are used to transform the MEPS data into a *.dta file that is usable by Stata. Follow the instructions in the programming statement to properly transform the MEPS data. This is similar to an extract-transform-load (ETL) process.

MEPS has a library of reports that uses its data. You can search for topics using their search engine. For example, Report #43 describes the annual opioid usage among adults treated for conditions associated with pain versus other conditions from 2013 to 2015.

Other examples of MEPS data being used in research include the following:

  1. Hamad R, Niedzwiecki MJ. The short-term effects of the earned income tax credit on health care expenditures among US adults. Health Serv Res. 2019 Dec;54(6):1295-1304. doi: 10.1111/1475-6773.13204. Epub 2019 Sep 30.

  2.  Watanabe JH. Examining the Pharmacist Labor Supply in the United States: Increasing Medication Use, Aging Society, and Evolution of Pharmacy Practice. Pharmacy (Basel). 2019 Sep 19;7(3). pii: E137. doi: 10.3390/pharmacy7030137.

  3.  Bounthavong M, Li M, Watanabe JH. An evaluation of health care expenditures in Crohn's disease using the United States Medical Expenditure Panel Survey from 2003 to 2013. Res Social Adm Pharm. 2017 May - Jun;13(3):530-538. doi: 10.1016/j.sapharm.2016.05.042. Epub 2016 May 20.