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Biostatistics in a Health Services Environment

Aurora Baluja is MD in the Department of Anesthesiology, Intensive Care and Pain Management of the Hospital Clinico Universitario of Santiago de Compostela, and PhD candidate at the Forensic Medicine Unit of the University of Santiago de Compostela (Spain).

As a medical doctor involved in patient management, -in operating room and in the ICU-, every day I witness the huge load of data that has to be processed, interpreted, and stored. In this situation, Biostatistics and Bioinformatics support becomes greatly important to analyse trends and patterns, that  ultimately lead to improve patient care.

I do research about risk profiles of mortality in the ICU, and given the amount of data obtained, the task of reporting my results and ensure reproducibility became very time-consuming.

In this post I intend to comment on the main tools that helped me so much to overcome those obstacles:

  •  R: for me, the possibility of learning a statistical computing language to write and recycle scripts, was definitely the way. R is a powerful, open source programming language and software environment, that allows a full variety of analyses and… beautiful graphs.
  • RStudio: to find a good IDE  for R code was also important. Fortunately, Altea recommended me this easy-to-use, visual piece of cake, with integrated options to report code and results… Thanks!
  • R Markdown is a quick, easy method to write scripts and to report clean code and results, with some formatting options, in an HTML page. It is implemented in R-studio by the package “knitr”. Just one click away, you can generate a complete, dynamic report with text and graphics.
  •  LaTeX: the main reason for me to use LaTeX is not writing documents with beautiful symbols and equations, but to somehow link my R console to a document editor, in order to generate tables and reports, just like I do with R Markdown. For this, I need to use R-studio again,  and 4 more ingredients:
  1. A LaTeX distribution: I have installed TeX Live for Linux, and MiKTeX for MS Windows. A variety of templates, included often in distributions, make the first approach quite easy. Beyond the use of Sweave (see below), I became so fond of LaTeX that now it is my favourite text editor for documents, posters and slides!
  2. R Sweave is the link between R-scripts and LaTeX, making possible to write an entire LaTeX document with dynamic results from R commands embedded in it.
  3. Texreg: maybe the reason why I’ll never quit using LaTeX. Its magic begins after you have run several models of your data, and you are trying to see and compare *all* of them at a glance. It generates latex-formatted tables with your models, ready to paste into a LaTeX document. As a tip, I often use them preserving their \{tabular} environments and customising \{table} options to fit my document style.
  4. Xtable: another R package, that allows to print nice tables in LaTeX format.

I encourage those who haven’t used any of these tools, to give them a try… surely they will help you!

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2 thoughts on “Biostatistics in a Health Services Environment

  1. You’re very welcome, Aurora, but I will have to pass on your thanks to Hector who was the person to introduce RStudio to me in the first place :-)

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