Welcome

revenue-cycle-management medical-billing medical-coding data-analytics rstats

An #rstats geek in healthcare analytics, here to spread the good word of R.

Andrew Bruce https://andrewbruce.netlify.app
03-14-2022

Hi. I hope you like health insurance.

Like, a lot.

This blog is primarily intended to be a personal knowledge management project (or second brain) with the goal of researching, connecting and simplifying all things medical billing, coding, and the healthcare revenue cycle, i.e. teaching myself. The primary tool that I’ll be using is the R programming language and it’s incredible packages. In case you are not aware, R, it’s most popular IDE, RStudio, and all of its packages are free and open-source.

Secondly, I hope that this site will be helpful to those in healthcare reimbursement that are curious about coding in R and are searching far and wide as I did when I started for coding examples using data and problems that they might recognize. So, short and sweet. Here we go.

R in EHRs/EMRs

Image of ReviewR from https://reviewr.thewileylab.org/

As an R teaser, here’s a short list of R packages created to do all manner of things in EHRs/EMRs:

Package Description
ReviewR ReviewR is a portable Shiny tool to help you explore patient-level electronic health record data and perform a chart review in a single integrated framework. It is distributed as an R package using the golem framework.
dxpr An R package for generating analysis-ready data from electronic health records—diagnoses and procedures
rEHR (second article) An R package for manipulating and analysing Electronic Health Record data
memr The memr (Multisource Embeddings for Medical Records) package in R allows for creating embeddings, i.e. vector representations, of medical free-text records written by doctors. It also provides a wide spectrum of tools to data visualization and medical visits’ segmentation. These tools aim to develop computer-supported medicine by facilitating medical data analysis and iterpretation. The package can be exploited for many applications like the recommendation prediction, patients’ clustering etc. that can aid doctors in their practice.
ROMOP A light-weight R package for interfacing with OMOP-formatted electronic health record data
rdrugtrajectory An R Package for the Analysis of Drug Prescriptions in Electronic Health Care Records
EHR The ‘EHR’ package provides modules to process and analyze electronic health record (EHR) data to perform diverse medication-related studies using data from EHR databases.
Shiny New Things Using R Bridge the Gap in Electronic Medical Record Reporting Not a package, but an excellent talk by Brendan Graham, a healthcare data analyst, wherein he describes how a cross-departmental project team that he’s part of uses an internal R package, RMarkdown reports scheduled via R Studio Connect, and an interactive flexdashboard app to quickly implement solutions to gaps in the reporting capabilities of the EMR. Highly Recommended.

Citations

Package Version Citation
base 4.2.0 R Core Team (2022)
distill 1.4 Dervieux et al. (2022)
grateful 0.1.11 Rodríguez-Sánchez, Jackson, and Hutchins (2022)
htmltools 0.5.2 Cheng et al. (2021)
knitr 1.39 Xie (2014); Xie (2015); Xie (2022)
rmarkdown 2.14 Xie, Allaire, and Grolemund (2018); Xie, Dervieux, and Riederer (2020); Allaire et al. (2022)
sessioninfo 1.2.2 Wickham et al. (2021)
xaringanExtra 0.5.5 Aden-Buie and Warkentin (2022)

Last updated on

[1] "2022-06-02 02:16:25 EDT"

Session Info

sessioninfo::session_info()

─ Session info ───────────────────────────────────────────────────────────────────────────────────────────────────────
 setting  value
 version  R version 4.2.0 (2022-04-22 ucrt)
 os       Windows 10 x64 (build 25126)
 system   x86_64, mingw32
 ui       RTerm
 language (EN)
 collate  English_United States.utf8
 ctype    English_United States.utf8
 tz       America/New_York
 date     2022-06-02
 pandoc   2.17.1.1 @ C:/Program Files/RStudio/bin/quarto/bin/ (via rmarkdown)

─ Packages ───────────────────────────────────────────────────────────────────────────────────────────────────────────
 package       * version date (UTC) lib source
 bslib           0.3.1   2021-10-06 [1] CRAN (R 4.2.0)
 cachem          1.0.6   2021-08-19 [1] CRAN (R 4.2.0)
 cli             3.3.0   2022-04-25 [1] CRAN (R 4.2.0)
 crayon          1.5.1   2022-03-26 [1] CRAN (R 4.2.0)
 digest          0.6.29  2021-12-01 [1] CRAN (R 4.2.0)
 distill         1.4     2022-05-12 [1] CRAN (R 4.2.0)
 downlit         0.4.0   2021-10-29 [1] CRAN (R 4.2.0)
 ellipsis        0.3.2   2021-04-29 [1] CRAN (R 4.2.0)
 evaluate        0.15    2022-02-18 [1] CRAN (R 4.2.0)
 fansi           1.0.3   2022-03-24 [1] CRAN (R 4.2.0)
 fastmap         1.1.0   2021-01-25 [1] CRAN (R 4.2.0)
 glue            1.6.2   2022-02-24 [1] CRAN (R 4.2.0)
 grateful      * 0.1.11  2022-05-07 [1] Github (Pakillo/grateful@ba9b003)
 highr           0.9     2021-04-16 [1] CRAN (R 4.2.0)
 htmltools       0.5.2   2021-08-25 [1] CRAN (R 4.2.0)
 jquerylib       0.1.4   2021-04-26 [1] CRAN (R 4.2.0)
 jsonlite        1.8.0   2022-02-22 [1] CRAN (R 4.2.0)
 knitr         * 1.39    2022-04-26 [1] CRAN (R 4.2.0)
 lifecycle       1.0.1   2021-09-24 [1] CRAN (R 4.2.0)
 magrittr        2.0.3   2022-03-30 [1] CRAN (R 4.2.0)
 memoise         2.0.1   2021-11-26 [1] CRAN (R 4.2.0)
 pillar          1.7.0   2022-02-01 [1] CRAN (R 4.2.0)
 pkgconfig       2.0.3   2019-09-22 [1] CRAN (R 4.2.0)
 purrr           0.3.4   2020-04-17 [1] CRAN (R 4.2.0)
 R.cache         0.15.0  2021-04-30 [1] CRAN (R 4.2.0)
 R.methodsS3     1.8.1   2020-08-26 [1] CRAN (R 4.2.0)
 R.oo            1.24.0  2020-08-26 [1] CRAN (R 4.2.0)
 R.utils         2.11.0  2021-09-26 [1] CRAN (R 4.2.0)
 R6              2.5.1   2021-08-19 [1] CRAN (R 4.2.0)
 renv            0.15.5  2022-05-26 [1] CRAN (R 4.2.0)
 rlang           1.0.2   2022-03-04 [1] CRAN (R 4.2.0)
 rmarkdown       2.14    2022-04-25 [1] CRAN (R 4.2.0)
 rstudioapi      0.13    2020-11-12 [1] CRAN (R 4.2.0)
 sass            0.4.1   2022-03-23 [1] CRAN (R 4.2.0)
 sessioninfo     1.2.2   2021-12-06 [1] CRAN (R 4.2.0)
 stringi         1.7.6   2021-11-29 [1] CRAN (R 4.2.0)
 stringr         1.4.0   2019-02-10 [1] CRAN (R 4.2.0)
 styler          1.7.0   2022-03-13 [1] CRAN (R 4.2.0)
 tibble          3.1.7   2022-05-03 [1] CRAN (R 4.2.0)
 utf8            1.2.2   2021-07-24 [1] CRAN (R 4.2.0)
 uuid            1.1-0   2022-04-19 [1] CRAN (R 4.2.0)
 vctrs           0.4.1   2022-04-13 [1] CRAN (R 4.2.0)
 xaringanExtra   0.5.5   2022-04-26 [1] Github (gadenbuie/xaringanExtra@ee5092d)
 xfun            0.31    2022-05-10 [1] CRAN (R 4.2.0)
 yaml            2.3.5   2022-02-21 [1] CRAN (R 4.2.0)

 [1] C:/Users/andyb/AppData/Local/R/win-library/4.2
 [2] C:/Program Files/R/R-4.2.0/library

──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
Aden-Buie, Garrick, and Matthew T. Warkentin. 2022. xaringanExtra: Extras and Extensions for Xaringan Slides. https://github.com/gadenbuie/xaringanExtra.
Allaire, JJ, Yihui Xie, Jonathan McPherson, Javier Luraschi, Kevin Ushey, Aron Atkins, Hadley Wickham, Joe Cheng, Winston Chang, and Richard Iannone. 2022. Rmarkdown: Dynamic Documents for r. https://github.com/rstudio/rmarkdown.
Cheng, Joe, Carson Sievert, Barret Schloerke, Winston Chang, Yihui Xie, and Jeff Allen. 2021. Htmltools: Tools for HTML. https://CRAN.R-project.org/package=htmltools.
Dervieux, Christophe, JJ Allaire, Rich Iannone, Alison Presmanes Hill, and Yihui Xie. 2022. Distill: ’R Markdown’ Format for Scientific and Technical Writing. https://CRAN.R-project.org/package=distill.
R Core Team. 2022. R: A Language and Environment for Statistical Computing. Vienna, Austria: R Foundation for Statistical Computing. https://www.R-project.org/.
Rodríguez-Sánchez, Francisco, Connor P. Jackson, and Shaurita D. Hutchins. 2022. Grateful: Facilitate Citation of r Packages. https://github.com/Pakillo/grateful.
Wickham, Hadley, Winston Chang, Robert Flight, Kirill Müller, and Jim Hester. 2021. Sessioninfo: R Session Information. https://CRAN.R-project.org/package=sessioninfo.
Xie, Yihui. 2014. “Knitr: A Comprehensive Tool for Reproducible Research in R.” In Implementing Reproducible Computational Research, edited by Victoria Stodden, Friedrich Leisch, and Roger D. Peng. Chapman; Hall/CRC. http://www.crcpress.com/product/isbn/9781466561595.
———. 2015. Dynamic Documents with R and Knitr. 2nd ed. Boca Raton, Florida: Chapman; Hall/CRC. https://yihui.org/knitr/.
———. 2022. Knitr: A General-Purpose Package for Dynamic Report Generation in r. https://yihui.org/knitr/.
Xie, Yihui, J. J. Allaire, and Garrett Grolemund. 2018. R Markdown: The Definitive Guide. Boca Raton, Florida: Chapman; Hall/CRC. https://bookdown.org/yihui/rmarkdown.
Xie, Yihui, Christophe Dervieux, and Emily Riederer. 2020. R Markdown Cookbook. Boca Raton, Florida: Chapman; Hall/CRC. https://bookdown.org/yihui/rmarkdown-cookbook.

References

Corrections

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Reuse

Text and figures are licensed under Creative Commons Attribution CC BY 4.0. Source code is available at https://github.com/andrewallenbruce, unless otherwise noted. The figures that have been reused from other sources don't fall under this license and can be recognized by a note in their caption: "Figure from ...".

Citation

For attribution, please cite this work as

Bruce (2022, March 14). Andrew Bruce: Welcome. Retrieved from https://andrewbruce.netlify.app/posts/welcome/

BibTeX citation

@misc{bruce2022welcome,
  author = {Bruce, Andrew},
  title = {Andrew Bruce: Welcome},
  url = {https://andrewbruce.netlify.app/posts/welcome/},
  year = {2022}
}

Andrew A. Bruce - - made with , and {distill}