NIH Inclusion Enrollment Report

This repository contains scripts and an rmarkdown report to demonstrate how to create an inclusion enrollment reporting table and dataset per NIH specifications

Report - NIH Inclusion Enrollment Report.Rmd

This is an rmarkdown report using the distill template that outputs the NIH specified enrollment table and provides a download capacity to download the NIH formatted dataset as CSV for upload to the NIH portal.

It uses the scripts below to format age, sex, race, and ethnicity data to NIH specifications and present the data as a table or CSV download.

Scripts

create_example.R - creates example data of necessary variables using randomly generated numbers

create_dataset.R - formats dataset from the above script to NIH specifications for table output and creates a dataset for output to CSV to NIH specs

create_table.R - creates a nested table per NIH specs

Dependencies

This code uses the following R packages: tidyverse, lubridate, gt, gtsummary, downloadthis, and rmarkdown/knitr.

In order to produce the inclusion enrollment table and dataset, you will need the following:

• Age
  • must be evaluable to units of years
• Race
  • must be evaluable to the categories listed in the NIH specs
• Ethnicity
  • must be evaluable to the categories listed in the NIH specs
• Gender
  • must be evaluable to Male, Female or Unknown/Not Reported
• Enrollment date
  • or date associated with the participant record that will be used to determine if the participant will be reported
• Inclusion date
  • date against which the above enrollment date will be tested to determine if a participant will be included in the report

How to use this repository

1. Install the above dependencies using install.packages(c("tidyverse", "lubridate", "gt", "gtsummary", "downloadthis")) if necessary
2. Knit NIH Inclusion Enrollment Report.Rmd

If you wish to look at individual components of the report:

1. Run create_example.R to create the example dataset.
2. Run create_dataset.R to format the dataset for output and create the CSV output dataset
3. Run create_table.R to create the output table.