CleanADHdata.R

Overview

CleanADHdata.R is an open-source R script designed to clean and enrich electronic monitoring (EM) adherence data. This tool is specifically developed for researchers to preprocess raw EM data collected from studies on medication adherence, particularly focusing on oral anticancer treatments. The script aids in preparing the data for subsequent implementation and persistence analysis.

Features

• Data Cleaning: Automatically cleans raw EM adherence data to correct errors and inconsistencies.
• Data Enrichment: Enhances the dataset with additional relevant covariables, such as demographic and clinical data.
• Standardization: Ensures data is standardized for accurate adherence analysis.
• Ease of Use: Requires minimal user input with predefined formats for input files.

Installation

To use the CleanADHdata.R script, you need to have R installed on your system. You can download and install R from CRAN.

Usage

1. Prepare Your Data: Extract your EM adherence data into a CSV or Excel file with the following columns:

   • PatientCode: Alphanumeric patient identifier
   • Monitor: Alphanumeric monitor identifier
   • Date: Date-time format of the EM event
   • Additional columns such as RecordedOpenings for daily adherence data

2. Gather auxiliary data: The script requires additional data to be provided in Excel file to enrich the dataset. This Excel file must contain the following sheets:

   • EMInfo
   • Regimen The following sheets are optional:
   • PatientCovariables
   • EMCovariables
   • AddedOpenings
   • NonMonitoredPeriods
   • AdverseEvents

3. Run the Script: Execute the CleanADHdata.R script in R. The script will prompt for the necessary input files and parameters.

   source("CleanADHdata.R")

4. Review the Output: The script generates a cleaned and enriched dataset ready for analysis, saved as implementation.xlsx.

Example

Sample raw EM data and a tutorial are provided to help users practice using the script. The sample raw EM can be accessed on our GitHub repository, whereas the tutorial is available on JMIR Formative Research.

Citation

If you use CleanADHdata.R in your research, please cite the following publication:

Bandiera C, Pasquier J, Locatelli I, Schneider MP. Using a Semiautomated Procedure (CleanADHdata.R Script) to Clean Electronic Adherence Monitoring Data: Tutorial. JMIR Form Res 2024;8:e51013. doi: 10.2196/51013.