LabTNS CPSS Package

This R package implements a pipeline to process clinical episode data, identify chronic pathologies, and calculate frailty and comorbidity scores based on patient diagnosis codes.

Overview

The pipeline performs the following steps:

1. Setup environment
   Load and install required R packages and source supporting scripts.

2. Data Preparation
   Clean and format input episode data based on user-specified column mappings.

3. Chronic Pathologies Identification
   Apply algorithms to detect and propagate chronic conditions within episodes.

4. Frailty Calculation
   Calculate frailty indices from updated episode data.

5. Comorbidity and Frailty Summary
   Combine frailty and comorbidity measures into final result tables.

Usage

Installation

You can either clone the repository or download the ZIP file.

git clone https://github.com/bayaniazadeh/LabTNSCPSSPackage.git
cd LabTNSCPSSPackage

Running the pipeline

Running the pipeline

1. Place your input CSV in LABTNSCPSS_Data/, e.g., LABTNSCPSS_Data/testpackage.csv

2. Go to your directory that the LabTNSCPSSPackage folder exists and run the file LabTNSCPSSPackage.Rproj,

then open Frailty_Comorbidity_Pipeline.R in your open R studio.

In the Frailty_Comorbidity_Pipeline.R code edit these information:

• The input dataset should be a CSV file with episode-level patient data.
• Required columns (default mapping):
  • Patient_id — patient ID
  • ICD — ICD coding system diagnosis codes
  • start_date — episode start date
  • end_date — episode end date
  • episode_id — unique episode identifier

You can customize these column names by modifying the col_mapping list in the pipeline.

2. Run the pipeline from your R session line by line:

source("./LABTNSCPSS_Code/setup_package.R")      # Load/install packages
source("./LABTNSCPSS_Code/source_scripts.R")     # Load pipeline functions

coding_system <- get_coding_system()

Here you should select the ICD vesion of according to your data: ICD-10-CA, ICD-10-CM, ICD-11, write it in the console part and press enter.

3. Run the rest of the code line by line.

4. Finally you can find the generated files at LABTNSCPSS_Data/

Important resources

In the folder data/ you can find all the mapping files and categorizations in ".rda"" format. To be able to explore the mappings in your R studio browser use this code, and replace "file_name" with your desired data file :

df <- as.data.frame(file_name)
View(df)