RHEA

Real-world observaional Health data Exploration Application (RHEA)

Introduction

RHEA provides a process for creating a data exploration system focus on patient with cancer from a medical database in OMOP-CDM format.

Technology

RHEA is an R package codes for process of the study.

Dependencies

install.package(data.table)

install.package(DatabaseConnector)

install.package(rjson)

install.package(purrr)

install.package(SqlRender)

install.package(dplyr)

install.package(highcharter)

install.package(listviewer)

install.package(tidyr)

install.package(tidyverse)

install.package(cli)

install.package(collapsibleTree)

install.package(DT)

install.package(fansi)

install.package(xfun)

install.package(lubridate)

install.package(ggplot2)

install.package(plyr)

install.package(RSQLite)

install.package(plotly)

install.package(quantmod)

install.package(shiny)

install.package(shinyalert)

install.package(shinycssloaders)

install.package(shinydashboard)

install.package(shinythemes)

install.package(shinyWidgets)

install.package(summaryBox)

install.package(ggrepel)

install.package(gridExtra)

install.package(stringr)

install.package(xml2)

install.package(htmlwidgets)

install.package(RColorBrewer)

Getting started

In R, use the following commands to download and install: install.packages("devtools") devtools::install_github("ABMI/RHEA") library(RHEA)

################
## DB connect ##
################
# Details for connectiong to the server
connectionDetails <- DatabaseConnector::createConnectionDetails(dbms= 'dbmd',
                                                                server='server',
                                                                user='user',
                                                                password='password',
                                                                port='port')
oracleTempSchema <- NULL
cdmDatabaseSchema <- "cdmDatabaseSchema"
cohortDatabaseSchema <- "cohortDatabaseSchema"
vocaDatabaseSchema <- cdmDatabaseSchema
oncologyDatabaseSchema <- cdmDatabaseSchema

#########################
## 1. data preparation ##
#########################
# 1) OMOP-CDM tables - COHORT, EPISODE, EPISODE_EVENT
# - The cohorts in this package are designed to work with Atlas.
atlasID <- 2087 # ATLAS Cohort Definition ID
cohortTable <- "cohortTable_name"
episodeTable <- "episodeTable_name"
episodeEventTable <- "episodeEventTable_name"


# 2) Treatment pathway
Graph_cohort <- "Graph_cohort_name"
outputFolder <- 'outputFolder pathway'
minSubject <- 0 # under 0 patients are removed from plot
collapseDates <- 0
treatmentLine <- 3 # Treatment line number for visualize in graph
minimumRegimenChange <- 1 # Target patients for at least 1 regimen change

# Draw and save a flow chart of the treatment pathway
executeExtraction(connectionDetails,
                  oracleTempSchema,
                  cdmDatabaseSchema,
                  vocaDatabaseSchema = cdmDatabaseSchema,
                  cohortDatabaseSchema,
                  oncologyDatabaseSchema= cdmDatabaseSchema,
                  cohortTable,
                  episodeTable,
                  episodeEventTable,
                  maxCores = 1,
                  # COHORT
                  createCohortTable = TRUE, # Create cohort table for your cohort table
                  # EPISODE, EPISODE_EVENT
                  createEpisodeAndEventTable = TRUE  # warning: existing table might be erased
                  )

# Load note report
BiopsyResult <- loadReportTable()

# Draw and save a flow chart of the treatment pathway
Txpathway(connectionDetails,
          oracleTempSchema,
          cdmDatabaseSchema,
          cohortDatabaseSchema,
          oncologyDatabaseSchema,
          vocaDatabaseSchema,
          cohortTable,
          Graph_cohort,
          episodeTable,
          outputFolder,
          identicalSeriesCriteria = 60,
          maximumCycleNumber = 18,
          minSubject = 0,
          collapseDates = 0,
          conditionCohortIds = atlasID,
          treatmentLine = 3,
          minimumRegimenChange = 1)

##################
## 2. Dashboard ##
##################
# Load Cohort table
Cohort <- loadCohortTable()

# Load Episode table
Episode <- loadEpisodTable()

# TNM stage code
TNMcode <- read.csv("./inst/csv/TNMcode.csv")

# TreatmentPathway figure
RegimenInfo <- loadRegimenlist()

# Calculation Patient care
PatientCareSummary <- calculation()

Antibiotics <- read.csv("./inst/csv/AntibioticsConcepts.csv")
connection <- DatabaseConnector::connect(connectionDetails = connectionDetails)

# 3. Run APP
runShinyApp()

License

RHEA is licensed under Apache License 2.0

Development

RHEA is being developed in R Studio.