cohortBuilder.db

cohortBuilder.db is database layer for cohortBuilder and shinyCohortBuilder. The package allows you to operate with cohortBuilder API on remote tables stores within a database.

All of the operations are performed directly on the database server side!

Installation

# CRAN version
install.packages("cohortBuilder.db")

# Latest development version
remotes::install_github("https://github.com/r-world-devs/cohortBuilder.db")

Overview

cohortBuilder.db allows you to use cohortBuilder and shinyCohortBuilder features working with database connection.

Comparing to the standard workflow (working on list of tables) you just need to create database tables configuration using dbtables where you provide database connection, schema name and table names. Than pass the created object to set_source method:

library(cohortBuilder)
library(cohortBuilder.db)
db_tables_conf <- dbtables(
  connection = <db-connection>,
  schema = <schema-name>,
  tables = <vector-of-table-names-to-use>
)

librarian_db_source <- set_source(
  db_tables_conf
)

and configure Cohort using the same rules known from cohortBuilder:

librarian_db_cohort <- cohort(
  librarian_source,
  filter(
    "discrete", id = "author", dataset = "books", 
    variable = "author", value = "Dan Brown"
  ),
  filter(
    "range", id = "copies", dataset = "books", 
    variable = "copies", range = c(5, 10)
  ),
  filter(
    "date_range", id = "registered", dataset = "borrowers", 
    variable = "registered", range = c(as.Date("2010-01-01"), Inf)
  )
) 

Now feel free to use all the known cohortBuilder features.

You can also use shinyCohortBuilder to use cohortBuilder features in shiny. Just use db-based Cohort with the known approach:

library(shiny)
library(shinyCohortBuilder)

ui <- fluidPage(
  sidebarLayout(
    sidebarPanel(
      cb_ui("librarian")
    ),
    mainPanel(
      verbatimTextOutput("cohort_data")
    )
  )
)

server <- function(input, output, session) {
  cb_server("librarian", librarian_db_cohort)
  
  output$cohort_data <- renderPrint({
    input[["librarian-data-updated"]]
    get_data(librarian_cohort)
  })
  
}

shinyApp(ui, server)

Acknowledgement

Special thanks to:

• Kamil Wais for highlighting the need for the package and its relevance to real-world applications.
• Adam Foryś for technical support, numerous suggestions for the current and future implementation of the package.
• Paweł Kawski for indication of initial assumptions about the package based on real-world medical data.

Getting help

In a case you found any bugs, have feature request or general question please file an issue at the package Github. You may also contact the package author directly via email at krystian8207@gmail.com.