# Using OhdsiShinyAppBuilder

## Jenna Reps, Jamie Gilbert, Josh Ide, Nate Hall

### 2026-07-22

# Using the Shiny App Builder

The shiny app builder provides a way to combine different ohdsi shiny modules into a single app. For example, if you have a characterization study, a cohort method study and a prediction study that are related as they all use the same cohorts, then you may want to view the results in a single shiny app. This can be done by using `OhdsiShinyAppBuilder` to combine the characterization, cohort method and prediction shiny modules in `OhdsiShinyModules`. The main source of shiny modules is the `OhdsiShinyModules` R package, however, it is possible to add modules from other R packages or use local functions.

In this vignette we provide examples on how to use the `OhdsiShinyAppBuilder` to create flexible shiny apps for exploring OHDSI results.

The `OhdsiShinyAppBuilder` requires that all results to be explored by the shiny app are saved into a single database (i.e., all results for the different shiny modules in an app are saved into the same result database), as a single database connection is shared across shiny modules.

# Creating a config file

To create a shiny app config that contains four shiny modules:

- About (an introduction to the shiny app)
- Cohort Generation (details about generated cohorts)
- Estimation (details about causal inference studies via the cohort method)
- Prediction (details about patient level prediction models)

All of these are available as shiny modules in `OhdsiShinyModules`.

## Creating module config settings

To create the shiny app via `OhdsiShinyAppBuilder` we first need to create a config specification for all the shiny modules we wish to include into the single shiny app. A config can be created using `createModuleConfig`.

Inputs | Description
--- | ---
moduleId | a unique id for the shiny app
tabName | The menu text for the module
shinyModulePackage | The R package that contains the shiny module or NULL if using a local function
shinyModulePackageVersion | The minimum version of shinyModulePackage that is require or NULL
moduleUiFunction | The name of the module’s UI function
moduleServerFunction | The name of the module’s server function
moduleInfoBoxFile | The function in the shinyModulePackage package that contains the helper information
moduleIcon | An icon to use in the menu for this module
installSource | The Repo (CRAN or github) where users can install shinyModulePackage
gitHubRepo | If shinyModulePackage is available from github, this is the github repo you can find it

Note: it is possible to add shiny modules from any R package by setting `shinyModulePackage` to the R package with the UI and server functions and then specifying the UI function as `moduleUiFunction` and server function as `moduleServerFunction`. If you wish to use local functions for the UI and server, set `shinyModulePackage` to NULL. However, the server function must take as input `id` (the module id as standard for shiny server modules) and `resultDatabaseSettings` (a list containing the database result details required when extracting the results from the database that can be created using `OhdsiShinyAppBuilder::createDefaultResultDatabaseSettings`).

## Creating the about module config

For the about module we will specify in the config to use the about shiny modules in `OhdsiShinyModules`. The UI is named `aboutViewer`, the server is named `aboutServer` and the about helper function is called `aboutHelperFile()`. As the about module provides information about the shiny app, the ‘info’ icon seems appropriate. The inputs into `createModuleConfig` for an about module are:

    aboutModule <- createModuleConfig(
          moduleId = 'about',
          tabName = "About",
          shinyModulePackage = "OhdsiShinyModules",
          moduleUiFunction = 'aboutViewer',
          moduleServerFunction = 'aboutServer',
          moduleInfoBoxFile =  "aboutHelperFile()",
          moduleIcon = 'info',
          installSource = 'github',
          gitHubRepo = 'ohdsi'
        )

For simplicity, the `OhdsiShinyAppBuilder` contains a function called `createDefaultAboutConfig` with these default about settings into `createModuleConfig`, this is quicker to use than `createModuleConfig` if you are using a standard about module. Alternatively, you could just run:

    aboutModule <- createDefaultAboutConfig()

## Creating the prediction module config

To add a prediction module you can specify the `OhdsiShinyModule` functions: `aboutPrediction` for the module UI, `aboutPrediction` for the module server and `aboutPredictionFile()` for the about helper function. A suitable icon is `chart-line`. For the prediction module, results in the database format created by the `PatientLevelPrediction` package must be in a database that will be connected to when viewing the shiny app.

    predictionModule <- createModuleConfig(
        moduleId = 'prediction',
        tabName = "Prediction",
        shinyModulePackage = 'OhdsiShinyModules',
        moduleUiFunction = "predictionViewer",
        moduleServerFunction = "predictionServer",
        moduleInfoBoxFile =  "predictionHelperFile()",
        moduleIcon = "chart-line",
        installSource = 'github',
        gitHubRepo = 'ohdsi'
        )

For simplicity, the `OhdsiShinyAppBuilder` contains a function called `createDefaultPredictionConfig` with these default prediction settings. Atlernatively, you could just run:

    predictionModule <- createDefaultPredictionConfig()

## Creating the cohort generation and cohort method using default functions

We have default config creation for cohort method and cohort generation using UI and server functions found in `OhdsiShinyAppBuilder`:

    cohortMethodModule <- createDefaultEstimationConfig()

    cohortGeneratorModule <- createDefaultCohortGeneratorConfig()

## Combining config settings

Next step is to combine the module config settings into a shiny app config. First we use `initializeModuleConfig()` to create an empty shiny app config and then we use `addModuleConfig()` to add each of the module configs we previously created:

    library(dplyr)
    shinyAppConfig <- initializeModuleConfig() %>%
      addModuleConfig(aboutModule) %>%
      addModuleConfig(cohortGeneratorModule) %>%
      addModuleConfig(cohortMethodModule) %>%
      addModuleConfig(predictionModule)

It is possible to save the shiny app config using `saveConfig(shinyAppConfig, 'save location')` and load a previously saved shiny app config `shinyAppConfig <- loadConfig('save location')`

# View Shiny App

## Create an app.R for a shiny server

To create the `shiny` app you need to first create the shinyAppConfig, then specify the connectionDetails where the results are stored and finally you can call `createShinyApp`.

To run the shiny app on a shiny server you need to create an app.R file with the config the connection correctly specified. For example, your app.R could contain the following lines of code:

    # save this as app.R and upload it to a shiny server

    # create the config using existing UI and server functions
    # in OhdsiShinyModules or by creating the UI and server functions
    fooModuleUi <- function (id = "foo") {
        shiny::fluidPage(title = "foo")
      }

    fooModule <- function(
      id = 'foo',
      connectionHandler = NULL,
      resultDatabaseSettings = NULL,
      config
      ) {
      shiny::moduleServer(id, function(input, output, session) { })
    }

    fooHelpInfo <- function() {
      'NA'
    }

    moduleConfig <- createModuleConfig(
      moduleId = 'foo',
      tabName = "foo",
      shinyModulePackage = NULL,
      moduleUiFunction = fooModuleUi,
      moduleServerFunction = fooModule,
      moduleInfoBoxFile = "fooHelpInfo()",
      moduleIcon = "info"
    )

    shinyAppConfig <- initializeModuleConfig()
    shinyAppConfig <- addModuleConfig(shinyAppConfig, moduleConfig)

    # create a connection to the result database
    # in this example it is an empty sql database
    connectionDetails <- DatabaseConnector::createConnectionDetails(
      dbms = 'sqlite',
      server = './madeup.sql'
      )
    # Create the app
    createShinyApp(
      config = shinyAppConfig,
      connectionDetails = connectionDetails,
      resultDatabaseSettings = createDefaultResultDatabaseSettings()
        )

Note: if you specify a package dependency via the ‘shinyModulePackage’ value in the config that was not previously installed, you will be asked whether you want to install the required package when you run `createShinyApp` or `viewShiny`.

## Open a shiny app locally

To just view the shiny app locally, you need to specify the config and connection details to the result database and then run the following lines of code in R:

    # create the config using existing UI and server functions
    # in OhdsiShinyModules or by creating the UI and server functions
    fooModuleUi <- function (id = "foo") {
        shiny::fluidPage(title = "foo")
      }

    fooModule <- function(
      id = 'foo',
      connectionHandler = NULL,
      resultDatabaseSettings = NULL,
      config
      ) {
      shiny::moduleServer(id, function(input, output, session) { })
    }

    fooHelpInfo <- function() {
      file.path(tempdir(), 'help.html')
    }

    moduleConfig <- createModuleConfig(
      moduleId = 'foo',
      tabName = "foo",
      shinyModulePackage = NULL,
      moduleUiFunction = fooModuleUi,
      moduleServerFunction = fooModule,
      moduleInfoBoxFile = "fooHelpInfo()",
      moduleIcon = "info"
    )

    shinyAppConfig <- initializeModuleConfig()
    shinyAppConfig <- addModuleConfig(shinyAppConfig, moduleConfig)

    # create a connection to the result database
    # in this example it is an empty sql database
    connectionDetails <- DatabaseConnector::createConnectionDetails(
      dbms = 'sqlite',
      server = './madeup.sql'
      )

    # specify the app title
    appTitle <- 'Example Foo App'

    # provide a short paragraph to described the study
    # that the is exploring the results of.
    studyDescription <- "An empty made up study for the vignette demo.  The shiny app with show one menu option called 'foo' that will not do anything."

    # specify whether you want to use a pooled connection
    usePooledConnection <- FALSE

    # open a shiny app that lets you explore results
    viewShiny(
      config = shinyAppConfig,
      connectionDetails = connectionDetails,
      resultDatabaseSettings = createDefaultResultDatabaseSettings(),
      title = appTitle,
      usePooledConnection = usePooledConnection,
      studyDescription = studyDescription
        )

You can specify the title for the app and a short description of the study via the inputs `title` and `studyDescription` into the `viewShiny` and `createShinyApp` functions.