This software tool is designed to extract data from a randomized subset of individuals within a cohort and make it available for exploration in a ‘Shiny’ application environment. It retrieves date-stamped, event-level records from one or more data sources that represent patient data in the Observational Medical Outcomes Partnership (OMOP) data model format. This tool features a user-friendly interface that enables users to efficiently explore the extracted profiles, thereby facilitating applications, such as reviewing structured profiles. The output of this R-package is a self-contained R shiny that contains person-level data for review.
cohortDatabaseSchema: Schema name where your cohort tables reside. cdmDatabaseSchema: Schema name where your OMOP CDM tables with person level data reside.
CohortExplorer has one function createCohortExplorerApp that when properly configured will connect to your database, check if the cohort table is instantiated, identify (random) sample of persons, extract their person level data, compile the output into an executable shiny application that may be executed.
Example: in the configuration example shown below, your output folder is “D:/myProject”. The output will be created in that location.
connectionDetails <- DatabaseConnector::createConnectionDetails( dbms = "postgresql", server = "some.server.com/ohdsi", user = "joe", password = "secret" ) createCohortExplorerApp <- function(connectionDetails = connectionDetails, cohortDatabaseSchema = "cohort", cdmDatabaseSchema = "CDM", vocabularyDatabaseSchema = "CDM", cohortTable = "myCohortTable", cohortDefinitionId, cohortName = "personsWithSomeDisease", sampleSize = 25, exportFolder = "D:/myProject", databaseId, shiftDates = FALSE, assignNewId = FALSE)
In the exportFolder location there will be a
Inside that folder is the
Please ensure all R and R-studio sessions are closed on your computer. Then, double click the file CohortExplorer.Rproj. This will start RStudio. We recommend that you now run renv::restore() as it will set up all R package dependencies and if executed properly will ensure your app will run smoothly. You can then start the shiny app by typing in R studio console
Please zip the CohortExplorerShiny folder into one zip file and upload to the folder on the remote R studio server. The name of the folder in the remote R studio server should become the published Shiny App name (url)