Features
- Create a cohort table and generate cohorts against an OMOP CDM.
- Get the count of subjects and events in a cohort.
- Provides functions for performing incremental tasks. This is used by CohortGenerator to skip any cohorts that were successfully generated in a previous run. This functionality is generic enough for other packages to use for performing their own incremental tasks.
Example
# First construct a cohort definition set: an empty
# data frame with the cohorts to generate
cohortsToCreate <- CohortGenerator::createEmptyCohortDefinitionSet()
# Fill the cohort set using cohorts included in this
# package as an example
cohortJsonFiles <- list.files(path = system.file("testdata/name/cohorts", package = "CohortGenerator"), full.names = TRUE)
for (i in 1:length(cohortJsonFiles)) {
cohortJsonFileName <- cohortJsonFiles[i]
cohortName <- tools::file_path_sans_ext(basename(cohortJsonFileName))
# Here we read in the JSON in order to create the SQL
# using [CirceR](https://ohdsi.github.io/CirceR/)
# If you have your JSON and SQL stored differenly, you can
# modify this to read your JSON/SQL files however you require
cohortJson <- readChar(cohortJsonFileName, file.info(cohortJsonFileName)$size)
cohortExpression <- CirceR::cohortExpressionFromJson(cohortJson)
cohortSql <- CirceR::buildCohortQuery(cohortExpression, options = CirceR::createGenerateOptions(generateStats = FALSE))
cohortsToCreate <- rbind(cohortsToCreate, data.frame(cohortId = i,
cohortName = cohortName,
sql = cohortSql,
stringsAsFactors = FALSE))
}
# Generate the cohort set against Eunomia.
# cohortsGenerated contains a list of the cohortIds
# successfully generated against the CDM
connectionDetails <- Eunomia::getEunomiaConnectionDetails()
# Create the cohort tables to hold the cohort generation results
cohortTableNames <- CohortGenerator::getCohortTableNames(cohortTable = "my_cohort_table")
CohortGenerator::createCohortTables(connectionDetails = connectionDetails,
cohortDatabaseSchema = "main",
cohortTableNames = cohortTableNames)
# Generate the cohorts
cohortsGenerated <- CohortGenerator::generateCohortSet(connectionDetails = connectionDetails,
cdmDatabaseSchema = "main",
cohortDatabaseSchema = "main",
cohortTableNames = cohortTableNames,
cohortDefinitionSet = cohortsToCreate)
# Get the cohort counts
cohortCounts <- CohortGenerator::getCohortCounts(connectionDetails = connectionDetails,
cohortDatabaseSchema = "main",
cohortTable = cohortTableNames$cohortTable)
print(cohortCounts)Getting Started
Make sure your R environment is properly configured. This means that Java must be installed. See these instructions for how to configure your R environment.
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In R, use the following commands to download and install CohortGenerator:
remotes::install_github("OHDSI/CohortGenerator")
User Documentation
Documentation can be found on the package website.
PDF versions of the documentation are also available:
- Vignette: Generating Cohorts
- Package manual: CohortGenerator.pdf
Support
- Developer questions/comments/feedback: OHDSI Forum
- We use the GitHub issue tracker for all bugs/issues/enhancements
Contributing
Read here how you can contribute to this package.