README.md

ClinicalCharacteristics

The goal of ClinicalCharacteristics is to characterize a patient population using OMOP data. This approach uses a table shell approach where characteristic extraction are limited to what is specified in the build object.

Installation

To install ClinicalCharacteristics, follow these steps:

1. clone the repository
2. Open the ClinicalCharacteristics.RProj file in the repository
3. Navigate to the build tab in RStudio and select Install
4. Exit out of the ClinicalCharacteristics.RProj session
5. Recommended create a new RProj to test the package.
6. Use CohortGenerator to build a cohort def in scratch

Example

To run this example you need to install Capr

library(ClinicalCharacteristics)
library(Capr)

# make connection details
connectionDetails <- DatabaseConnector::createConnectionDetails(
  dbms = '<dbms>',
  user = "<user>",
  password = "<password>",
  connectionString = "<jdbcString>"
)

executionSettings <- list(
  databaseName = "my_omop_data",
  cdmDatabaseSchema = "cdm",
  workDatabaseSchema = "scratch",
  cohortTable = "cohorts"
)

outputFolder <- here::here("my_output")

connection <- DatabaseConnector::connect(connectionDetails)

clinChar <- makeClinChar(
  targetCohortIds = 1,
  targetCohortNames = "Target",
  dbms = connection@dbms,
  database = executionSettings$databaseName,
  cdmDatabaseSchema = executionSettings$cdmDatabaseSchema,
  workDatabaseSchema = executionSettings$workDatabaseSchema,
  cohortTable = executionSettings$cohortTable
) |>
  addAgeChar(categorize = age10yrGrp()) |>
  addGenderChar() |>
  addRaceChar() |>
  addYearChar(categorize = year5yrGrp()) |>
  addConditionPresence(
    conceptSets = charlsonConcepts(),
    timeWindows = makeTimeTable(time_a = -365, time_b = -1),
    limit = "first",
    score = charlsonIndexScore(ageId = 1)
  ) |>
  addDrugPresence(
    conceptSets = atcConcepts(),
    timeWindows = makeTimeTable(
      time_a = c(-365, 0, 0, 0),
      time_b = c(-1, 183, 365, 730)
      ),
    limit = "first"
  ) |>
  addDrugCount(
    timeWindows = makeTimeTable(
      time_a = c(-365, 0, 0, 0),
      time_b = c(-1, 183, 365, 730)
    )
  ) |>
  addVisitCount(
    conceptSets = standardVisitConcepts(),
    timeWindows = makeTimeTable(
      time_a = c(-365, 0, 0, 0),
      time_b = c(-1, 183, 365, 730)
    )
  )


# run the clinical characteristics
dt <- runClinicalCharacteristics(connection = connection,
                                      clinChar = clinChar,
                                      saveName = "internals_test",
                                      savePath = outputFolder,
                                      dropDat = FALSE)

# preview the categorical results
previewClincalCharacteristics(dt, type = "categorical")
# preview the continuous results
previewClincalCharacteristics(dt, type = "continuous")
#build a report
createReport(clinChar, outputFolder = outputFolder)