In HealthInformaticsUT/Cohort2Trajectory: Package for creating patient orientated treatment trajectories from cohorts defined in OHDSI ATLAS

knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>"
)

Creating trajectories

This section outlines the process for creating trajectories, including handling edge cases.

The standard approach involves using the default configuration, data import, and pre-processing steps, as described in getting started.

createTrajectories (cdm = cdm, studyEnv = studyEnv)

If the user opts out of using the previous configuration, the necessary inputs must be provided manually. Below is list of default values:

createTrajectories(
  cdm = NULL,
  studyEnv = NULL,
  trajectoryType = studyEnv$trajectoryType,
  runSavedStudy = studyEnv$runSavedStudy,
  oocFix = studyEnv$oocFix,
  outOfCohortAllowed = studyEnv$outOfCohortAllowed,
  lengthOfStay = studyEnv$lengthOfStay,
  stateCohortLabels = studyEnv$stateCohortLabels,
  stateCohortPriorityOrder = studyEnv$stateCohortPriorityOrder,
  stateSelectionType = studyEnv$stateSelectionType,
  stateCohortAbsorbing = studyEnv$stateCohortAbsorbing,
  stateCohortMandatory = studyEnv$stateCohortMandatory,
  allowedStatesList = studyEnv$allowedStatesList,
  useCDM = studyEnv$useCDM,
  pathToStudy = studyEnv$pathToStudy,
  batchSize = studyEnv$batchSize
)

Adding personal data to self-inserted data

To include personal data such as patient age and gender while creating trajectories, ensure useCDM is set to TRUE.

createTrajectories (
  cdm = cdm,
  studyEnv = studyEnv,
  useCDM = TRUE
)

The function returns a dataframe with the trajectories and saves the trajectories to the study path.

HealthInformaticsUT/Cohort2Trajectory documentation built on March 1, 2025, 7:47 p.m.