R/Feasibility.R

In ohdsi-studies/VaccineEffectivenessEvaluation: Evaluating Use of Methods for Vaccine Effectiveness

# Copyright 2021 Observational Health Data Sciences and Informatics
#
# This file is part of Eumaeus
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.

#' Execute the Feasibility assessment
#'
#' @details
#' This function executes the Study.
#'
#' The \code{createCohorts}, \code{synthesizePositiveControls}, \code{runAnalyses}, and \code{runDiagnostics} arguments
#' are intended to be used to run parts of the full study at a time, but none of the parts are considerd to be optional.
#'
#' @param connectionDetails    An object of type \code{connectionDetails} as created using the
#'                             \code{\link[DatabaseConnector]{createConnectionDetails}} function in the
#'                             DatabaseConnector package.
#' @param cdmDatabaseSchema    Schema name where your patient-level data in OMOP CDM format resides.
#'                             Note that for SQL Server, this should include both the database and
#'                             schema name, for example 'cdm_data.dbo'.
#' @param outcomeDatabaseSchema Schema name where outcome data can be stored. You will need to have
#'                             write privileges in this schema. Note that for SQL Server, this should
#'                             include both the database and schema name, for example 'cdm_data.dbo'.
#' @param outcomeTable          The name of the table that will be created in the outcomeDatabaseSchema.
#'                             This table will hold the outcome cohorts used in this
#'                             study.
#' @param exposureDatabaseSchema For PanTher only: Schema name where exposure data can be stored. You will need to have
#'                             write priviliges in this schema. Note that for SQL Server, this should
#'                             include both the database and schema name, for example 'cdm_data.dbo'.
#' @param exposureTable          For PanTher only: The name of the table that will be created in the exposureDatabaseSchema
#'                             This table will hold the exposure cohorts used in this
#'                             study.
#' @param nestingCohortDatabaseSchema Schema name where nesting cohort data can be stored. You will need to have
#'                             write priviliges in this schema. Note that for SQL Server, this should
#'                             include both the database and schema name, for example 'cdm_data.dbo'.
#' @param nestingCohortTable          The name of the table that will be created in the nestingCohortDatabaseSchema
#'                             This table will hold the nesting cohorts used in this
#'                             study.
#' @param outputFolder         Name of local folder to place results; make sure to use forward slashes
#'                             (/). Do not use a folder on a network drive since this greatly impacts
#'                             performance.
#' @param databaseName         A short string for identifying the database (e.g.
#'                             'Synpuf').
#' @param maxCores             How many parallel cores should be used? If more cores are made available
#'                             this can speed up the analyses.
#' @param cdmVersion           Version of the Common Data Model used. Currently only version 5 is supported.
#' @param createNegativeControlCohorts        Create the negative control outcome and nesting cohorts?
#' @param imputeExposureLengthForPanther      For PanTher only: impute exposure length?
#' @param synthesizePositiveControls          Should positive controls be synthesized?
#' @param runCohortMethod                     Perform the cohort method analyses?
#' @param runSelfControlledCaseSeries                     Perform the SCCS analyses?
#' @param runSelfControlledCohort                     Perform the SCC analyses?
#' @param runCaseControl                     Perform the case-control analyses?
#' @param runCaseCrossover       Perform the case-crossover analyses?
#' @param createCharacterization       Create a general characterization of the database population?
#' @param packageResults       Should results be packaged for later sharing and viewing?
#'
#' @export
assessFeasibility <- function(connectionDetails,
                              cdmDatabaseSchema,
                              cohortDatabaseSchema,
                              cohortTable,
                              outputFolder,
                              databaseId,
                              databaseName = databaseId,
                              databaseDescription = databaseId,
                              cdmVersion = "5",
                              createNegativeControlCohorts = TRUE,
                              runCohortDiagnostics = TRUE) {
    cohortDiagnosticsFolder <- file.path(outputFolder, "cohortDiagnostics")
    if (!file.exists(cohortDiagnosticsFolder)) {
        dir.create(cohortDiagnosticsFolder, recursive = TRUE)
    }
    
    ParallelLogger::addDefaultFileLogger(file.path(cohortDiagnosticsFolder, "log.txt"))
    ParallelLogger::addDefaultErrorReportLogger(file.path(cohortDiagnosticsFolder, "errorReportR.txt"))
    on.exit(ParallelLogger::unregisterLogger("DEFAULT_FILE_LOGGER", silent = TRUE))
    on.exit(ParallelLogger::unregisterLogger("DEFAULT_ERRORREPORT_LOGGER", silent = TRUE), add = TRUE)
    
    # Create outcome and nesting cohorts for positive and negative controls ----------------------------------
    
    if (createNegativeControlCohorts) {
        ParallelLogger::logInfo("Creating negative control cohorts")
        createCohorts(connectionDetails = connectionDetails,
                      cdmDatabaseSchema = cdmDatabaseSchema,
                      cohortDatabaseSchema = cohortDatabaseSchema,
                      cohortTable = cohortTable,
                      outputFolder = outputFolder)
    }
    
    if (runCohortDiagnostics) {
        ParallelLogger::logInfo("Running cohort diagnostics")
        # tempFile <- tempfile(fileext = ".csv")
        # exposureCohorts <- loadExposureCohorts(outputFolder) %>%
        #     filter(.data$sampled == TRUE) %>%
        #     transmute(cohortId = .data$exposureId,
        #               name = .data$exposureName) %>%
        #     readr::write_csv(file = tempFile)
        
        CohortDiagnostics::runCohortDiagnostics(packageName = "Eumaeus",
                                                cohortToCreateFile = "settings/AllExposureCohorts.csv",
                                                connectionDetails = connectionDetails,
                                                cdmDatabaseSchema = cdmDatabaseSchema,
                                                cohortDatabaseSchema = cohortDatabaseSchema,
                                                cohortTable = cohortTable,
                                                exportFolder = cohortDiagnosticsFolder,
                                                databaseId = databaseId,
                                                databaseName = databaseName,
                                                databaseDescription = databaseDescription,
                                                runInclusionStatistics = FALSE,
                                                runBreakdownIndexEvents = FALSE,
                                                runCohortCharacterization = TRUE,
                                                runIncludedSourceConcepts = FALSE,
                                                runCohortOverlap = FALSE,
                                                runIncidenceRate = TRUE,
                                                runOrphanConcepts = FALSE,
                                                runTemporalCohortCharacterization = TRUE,
                                                runTimeDistributions = TRUE,
                                                runVisitContext = FALSE)
    }
}