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| #' Summarise concept use in patient-level data | ||
| #' | ||
| #' @param cdm A cdm object | ||
| #' @param omopTableName A character vector of the names of the tables to | ||
| #' summarise in the cdm object. | ||
| #' @param countBy Either "record" for record-level counts or "person" for | ||
| #' person-level counts | ||
| #' @param year TRUE or FALSE. If TRUE code use will be summarised by year. | ||
| #' @param sex TRUE or FALSE. If TRUE code use will be summarised by sex. | ||
| #' @param ageGroup A list of ageGroup vectors of length two. Code use will be | ||
| #' thus summarised by age groups. | ||
| #' @param sample An integer to sample the tables to only that number of records. | ||
| #' If NULL no sample is done. | ||
| #' @param dateRange A list containing the minimum and the maximum dates | ||
| #' defining the time range within which the analysis is performed. | ||
| #' | ||
| #' @return A summarised_result object with results overall and, if specified, by | ||
| #' strata. | ||
| #' | ||
| #' @export | ||
| #' | ||
| #' @examples | ||
| #' \donttest{ | ||
| #' library(OmopSketch) | ||
| #' library(CDMConnector) | ||
| #' library(duckdb) | ||
| #' | ||
| #' requireEunomia() | ||
| #' con <- dbConnect(duckdb(), eunomiaDir()) | ||
| #' cdm <- cdmFromCon(con = con, cdmSchema = "main", writeSchema = "main") | ||
| #' | ||
| #' summariseConceptIdCounts(cdm, "condition_occurrence") | ||
| #' } | ||
| #' | ||
| summariseConceptIdCounts <- function(cdm, | ||
| omopTableName, | ||
| countBy = "record", | ||
| year = FALSE, | ||
| sex = FALSE, | ||
| ageGroup = NULL, | ||
| sample = NULL, | ||
| dateRange = NULL) { | ||
| # initial checks | ||
| cdm <- omopgenerics::validateCdmArgument(cdm) | ||
| checkCountBy(countBy) | ||
| omopgenerics::assertLogical(year, length = 1) | ||
| omopgenerics::assertLogical(sex, length = 1) | ||
| omopgenerics::assertChoice(omopTableName, choices = omopgenerics::omopTables(), unique = TRUE) | ||
| ageGroup <- omopgenerics::validateAgeGroupArgument(ageGroup) | ||
| dateRange <- validateStudyPeriod(cdm, dateRange) | ||
| omopgenerics::assertNumeric(sample, integerish = TRUE, min = 1, null = TRUE, length = 1) | ||
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| # settings for the created results | ||
| set <- createSettings(result_type = "summarise_all_concept_counts", study_period = dateRange) | ||
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| # get strata | ||
| strata <- omopgenerics::combineStrata(c(strataCols(sex = sex, ageGroup = ageGroup), "year"[year])) | ||
| concepts <- c("concept_id", "concept_name") | ||
| stratax <- c(list(concepts), purrr::map(strata, \(x) c(concepts, x))) | ||
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| # how to count | ||
| counts <- c("records", "person_id")[c("record", "person") %in% countBy] | ||
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| # summarise counts | ||
| resultTables <- purrr::map(omopTableName, \(table) { | ||
| # initial table | ||
| omopTable <- dplyr::ungroup(cdm[[table]]) | ||
| conceptId <- omopgenerics::omopColumns(table = table, field = "standard_concept") | ||
| if (is.na(conceptId)) { | ||
| cli::cli_warn(c("!" = "No standard concept identified for {table}.")) | ||
| return(NULL) | ||
| } | ||
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| prefix <- omopgenerics::tmpPrefix() | ||
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| # restrict study period | ||
| omopTable <- restrictStudyPeriod(omopTable, dateRange) | ||
| if (is.null(omopTable)) return(NULL) | ||
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| # sample table | ||
| omopTable <- omopTable |> | ||
| sampleOmopTable(sample = sample, name = omopgenerics::uniqueTableName(prefix)) | ||
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| result <- omopTable |> | ||
| # add concept names | ||
| dplyr::rename(concept_id = dplyr::all_of(conceptId)) |> | ||
| dplyr::left_join( | ||
| cdm$concept |> | ||
| dplyr::select("concept_id", "concept_name"), | ||
| by = "concept_id" | ||
| ) |> | ||
| # add demographics and year | ||
| addStratifications( | ||
| indexDate = omopgenerics::omopColumns(table = table, field = "start_date"), | ||
| sex = sex, | ||
| ageGroup = ageGroup, | ||
| interval = dplyr::if_else(year, "years", "overall"), | ||
| intervalName = "year", | ||
| name = omopgenerics::uniqueTableName(prefix) | ||
| ) |> | ||
| # summarise results | ||
| summariseCountsInternal(stratax, counts) |> | ||
| dplyr::mutate(omop_table = .env$table) | ||
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| omopgenerics::dropSourceTable(cdm = cdm, name = dplyr::starts_with(prefix)) | ||
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| return(result) | ||
| }) |> | ||
| purrr::compact() | ||
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| if (length(resultTables) == 0) { | ||
| return(omopgenerics::emptySummarisedResult(settings = set)) | ||
| } | ||
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| resultTables |> | ||
| dplyr::bind_rows() |> | ||
| dplyr::mutate( | ||
| result_id = 1L, | ||
| cdm_name = omopgenerics::cdmName(cdm) | ||
| ) |> | ||
| omopgenerics::uniteGroup(cols = "omop_table") |> | ||
| omopgenerics::uniteStrata(cols = unique(unlist(strata)) %||% character()) |> | ||
| omopgenerics::uniteAdditional() |> | ||
| dplyr::mutate( | ||
| estimate_value = as.character(.data$estimate_value), | ||
| estimate_type = "integer", | ||
| variable_level = as.character(.data$concept_id) | ||
| ) |> | ||
| dplyr::rename("variable_name" = "concept_name") |> | ||
| dplyr::select(!"concept_id") |> | ||
| omopgenerics::newSummarisedResult(settings = set) | ||
| } |
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