tests/testthat/test-summariseConceptSetCounts.R

In OmopSketch: Characterise Tables of an OMOP Common Data Model Instance

test_that("summarise code use - eunomia", {
  skip_on_cran()
  cdm <- cdmEunomia()
  acetiminophen <- c(
    1125315, 1127433, 40229134,
    40231925, 40162522, 19133768, 1127078
  )
  poliovirus_vaccine <- c(40213160)
  cs <- list(
    acetiminophen = acetiminophen,
    poliovirus_vaccine = poliovirus_vaccine
  )
  startNames <- CDMConnector::listSourceTables(cdm)
  results <- summariseConceptSetCounts(
    cdm = cdm,
    conceptSet = cs,
    interval = "years",
    countBy = c("record", "person"),
    concept = TRUE,
    sex = TRUE,
    ageGroup = list(
      c(0, 17),
      c(18, 65),
      c(66, 100)
    )
  )
  endNames <- CDMConnector::listSourceTables(cdm)
  expect_true(length(setdiff(endNames, startNames)) == 0)

  # Check result type
  checkResultType(results, "summarise_concept_set_counts")

  # min cell counts:
  expect_equal(
    omopgenerics::suppress(results, 5) |>
      omopgenerics::splitAdditional() |>
      dplyr::filter(
        strata_level == "overall",
        variable_name == "Number records",
        standard_concept_id == "overall",
        time_interval == "1909-01-01 to 1909-12-31",
        group_level == "acetiminophen"
      ) |>
      dplyr::pull("estimate_value"),
    "-"
  )

  # check is a summarised result
  expect_true("summarised_result" %in% class(results))
  expect_equal(
    omopgenerics::resultColumns(),
    colnames(results)
  )

  # overall record count
  expect_true(results %>%
    dplyr::filter(
      group_name == "codelist_name",
      strata_name == "overall",
      strata_level == "overall",
      additional_level == "overall",
      group_level == "acetiminophen",
      variable_name == "Number records"
    ) %>%
    dplyr::pull("estimate_value") |>
    as.numeric() ==
    cdm$drug_exposure %>%
      dplyr::inner_join(cdm[["person"]] |> dplyr::select("person_id"), by = "person_id") |>
      dplyr::filter(drug_concept_id %in% c(acetiminophen)) %>%
      dplyr::tally() %>%
      dplyr::pull("n"))

  # overall person count
  expect_true(results %>%
    dplyr::filter(
      group_name == "codelist_name" &
        strata_name == "overall" &
        strata_level == "overall" &
        group_level == "acetiminophen" &
        variable_name == "Number subjects",
      additional_name == "overall"
    ) %>%
    dplyr::pull("estimate_value") |>
    as.numeric() ==
    cdm$drug_exposure %>%
      dplyr::filter(drug_concept_id %in% acetiminophen) %>%
      dplyr::select("person_id") %>%
      dplyr::distinct() %>%
      dplyr::tally() %>%
      dplyr::pull("n"))

  # by year
  # overall record count
  expect_true(results %>%
    omopgenerics::splitAdditional() |>
    dplyr::filter(
      group_name == "codelist_name" &
        strata_name == "overall" &
        time_interval == "2008-01-01 to 2008-12-31" &
        group_level == "acetiminophen" &
        variable_name == "Number records",
      standard_concept_name == "overall"
    ) %>%
    dplyr::pull("estimate_value") |>
    as.numeric() ==
    cdm$drug_exposure %>%
      dplyr::filter(drug_concept_id %in% acetiminophen) %>%
      dplyr::filter(year(drug_exposure_start_date) == 2008) %>%
      dplyr::tally() %>%
      dplyr::pull("n"))

  # overall person count
  expect_true(results %>%
    omopgenerics::splitAdditional() |>
    dplyr::filter(
      group_name == "codelist_name" &
        strata_name == "overall" &
        time_interval == "2008-01-01 to 2008-12-31" &
        group_level == "acetiminophen" &
        variable_name == "Number subjects",
      standard_concept_name == "overall"
    ) %>%
    dplyr::pull("estimate_value") |>
    as.numeric() ==
    cdm$drug_exposure %>%
      dplyr::filter(drug_concept_id %in% acetiminophen) %>%
      dplyr::filter(year(drug_exposure_start_date) == 2008) %>%
      dplyr::select("person_id") %>%
      dplyr::distinct() %>%
      dplyr::tally() %>%
      dplyr::pull("n"))

  # by age group and sex
  # overall record count
  expect_true(results %>%
    dplyr::filter(group_name == "codelist_name" &
      strata_name == "sex" &
      strata_level == "Male" &
      group_level == "acetiminophen" &
      variable_name == "Number records" &
      additional_name == "overall") %>%
    dplyr::pull("estimate_value") |>
    as.numeric() ==
    cdm$drug_exposure %>%
      dplyr::filter(drug_concept_id %in% acetiminophen) %>%
      PatientProfiles::addSex() %>%
      dplyr::filter(sex == "Male") %>%
      dplyr::tally() %>%
      dplyr::pull("n"))

  expect_true(results %>%
    dplyr::filter(
      group_name == "codelist_name" &
        strata_name == "age_group &&& sex" &
        strata_level == "18 to 65 &&& Male" &
        group_level == "acetiminophen" &
        variable_name == "Number records",
      additional_name == "overall"
    ) %>%
    dplyr::pull("estimate_value") |>
    as.numeric() ==
    cdm$drug_exposure %>%
      dplyr::filter(drug_concept_id %in% acetiminophen) %>%
      PatientProfiles::addAge(indexDate = "drug_exposure_start_date") %>%
      PatientProfiles::addSex() %>%
      dplyr::filter(sex == "Male" &
        age >= "18" &
        age <= "65") %>%
      dplyr::tally() %>%
      dplyr::pull("n"))

  # overall person count
  expect_true(results %>%
    dplyr::filter(
      group_name == "codelist_name" &
        strata_name == "age_group &&& sex" &
        strata_level == "18 to 65 &&& Male" &
        group_level == "acetiminophen" &
        variable_name == "Number subjects",
      additional_name == "overall"
    ) %>%
    dplyr::pull("estimate_value") |>
    as.numeric() ==
    cdm$drug_exposure %>%
      dplyr::filter(drug_concept_id %in% acetiminophen) %>%
      PatientProfiles::addAge(indexDate = "drug_exposure_start_date") %>%
      PatientProfiles::addSex() %>%
      dplyr::filter(sex == "Male" &
        age >= "18" &
        age <= "65") %>%
      dplyr::select("person_id") %>%
      dplyr::distinct() %>%
      dplyr::tally() %>%
      dplyr::pull("n"))

  results1 <- summariseConceptSetCounts(
    cdm = cdm,
    conceptSet = cs,
    interval = "years",
    concept = FALSE,
    sex = TRUE,
    ageGroup = list(
      c(0, 17),
      c(18, 65),
      c(66, 100)
    )
  )

  expect_equal(
    results1 |>
      omopgenerics::splitAdditional() |>
      dplyr::filter(variable_name == "Number records") |>
      dplyr::arrange(dplyr::across(dplyr::everything())),
    results |>
      omopgenerics::splitAdditional() |>
      dplyr::filter(variable_name == "Number records", standard_concept_name == "overall") |>
      dplyr::select(-c(starts_with("standard_"), starts_with("source_"), "domain_id")) |>
      dplyr::arrange(dplyr::across(dplyr::everything())),
    ignore_attr = TRUE
  )
  expect_true(results1 |>
    omopgenerics::splitAdditional() |>
    dplyr::filter(
      variable_name == "Number subjects",
      group_level == "acetiminophen",
      time_interval == "1909-01-01 to 1909-12-31",
      strata_level == "0 to 17"
    ) |>
    dplyr::pull("estimate_value") |>
    as.numeric() ==
    cdm$drug_exposure %>%
      dplyr::filter(drug_concept_id %in% acetiminophen) %>%
      PatientProfiles::addAge(indexDate = "drug_exposure_start_date") %>%
      PatientProfiles::addSex() %>%
      dplyr::filter(age >= "0", age <= "17", clock::get_year(drug_exposure_start_date) == 1909) |>
      dplyr::select("person_id") %>%
      dplyr::distinct() %>%
      dplyr::tally() %>%
      dplyr::pull("n"))
  expect_true(results1$group_level |> unique() |> length() == 2)

  results <- summariseConceptSetCounts(list("acetiminophen" = acetiminophen),
    cdm = cdm, countBy = "person",
    interval = "years",
    sex = FALSE,
    ageGroup = NULL
  )
  expect_true(nrow(results %>%
    dplyr::filter(variable_name == "Number subjects")) > 0)
  expect_true(nrow(results %>%
    dplyr::filter(variable_name == "Number records")) == 0)


  results <- summariseConceptSetCounts(list("acetiminophen" = acetiminophen),
    cdm = cdm, countBy = "record",
    interval = "years",
    sex = FALSE,
    ageGroup = NULL
  )
  expect_true(nrow(results %>%
    dplyr::filter(variable_name == "Number subjects")) == 0)
  expect_true(nrow(results %>%
    dplyr::filter(variable_name == "Number records")) > 0)

  # domains covered
  # condition
  expect_true(nrow(summariseConceptSetCounts(list(cs = c(4112343)),
    cdm = cdm,
    interval = "years",
    sex = FALSE,
    ageGroup = NULL
  )) > 1)

  # visit
  expect_true(nrow(summariseConceptSetCounts(list(cs = c(9201)),
    cdm = cdm,
    interval = "years",
    sex = FALSE,
    ageGroup = NULL
  )) > 1)

  # drug
  expect_true(nrow(summariseConceptSetCounts(list(cs = c(40213160)),
    cdm = cdm,
    interval = "years",
    sex = FALSE,
    ageGroup = NULL
  )) > 1)

  # measurement
  expect_true(nrow(summariseConceptSetCounts(list(cs = c(3006322)),
    cdm = cdm,
    interval = "years",
    sex = FALSE,
    ageGroup = NULL
  )) > 1)

  # procedure and condition
  expect_true(nrow(summariseConceptSetCounts(list(cs = c(4107731, 4112343)),
    cdm = cdm,
    interval = "years",
    sex = FALSE,
    ageGroup = NULL
  )) > 1)

  # no records
  expect_warning(results <- summariseConceptSetCounts(list(cs = c(999999)),
    cdm = cdm,
    interval = "years",
    sex = FALSE,
    ageGroup = NULL
  ))
  expect_true(nrow(results) == 0)

  # conceptSet NULL (but reduce the computational time by filtering concepts first)
  # cdm$concept <- cdm$concept |>
  #   dplyr::filter(grepl("k", concept_name))
  #
  # skip("conceptSet = NULL not supported yet")
  # results <- summariseConceptSetCounts(cdm = cdm,
  #                                   year = FALSE,
  #                                   sex = FALSE,
  #                                   ageGroup = NULL)
  #
  # results_concepts <- results |>
  #   dplyr::select(variable_name) |>
  #   dplyr::distinct() |>
  #   dplyr::pull()
  # concepts <- cdm$concept |>
  #   dplyr::select(concept_name) |>
  #   dplyr::distinct() |>
  #   dplyr::pull()
  #
  # expect_true(all(results_concepts %in% c("overall",concepts)))

  # check attributes
  results <- summariseConceptSetCounts(
    cdm = cdm,
    conceptSet = cs,
    interval = "years",
    sex = TRUE,
    ageGroup = list(
      c(0, 17),
      c(18, 65),
      c(66, 100)
    )
  )

  expect_true(omopgenerics::settings(results)$package_name == "OmopSketch")
  expect_true(omopgenerics::settings(results)$result_type == "summarise_concept_set_counts")
  expect_true(omopgenerics::settings(results)$package_version == packageVersion("OmopSketch"))

  # expected errors# expected errors
  expect_error(summariseConceptSetCounts("not a concept",
    cdm = cdm,
    interval = "years",
    sex = FALSE,
    ageGroup = NULL
  ))
  expect_error(summariseConceptSetCounts("123",
    cdm = cdm,
    interval = "years",
    sex = FALSE,
    ageGroup = NULL
  ))
  expect_error(summariseConceptSetCounts(list("123"), # not named
    cdm = cdm,
    interval = "years",
    sex = FALSE,
    ageGroup = NULL
  ))
  expect_error(summariseConceptSetCounts(list(a = 123),
    cdm = "not a cdm",
    interval = "years",
    sex = FALSE,
    ageGroup = NULL
  ))
  expect_error(summariseConceptSetCounts(list(a = 123),
    cdm = cdm,
    interval = "Maybe",
    sex = FALSE,
    ageGroup = NULL
  ))
  expect_error(summariseConceptSetCounts(list(a = 123),
    cdm = cdm,
    interval = "years",
    sex = "Maybe",
    ageGroup = NULL
  ))
  expect_error(summariseConceptSetCounts(list(a = 123),
    cdm = cdm,
    interval = "years",
    sex = FALSE,
    ageGroup = list(c(18, 17))
  ))
  expect_error(summariseConceptSetCounts(list(a = 123),
    cdm = cdm,
    interval = "years",
    sex = FALSE,
    ageGroup = list(
      c(0, 17),
      c(15, 20)
    )
  ))





  CDMConnector::cdmDisconnect(cdm)
})

test_that("summarise code use - mock data", {
  skip_on_cran()
  person <- tibble::tibble(
    person_id = c(1L, 2L),
    gender_concept_id = c(8532L, 8507L),
    year_of_birth = c(1997L, 1963L),
    month_of_birth = c(8L, 1L),
    day_of_birth = c(22L, 27L),
    race_concept_id = c(1L, 1L),
    ethnicity_concept_id = c(1L, 1L)
  )
  observation_period <- tibble::tibble(
    person_id = c(1L, 2L),
    observation_period_id = c(1L, 2L),
    observation_period_start_date = c(as.Date("2000-06-03"), as.Date("1999-05-04")),
    observation_period_end_date = c(as.Date("2013-08-03"), as.Date("2004-01-04")),
    period_type_concept_id = c(1L, 1L)
  )
  condition_occurrence <- tibble::tibble(
    person_id = c(1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L),
    condition_concept_id = c(1L, 3L, 5L, 1L, 5L, 5L, 17L, 17L),
    condition_start_date = c(
      as.Date("2002-06-30"), as.Date("2004-05-29"), as.Date("2001-12-20"),
      as.Date("2000-03-10"), as.Date("2000-02-25"), as.Date("1999-07-15"),
      as.Date("1999-06-06"), as.Date("2000-07-17")
    ),
    condition_end_date = c(
      as.Date("2004-09-30"), as.Date("2009-05-29"), as.Date("2008-12-20"),
      as.Date("2001-03-10"), as.Date("2001-12-25"), as.Date("2001-07-15"),
      as.Date("2002-06-06"), as.Date("2000-11-17")
    ),
    condition_occurrence_id = c(1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L),
    condition_type_concept_id = c(1L),
    condition_source_concept_id = c(as.integer(NA))
  )
  concept <- tibble::tibble(
    concept_id = c(1L, 3L, 5L, 17L),
    concept_name = c("Musculoskeletal disorder", "Arthritis", "Osteoarthritis of hip", "Arthritis"),
    domain_id = c("Condition"),
    standard_concept = c("S", "S", "S", NA),
    vocabulary_id = c("SNOMED", "SNOMED", "SNOMED", "ICD10"),
    concept_class_id = c("Clinical Finding", "Clinical Finding", "Clinical Finding", "ICD Code"),
    concept_code = c("1234"),
    valid_start_date = c(as.Date(NA)),
    valid_end_date = c(as.Date(NA))
  )

  cdm <- omopgenerics::cdmFromTables(
    tables = list(
      person = person,
      observation_period = observation_period,
      condition_occurrence = condition_occurrence,
      concept = concept
    ),
    cdmName = "mock data"
  )
  cdm <- CDMConnector::copyCdmTo(
    con = connection(), cdm = cdm, schema = schema()
  )

  conceptSet <- list(
    "Arthritis" = c(17, 3),
    "Musculoskeletal disorder" = c(1),
    "Osteoarthritis of hip" = c(5)
  )

  result <- summariseConceptSetCounts(cdm, conceptSet)

  # Arthritis (codes 3 and 17), one record of 17 per ind and one record of 3 ind 1
  expect_equal(
    result |>
      omopgenerics::splitAdditional() |>
      dplyr::filter(
        standard_concept_name == "Arthritis",
        strata_level == "overall"
      ) |>
      dplyr::arrange(standard_concept_id, variable_name) |>
      dplyr::pull(estimate_value),
    c("2", "1", "1", "1")
  )

  # Osteoarthritis (code 5), two records ind 2, one record ind 1
  expect_equal(
    result |>
      omopgenerics::splitAdditional() |>
      dplyr::filter(
        standard_concept_name == "Osteoarthritis of hip",
        strata_level == "overall"
      ) |>
      dplyr::arrange(standard_concept_id, variable_name) |>
      dplyr::pull(estimate_value),
    c("3", "2")
  )

  # Musculoskeletal disorder (code 1), one record each ind
  expect_equal(
    result |>
      omopgenerics::splitAdditional() |>
      dplyr::filter(
        standard_concept_name == "Musculoskeletal disorder",
        strata_level == "overall"
      ) |>
      dplyr::arrange(standard_concept_id, variable_name) |>
      dplyr::pull(estimate_value),
    c("2", "2")
  )

  result <- summariseConceptSetCounts(cdm, conceptSet, ageGroup = list(c(0, 2), c(3, 150)), sex = TRUE)
  # Individuals belong to the same age group but to different sex groups

  # Arthritis (codes 3 and 17), one record of each per ind
  expect_equal(
    result |>
      omopgenerics::splitAdditional() |>
      dplyr::filter(standard_concept_name == "Arthritis" & strata_level == "Male") |>
      dplyr::arrange(standard_concept_id, variable_name) |>
      dplyr::pull(estimate_value),
    c("2", "1")
  )
  expect_equal(
    result |>
      omopgenerics::splitAdditional() |>
      dplyr::filter(standard_concept_name == "Arthritis" & strata_level == "3 to 150 &&& Male") |>
      dplyr::arrange(standard_concept_id, variable_name) |>
      dplyr::pull(estimate_value),
    c("2", "1")
  )
  expect_equal(
    result |>
      omopgenerics::splitAdditional() |>
      dplyr::filter(standard_concept_name == "Arthritis" & strata_level == "3 to 150") |>
      dplyr::arrange(standard_concept_id, variable_name) |>
      dplyr::pull(estimate_value),
    c("2", "1", "1", "1")
  )

  # Osteoarthritis of hip (code 5), two records ind 2 and one ind 1
  expect_equal(
    result |>
      omopgenerics::splitAdditional() |>
      dplyr::filter(standard_concept_name == "Osteoarthritis of hip" & strata_level == "Female") |>
      dplyr::tally() |>
      dplyr::pull(),
    2
  )

  # Musculoskeletal disorder (code 1), one record each ind
  expect_equal(
    result |>
      omopgenerics::splitAdditional() |>
      dplyr::filter(standard_concept_name == "Musculoskeletal disorder" & strata_level == "3 to 150 &&& Female") |>
      dplyr::arrange(standard_concept_id, variable_name) |>
      dplyr::pull(estimate_value),
    c("1", "1")
  )
  expect_equal(
    result |>
      omopgenerics::splitAdditional() |>
      dplyr::filter(standard_concept_name == "Musculoskeletal disorder" & strata_level == "3 to 150 &&& Male") |>
      dplyr::arrange(standard_concept_id, variable_name) |>
      dplyr::pull(estimate_value),
    c("1", "1")
  )
  expect_equal(
    result |>
      omopgenerics::splitAdditional() |>
      dplyr::filter(standard_concept_name == "Musculoskeletal disorder" & strata_level == "3 to 150") |>
      dplyr::arrange(standard_concept_id, variable_name) |>
      dplyr::pull(estimate_value),
    c("2", "2")
  )
  expect_equal(
    result |>
      omopgenerics::splitAdditional() |>
      dplyr::filter(standard_concept_name == "Musculoskeletal disorder" & strata_level == "overall") |>
      dplyr::arrange(standard_concept_id, variable_name) |>
      dplyr::pull(estimate_value),
    c("2", "2")
  )

  PatientProfiles::mockDisconnect(cdm)
})

test_that("plot concept set counts works", {
  skip_on_cran()
  # Load mock database ----
  cdm <- cdmEunomia()

  # summariseInObservationPlot plot ----
  x <- summariseConceptSetCounts(cdm, conceptSet = list(codes = c(40213160)))
  expect_error(plotConceptSetCounts(x))
  x <- x |> dplyr::filter(variable_name == "Number records")
  expect_no_error(plotConceptSetCounts(x))
  expect_true(inherits(plotConceptSetCounts(x), "ggplot"))

  x <- summariseConceptSetCounts(cdm,
    conceptSet = list(
      "polio" = c(40213160),
      "acetaminophen" = c(1125315, 1127433, 40229134, 40231925, 40162522, 19133768, 1127078)
    )
  )
  expect_error(plotConceptSetCounts(x))
  x <- x |> dplyr::filter(variable_name == "Number records")
  expect_no_error(plotConceptSetCounts(x))
  expect_message(plotConceptSetCounts(x))
  expect_no_error(plotConceptSetCounts(x, facet = "codelist_name"))
  expect_no_error(plotConceptSetCounts(x, colour = "codelist_name"))

  x <- x |> dplyr::filter(result_id == -1)
  expect_error(plotInObservation(x))

  PatientProfiles::mockDisconnect(cdm = cdm)
})

test_that("dateRange argument works", {
  skip_on_cran()
  # Load mock database ----
  cdm <- cdmEunomia()

  expect_no_error(summariseConceptSetCounts(cdm, conceptSet = list("polio" = c(40213160)), dateRange = as.Date(c("1930-01-01", "2018-01-01"))))
  expect_message(x <- summariseConceptSetCounts(cdm, conceptSet = list("polio" = c(40213160)), dateRange = as.Date(c("1930-01-01", "2025-01-01"))))
  observationRange <- cdm$observation_period |>
    dplyr::summarise(
      minobs = min(.data$observation_period_start_date, na.rm = TRUE),
      maxobs = max(.data$observation_period_end_date, na.rm = TRUE)
    )
  expect_no_error(y <- summariseConceptSetCounts(cdm, conceptSet = list("polio" = c(40213160)), dateRange = as.Date(c("1930-01-01", observationRange |> dplyr::pull("maxobs")))))
  expect_equal(x, y, ignore_attr = TRUE)
  expect_false(settings(x)$study_period_end == settings(y)$study_period_end)
  expect_error(summariseConceptSetCounts(cdm, conceptSet = list("polio" = c(40213160)), dateRange = as.Date(c("2015-01-01", "2014-01-01"))))
  expect_warning(z <- summariseConceptSetCounts(cdm, conceptSet = list("polio" = c(40213160)), dateRange = as.Date(c("2020-01-01", "2021-01-01"))))
  expect_equal(z, omopgenerics::emptySummarisedResult(), ignore_attr = TRUE)
  expect_equal(summariseConceptSetCounts(cdm, conceptSet = list("polio" = c(40213160)), dateRange = as.Date(c("1930-01-01", NA))), y, ignore_attr = TRUE)
  checkResultType(z, "summarise_concept_set_counts")
  expect_equal(colnames(settings(z)), colnames(settings(x)))
  PatientProfiles::mockDisconnect(cdm = cdm)
})

test_that("interval argument works", {
  skip_on_cran()
  # Load mock database ----
  cdm <- cdmEunomia()
  expect_no_error(y <- summariseConceptSetCounts(list("polio" = c(40213160)),
    cdm = cdm,
    interval = "years"
  ))

  expect_no_error(o <- summariseConceptSetCounts(list("polio" = c(40213160)),
    cdm = cdm,
    interval = "overall"
  ))
  expect_no_error(q <- summariseConceptSetCounts(list("polio" = c(40213160)),
    cdm = cdm,
    interval = "quarters"
  ))
  expect_no_error(m <- summariseConceptSetCounts(list("polio" = c(40213160)),
    cdm = cdm,
    interval = "months"
  ))



  m_quarters <- m |>
    omopgenerics::splitAdditional() |>
    omopgenerics::pivotEstimates() |>
    dplyr::filter(time_interval != "overall" & variable_name == "Number records" & standard_concept_id == 40213160) |>
    dplyr::mutate(
      start_date = as.Date(sub(" to .*", "", time_interval)),
      quarter_start = lubridate::quarter(start_date, type = "date_first"),
      quarter_end = lubridate::quarter(start_date, type = "date_last"),
      quarter = paste(quarter_start, "to", quarter_end)
    ) |>
    dplyr::select(!c("time_interval", "start_date", "quarter_start", "quarter_end")) |>
    dplyr::group_by(quarter, ) |>
    dplyr::summarise(count = sum(count), .groups = "drop") |>
    dplyr::rename("time_interval" = quarter) |>
    dplyr::arrange(time_interval)

  q_quarters <- q |>
    omopgenerics::splitAdditional() |>
    omopgenerics::pivotEstimates() |>
    dplyr::filter(time_interval != "overall" & variable_name == "Number records" & standard_concept_id == 40213160) |>
    dplyr::select(time_interval, count) |>
    dplyr::arrange(time_interval)

  expect_equal(m_quarters, q_quarters)

  m_year <- m |>
    omopgenerics::splitAdditional() |>
    dplyr::filter(time_interval != "overall" & variable_name == "Number records" & standard_concept_id == 40213160) |>
    dplyr::mutate(
      # Extract the start date
      start_date = clock::date_parse(stringr::str_extract(time_interval, "^\\d{4}-\\d{2}-\\d{2}")),
      # Convert start_date to a year-month-day object and extract the year
      year = clock::get_year(clock::as_year_month_day(start_date))
    ) |>
    omopgenerics::pivotEstimates() |>
    dplyr::group_by(year) %>%
    dplyr::summarise(
      count = sum(count),
      .groups = "drop"
    ) |>
    dplyr::arrange(year)
  y_year <- y |>
    omopgenerics::splitAdditional() |>
    dplyr::filter(time_interval != "overall" & variable_name == "Number records" & standard_concept_id == 40213160) |>
    dplyr::mutate(
      # Extract the start date
      start_date = clock::date_parse(stringr::str_extract(time_interval, "^\\d{4}-\\d{2}-\\d{2}")),
      # Convert start_date to a year-month-day object and extract the year
      year = clock::get_year(clock::as_year_month_day(start_date))
    ) |>
    omopgenerics::pivotEstimates() |>
    dplyr::select(year, count) |>
    dplyr::arrange(year)

  expect_equal(m_year, y_year)
  o <- o |>
    omopgenerics::splitAdditional() |>
    dplyr::filter(variable_name == "Number records" & standard_concept_id == 40213160) |>
    omopgenerics::pivotEstimates() |>
    dplyr::select(count)

  expect_equal(y_year |> dplyr::summarise(count = sum(count)), o)


  q_year <- q |>
    omopgenerics::splitAdditional() |>
    dplyr::filter(time_interval != "overall" & variable_name == "Number records" & standard_concept_id == 40213160) |>
    dplyr::mutate(
      # Extract the start date
      start_date = clock::date_parse(stringr::str_extract(time_interval, "^\\d{4}-\\d{2}-\\d{2}")),
      # Convert start_date to a year-month-day object and extract the year
      year = clock::get_year(clock::as_year_month_day(start_date))
    ) |>
    omopgenerics::pivotEstimates() |>
    dplyr::group_by(year) %>%
    dplyr::summarise(
      count = sum(count),
      .groups = "drop"
    ) |>
    dplyr::arrange(year)

  expect_equal(q_year, y_year)
  PatientProfiles::mockDisconnect(cdm = cdm)
})