context("Testing apportioning")
# Test standard apportioning ####
test_that("NA values in admission date are correctly handled", {
expect_equal(
apportion("mssa", patient_location = "Unknown", patient_category = NA,
date_admitted = as.Date(NA_real_, origin = "01-01-1970"), specimen_date = as.Date("14/08/2017", "%d/%m/%Y"),
date_entered = as.Date("14/08/2017", "%d/%m/%Y")
),
1)
})
test_that("apportion.R does apportion cases that should be apportioned", {
expect_equal(apportion("mssa", "NHS Acute Trust", "In-patient",
date_admitted = lubridate::dmy("01-01-2015"), specimen_date =
lubridate::dmy("05-01-2015"), date_entered = lubridate::dmy("26-10-2015")), 1)
expect_equal(apportion("mssa", "Unknown", "",
date_admitted = as.Date(NA_real_, origin = "01/01/1970"), specimen_date =
lubridate::ymd("2012-10-16"), date_entered = lubridate::ymd("2012-10-23")), 0)
expect_equal(apportion("mssa", "", "In-patient",
date_admitted = lubridate::dmy("01-01-2015"), specimen_date =
lubridate::dmy("05-01-2015"), date_entered = lubridate::dmy("26-10-2015")), 1)
# trust apportion when patient location is blank
expect_equal(apportion("mssa", "", "Unknown",
date_admitted = lubridate::dmy("01-01-2015"), specimen_date =
lubridate::dmy("05-01-2015"), date_entered = lubridate::dmy("26-10-2015")), 1)
# trust apportion when patient category is blank
expect_equal(apportion("mssa", "NHS Acute Trust", "",
date_admitted = lubridate::dmy("01-01-2015"), specimen_date =
lubridate::dmy("05-01-2015"), date_entered = lubridate::dmy("26-10-2015")), 1)
# when both patient location and category are blank
expect_equal(apportion("mssa", NA_character_, NA_character_,
date_admitted = lubridate::dmy("01-01-2013"), specimen_date =
lubridate::dmy("05-01-2013"), date_entered = lubridate::dmy("26-10-2013")), 1)
# just for coverage stats
expect_equal(apportion("cdi", NA_character_, NA_character_,
date_admitted = lubridate::dmy("01-01-2013"), specimen_date =
lubridate::dmy("05-01-2013"), date_entered = lubridate::dmy("26-10-2013")), 1)
})
test_that("apportion.R does not trust apportion records less than two days after admission", {
expect_equal(apportion("mssa", "NHS Acute Trust", "In-patient", date_admitted =
lubridate::dmy("01-01-2015"), specimen_date = lubridate::dmy("01-01-2015"),
date_entered = lubridate::dmy("26-10-2015")), 0)
})
# Test apportion_prior_healthcare ####
test_that("apportion_prior_healthcare returns correct result depending on difference between date of admission and date of specimen",
{
# specimen on same day as admission
testdat <- data.frame(
patient_location = "NHS Acute Trust",
patient_category = "In-patient",
date_admitted = as.Date("01/01/2017", format = "%d/%m/%Y"),
date_specimen = as.Date("01/01/2017", format = "%d/%m/%Y"),
adm_3_mos = "no",
adm_4_wks = "no",
adm_12_wks = "no",
date_entered = as.Date("01/04/2017", format = "%d/%m/%Y"),
stringsAsFactors = FALSE)
expect_equal(
apportion_prior_healthcare(
patient_location = testdat$patient_location,
patient_category = testdat$patient_category,
testdat$date_admitted, testdat$date_specimen,
adm_3_mo = testdat$adm_3_mos, adm_4_weeks = testdat$adm_4_wks,
adm_12_weeks = testdat$adm_12_wks,
date_record_created = testdat$date_entered), "coca")
# 1 day difference
testdat <- data.frame(
patient_location = "NHS Acute Trust",
patient_category = "In-patient",
date_admitted = as.Date("01/01/2017", format = "%d/%m/%Y"),
date_specimen = as.Date("02/01/2017", format = "%d/%m/%Y"),
adm_3_mos = "no",
adm_4_wks = "no",
adm_12_wks = "no",
date_entered = as.Date("01/04/2017", format = "%d/%m/%Y"),
stringsAsFactors = FALSE)
expect_equal(
apportion_prior_healthcare(
patient_location = testdat$patient_location,
patient_category = testdat$patient_category,
testdat$date_admitted, testdat$date_specimen,
adm_3_mo = testdat$adm_3_mos, testdat$adm_4_wks,
testdat$adm_12_wks, testdat$date_entered), "coca")
# 2 days difference
testdat <- data.frame(
patient_location = "NHS Acute Trust",
patient_category = "In-patient",
date_admitted = as.Date("01/01/2017", format = "%d/%m/%Y"),
date_specimen = as.Date("03/01/2017", format = "%d/%m/%Y"),
adm_3_mos = "no",
adm_4_wks = "no",
adm_12_wks = "no",
date_entered = as.Date("01/04/2017", format = "%d/%m/%Y"),
stringsAsFactors = FALSE)
expect_equal(
apportion_prior_healthcare(
patient_location = testdat$patient_location,
patient_category = testdat$patient_category,
testdat$date_admitted, testdat$date_specimen,
adm_3_mo = testdat$adm_3_mos, testdat$adm_4_wks,
testdat$adm_12_wks, testdat$date_entered), "hoha")
})
test_that("Apportioning to coha works", {
testdat <- data.frame(
patient_location = "NHS Acute Trust",
patient_category = "In-patient",
date_admitted = as.Date("01/01/2017", format = "%d/%m/%Y"),
date_specimen = as.Date("01/01/2017", format = "%d/%m/%Y"),
adm_3_mos = "no",
adm_4_wks = "yes",
adm_12_wks = "no",
date_entered = as.Date("01/04/2017", format = "%d/%m/%Y"),
stringsAsFactors = FALSE)
expect_equal(
apportion_prior_healthcare(
testdat$patient_location,
testdat$patient_category,
testdat$date_admitted, testdat$date_specimen,
adm_3_mo = testdat$adm_3_mos, testdat$adm_4_wks,
testdat$adm_12_wks, testdat$date_entered), "coca")
# testing NA for adm at 3 months
testdat <- data.frame(
patient_location = "NHS Acute Trust",
patient_category = "In-patient",
date_admitted = as.Date("01/01/2017", format = "%d/%m/%Y"),
date_specimen = as.Date("01/01/2017", format = "%d/%m/%Y"),
adm_3_mos = NA_character_,
adm_4_wks = "yes",
adm_12_wks = "no",
date_entered = as.Date("01/04/2017", format = "%d/%m/%Y"),
stringsAsFactors = FALSE)
expect_equal(
apportion_prior_healthcare(
testdat$patient_location,
testdat$patient_category,
testdat$date_admitted, testdat$date_specimen,
adm_3_mo = testdat$adm_3_mos, testdat$adm_4_wks,
testdat$adm_12_wks, testdat$date_entered), "coca")
testdat <- data.frame(
patient_location = "NHS Acute Trust",
patient_category = "In-patient",
date_admitted = as.Date("01/01/2017", format = "%d/%m/%Y"),
date_specimen = as.Date("01/01/2017", format = "%d/%m/%Y"),
adm_3_mos = NA_character_,
adm_4_wks = NA_character_,
adm_12_wks = NA_character_,
date_entered = as.Date("01/04/2017", format = "%d/%m/%Y"),
stringsAsFactors = FALSE)
expect_equal(
apportion_prior_healthcare(
testdat$patient_location,
testdat$patient_category,
testdat$date_admitted, testdat$date_specimen,
adm_3_mo = testdat$adm_3_mos, testdat$adm_4_wks,
testdat$adm_12_wks, testdat$date_entered), "all_blank")
testdat <- data.frame(
patient_location = "NHS Acute Trust",
patient_category = "In-patient",
date_admitted = as.Date("01/01/2017", format = "%d/%m/%Y"),
date_specimen = as.Date("01/01/2017", format = "%d/%m/%Y"),
adm_3_mos = "yes",
adm_4_wks = "yes",
adm_12_wks = NA_character_,
date_entered = as.Date("01/04/2017", format = "%d/%m/%Y"),
stringsAsFactors = FALSE)
expect_equal(
apportion_prior_healthcare(
testdat$patient_location,
testdat$patient_category,
testdat$date_admitted, testdat$date_specimen,
adm_3_mo = testdat$adm_3_mos, testdat$adm_4_wks,
testdat$adm_12_wks, testdat$date_entered), "coha")
})
test_that("Apportioning to coia works", {
testdat <- data.frame(
patient_location = "GP",
patient_category = NA_character_,
date_admitted = as.Date(NA_character_, format = "%d/%m/%Y"),
date_specimen = as.Date("01/01/2017", format = "%d/%m/%Y"),
adm_3_mos = "yes",
adm_4_wks = "no",
adm_12_wks = "yes",
date_entered = as.Date("01/04/2017", format = "%d/%m/%Y"),
stringsAsFactors = FALSE)
expect_equal(
apportion_prior_healthcare(
patient_location = testdat$patient_location,
patient_category = testdat$patient_category,
testdat$date_admitted, testdat$date_specimen,
adm_3_mo = testdat$adm_3_mos, testdat$adm_4_wks,
testdat$adm_12_wks, testdat$date_entered), "coia")
testdat <- data.frame(
patient_location = "GP",
patient_category = NA_character_,
date_admitted = as.Date("01/01/2017", format = "%d/%m/%Y"),
date_specimen = as.Date("01/01/2017", format = "%d/%m/%Y"),
adm_3_mos = "yes",
adm_4_wks = "no",
adm_12_wks = NA_character_,
date_entered = as.Date("01/04/2017", format = "%d/%m/%Y"),
stringsAsFactors = FALSE)
expect_equal(
apportion_prior_healthcare(
testdat$patient_location,
testdat$patient_category,
testdat$date_admitted, testdat$date_specimen,
adm_3_mo = testdat$adm_3_mos, testdat$adm_4_wks,
testdat$adm_12_wks, testdat$date_entered), "coia")
})
test_that("Apportioning to coca works", {
testdat <- data.frame(
patient_location = "NHS Acute Trust",
patient_category = "In-patient",
date_admitted = as.Date("01/01/2017", format = "%d/%m/%Y"),
date_specimen = as.Date("01/01/2017", format = "%d/%m/%Y"),
adm_3_mos = "no",
adm_4_wks = "no",
adm_12_wks = "no",
date_entered = as.Date("01/04/2017", format = "%d/%m/%Y"),
stringsAsFactors = FALSE)
expect_equal(
apportion_prior_healthcare(
patient_location = testdat$patient_location,
patient_category = testdat$patient_category,
testdat$date_admitted, testdat$date_specimen,
adm_3_mo = testdat$adm_3_mos, testdat$adm_4_wks,
testdat$adm_12_wks, testdat$date_entered
), "coca")
testdat <- data.frame(
patient_location = "NHS Acute Trust",
patient_category = "In-patient",
date_admitted = as.Date("01/01/2017", format = "%d/%m/%Y"),
date_specimen = as.Date("01/01/2017", format = "%d/%m/%Y"),
adm_3_mos = "no",
adm_4_wks = NA_character_,
adm_12_wks = NA_character_,
date_entered = as.Date("01/04/2017", format = "%d/%m/%Y"),
stringsAsFactors = FALSE)
expect_equal(
apportion_prior_healthcare(
patient_location = testdat$patient_location,
patient_category = testdat$patient_category,
testdat$date_admitted, testdat$date_specimen,
adm_3_mo = testdat$adm_3_mos, testdat$adm_4_wks,
testdat$adm_12_wks, testdat$date_entered
), "coca")
testdat <- data.frame(
patient_location = "NHS Acute Trust",
patient_category = "In-patient",
date_admitted = as.Date("01/01/2017", format = "%d/%m/%Y"),
date_specimen = as.Date("01/01/2017", format = "%d/%m/%Y"),
adm_3_mos = "no",
adm_4_wks = "yes",
adm_12_wks = "yes",
date_entered = as.Date("01/04/2017", format = "%d/%m/%Y"),
stringsAsFactors = FALSE)
expect_equal(
apportion_prior_healthcare(
patient_location = testdat$patient_location,
patient_category = testdat$patient_category,
testdat$date_admitted, testdat$date_specimen,
adm_3_mo = testdat$adm_3_mos, testdat$adm_4_wks,
testdat$adm_12_wks, testdat$date_entered
), "coca")
testdat <- data.frame(
patient_location = "NHS Acute Trust",
patient_category = "In-patient",
date_admitted = as.Date("01/01/2017", format = "%d/%m/%Y"),
date_specimen = as.Date("01/01/2017", format = "%d/%m/%Y"),
adm_3_mos = "no",
adm_4_wks = NA,
adm_12_wks = NA,
date_entered = as.Date("01/04/2017", format = "%d/%m/%Y"),
stringsAsFactors = FALSE)
expect_equal(
apportion_prior_healthcare(
patient_location = testdat$patient_location,
patient_category = testdat$patient_category,
testdat$date_admitted, testdat$date_specimen,
adm_3_mo = testdat$adm_3_mos, testdat$adm_4_wks,
testdat$adm_12_wks, testdat$date_entered
), "coca")
# This shouldn't happen, but agreed change on basis that want worst case
# scenario to encourage trusts to enter data accurately.
testdat <- data.frame(
patient_location = "NHS Acute Trust",
patient_category = "In-patient",
date_admitted = as.Date("01/01/2017", format = "%d/%m/%Y"),
date_specimen = as.Date("01/01/2017", format = "%d/%m/%Y"),
adm_3_mos = "no",
adm_4_wks = "no",
adm_12_wks = "yes",
date_entered = as.Date("01/04/2017", format = "%d/%m/%Y"),
stringsAsFactors = FALSE)
expect_equal(
apportion_prior_healthcare(
patient_location = testdat$patient_location,
patient_category = testdat$patient_category,
testdat$date_admitted, testdat$date_specimen,
adm_3_mo = testdat$adm_3_mos, testdat$adm_4_wks,
testdat$adm_12_wks, testdat$date_entered
), "coca")
# This shouldn't happen, but agreed change on basis that want worst case
# scenario to encourage trusts to enter data accurately.
testdat <- data.frame(
patient_location = "NHS Acute Trust",
patient_category = "In-patient",
date_admitted = as.Date("01/01/2017", format = "%d/%m/%Y"),
date_specimen = as.Date("01/01/2017", format = "%d/%m/%Y"),
adm_3_mos = "no",
adm_4_wks = "yes",
adm_12_wks = "yes",
date_entered = as.Date("01/04/2017", format = "%d/%m/%Y"),
stringsAsFactors = FALSE)
expect_equal(
apportion_prior_healthcare(
patient_location = testdat$patient_location,
patient_category = testdat$patient_category,
testdat$date_admitted, testdat$date_specimen,
adm_3_mo = testdat$adm_3_mos, testdat$adm_4_wks,
testdat$adm_12_wks, testdat$date_entered
), "coca")
testdat <- data.frame(
patient_location = "NHS Acute Trust",
patient_category = "In-patient",
date_admitted = as.Date("01/01/2017", format = "%d/%m/%Y"),
date_specimen = as.Date("01/01/2017", format = "%d/%m/%Y"),
adm_3_mos = "no",
adm_4_wks = "yes",
adm_12_wks = NA_character_,
date_entered = as.Date("01/04/2017", format = "%d/%m/%Y"),
stringsAsFactors = FALSE)
expect_equal(
apportion_prior_healthcare(
patient_location = testdat$patient_location,
patient_category = testdat$patient_category,
testdat$date_admitted, testdat$date_specimen,
adm_3_mo = testdat$adm_3_mos, testdat$adm_4_wks,
testdat$adm_12_wks, testdat$date_entered
), "coca")
# Changed following on 26/04/2018 after discussion with Olisa. Moved such cases from COCA to COIA
# testdat <- data.frame(
# patient_location = "GP",
# patient_category = NA_character_,
# date_admitted = as.Date("NA", format = "%d/%m/%Y"),
# date_specimen = as.Date("01/01/2017", format = "%d/%m/%Y"),
# adm_3_mos = "yes",
# adm_4_wks = "no",
# adm_12_wks = "no",
# date_entered = as.Date("01/04/2017", format = "%d/%m/%Y"),
# stringsAsFactors = FALSE)
#
# expect_equal(
# apportion_prior_healthcare(
# patient_location = testdat$patient_location,
# patient_category = testdat$patient_category,
# testdat$date_admitted, testdat$date_specimen,
# adm_3_mo = testdat$adm_3_mos, testdat$adm_4_wks,
# testdat$adm_12_wks, testdat$date_entered
# ), "coca")
})
test_that("Irritating cases that are yes for 3 mo, but no for 4 weeks AND 12 weeks are coia", {
testdat <- data.frame(
patient_location = "NHS Acute Trust",
patient_category = "In-patient",
date_admitted = as.Date("01/01/2017", format = "%d/%m/%Y"),
date_specimen = as.Date("01/01/2017", format = "%d/%m/%Y"),
adm_3_mos = "Yes",
adm_4_wks = "No",
adm_12_wks = "No",
date_entered = as.Date("01/04/2017", format = "%d/%m/%Y"),
stringsAsFactors = FALSE)
expect_equal(
apportion_prior_healthcare(
patient_location = testdat$patient_location,
patient_category = testdat$patient_category,
testdat$date_admitted, testdat$date_specimen,
adm_3_mo = testdat$adm_3_mos, testdat$adm_4_wks,
testdat$adm_12_wks, testdat$date_entered
), "coia")
testdat <- data.frame(
patient_location = "NHS Acute Trust",
patient_category = "In-patient",
date_admitted = as.Date("01/01/2017", format = "%d/%m/%Y"),
date_specimen = as.Date("01/01/2017", format = "%d/%m/%Y"),
adm_3_mos = "Yes",
adm_4_wks = "No",
adm_12_wks = "",
date_entered = as.Date("01/04/2017", format = "%d/%m/%Y"),
stringsAsFactors = FALSE)
expect_equal(
apportion_prior_healthcare(
patient_location = testdat$patient_location,
patient_category = testdat$patient_category,
testdat$date_admitted, testdat$date_specimen,
adm_3_mo = testdat$adm_3_mos, testdat$adm_4_wks,
testdat$adm_12_wks, testdat$date_entered
), "coia")
})
test_that("Missings are correctly labelled", {
testdat <- data.frame(
patient_location = "NHS Acute Trust",
patient_category = "In-patient",
date_admitted = as.Date("01/01/2017", format = "%d/%m/%Y"),
date_specimen = as.Date("01/01/2017", format = "%d/%m/%Y"),
adm_3_mos = "Don't know",
adm_4_wks = "",
adm_12_wks = "",
date_entered = as.Date("01/04/2017", format = "%d/%m/%Y"),
stringsAsFactors = FALSE)
expect_equal(
apportion_prior_healthcare(
patient_location = testdat$patient_location,
patient_category = testdat$patient_category,
testdat$date_admitted, testdat$date_specimen,
adm_3_mo = testdat$adm_3_mos, testdat$adm_4_wks,
testdat$adm_12_wks, testdat$date_entered
), "unknown_3_mo")
testdat <- data.frame(
patient_location = "NHS Acute Trust",
patient_category = "In-patient",
date_admitted = as.Date("01/01/2017", format = "%d/%m/%Y"),
date_specimen = as.Date("01/01/2017", format = "%d/%m/%Y"),
adm_3_mos = NA_character_,
adm_4_wks = NA_character_,
adm_12_wks = NA_character_,
date_entered = as.Date("01/04/2017", format = "%d/%m/%Y"),
stringsAsFactors = FALSE)
expect_equal(
apportion_prior_healthcare(
patient_location = testdat$patient_location,
patient_category = testdat$patient_category,
testdat$date_admitted, testdat$date_specimen,
adm_3_mo = testdat$adm_3_mos, testdat$adm_4_wks,
testdat$adm_12_wks, testdat$date_entered
), "all_blank")
testdat <- data.frame(
patient_location = "NHS Acute Trust",
patient_category = "Outpatient",
date_admitted = as.Date(NA_character_, format = "%d/%m/%Y"),
date_specimen = as.Date("13/12/2018", format = "%d/%m/%Y"),
adm_3_mos = NA_character_,
adm_4_wks = "",
adm_12_wks = NA,
date_entered = as.Date("14/12/2018", format = "%d/%m/%Y"),
stringsAsFactors = FALSE)
expect_equal(
apportion_prior_healthcare(
patient_location = testdat$patient_location,
patient_category = testdat$patient_category,
testdat$date_admitted, testdat$date_specimen,
adm_3_mo = testdat$adm_3_mos, testdat$adm_4_wks,
testdat$adm_12_wks, testdat$date_entered
), "all_blank")
})
test_that("Apportioning by prior health care is vectorised", {
testdat <- data.frame(
patient_location = rep("NHS Acute Trust", 2),
patient_category = rep("In-patient", 2),
date_admitted = rep(as.Date("01/01/2017", format = "%d/%m/%Y"), 2),
date_specimen = as.Date(c("01/01/2017", "05/01/2017"), format = "%d/%m/%Y"),
adm_3_mos = rep("no", 2),
adm_4_wks = rep("no", 2),
adm_12_wks = rep("no", 2),
date_entered = rep(as.Date("01/04/2017", format = "%d/%m/%Y"), 2),
stringsAsFactors = FALSE)
expect_equal(
length(unique(apportion_prior_healthcare(
patient_location = testdat$patient_location,
patient_category = testdat$patient_category,
testdat$date_admitted, testdat$date_specimen,
adm_3_mo = testdat$adm_3_mos, testdat$adm_4_wks,
testdat$adm_12_wks, testdat$date_entered
))), 2)
})
test_that("Apportioning by prior health care returns NA when date record created earlier than 01/04/2017", {
testdat <- data.frame(
patient_location = "NHS Acute Trust",
patient_category = "In-patient",
date_admitted = as.Date("01/01/2017", format = "%d/%m/%Y"),
date_specimen = as.Date("01/01/2017", format = "%d/%m/%Y"),
adm_3_mos = "no",
adm_4_wks = "no",
adm_12_wks = "no",
date_entered = as.Date("31/03/2017", format = "%d/%m/%Y"),
stringsAsFactors = FALSE)
expect_equal(apportion_prior_healthcare(
patient_location = testdat$patient_location,
patient_category = testdat$patient_category,
testdat$date_admitted, testdat$date_specimen,
adm_3_mo = testdat$adm_3_mos,
testdat$adm_4_wks,
testdat$adm_12_wks, testdat$date_entered), NA)
})
test_that("Apportioning by prior health care works inside dplyr", {
testdat <- data.frame(
patient_location = rep("NHS Acute Trust", 2),
patient_category = rep("In-patient", 2),
date_admitted = rep(as.Date("01/01/2017", format = "%d/%m/%Y"), 2),
date_specimen = as.Date(c("01/01/2017", "05/01/2017"), format = "%d/%m/%Y"),
adm_3_mos = rep("no", 2),
adm_4_wks = rep("no", 2),
adm_12_wks = rep("no", 2),
date_entered = rep(as.Date("01/04/2017", format = "%d/%m/%Y"), 2),
stringsAsFactors = FALSE)
expect_equal(ncol(dplyr::mutate(testdat,
new_apportioned = apportion_prior_healthcare(
patient_location,
patient_category,
date_admitted, date_specimen, adm_3_mos,
adm_4_wks, adm_12_wks, date_entered))), 9
)
})
test_that("assertions work for healthcare apportioning algorithm", {
# 3 mo is one of Yes, No, Don't know
testdat <- data.frame(
patient_location = "NHS Acute Trust",
patient_category = "In-patient",
date_admitted = as.Date("01/01/2017", format = "%d/%m/%Y"),
date_specimen = as.Date("01/01/2017", format = "%d/%m/%Y"),
adm_3_mos = "Aardvark",
adm_4_wks = "yes",
adm_12_wks = "no",
date_entered = as.Date("01/04/2017", format = "%d/%m/%Y"),
stringsAsFactors = FALSE)
expect_error(apportion_prior_healthcare(
patient_location = testdat$patient_location,
patient_category = testdat$patient_category,
testdat$date_admitted, testdat$date_specimen, adm_3_mo = testdat$adm_3_mos,
testdat$adm_4_wks,
testdat$adm_12_wks, testdat$date_entered))
# dates are dates
testdat <- data.frame(
patient_location = "NHS Acute Trust",
patient_category = "In-patient",
date_admitted = "01/01/2017",
date_specimen = as.Date("01/01/2017", format = "%d/%m/%Y"),
adm_3_mos = "yes",
adm_4_wks = "yes",
adm_12_wks = "no",
date_entered = as.Date("01/04/2017", format = "%d/%m/%Y"),
stringsAsFactors = FALSE)
expect_error(apportion_prior_healthcare(
patient_location = testdat$patient_location,
patient_category = testdat$patient_category,
testdat$date_admitted, testdat$date_specimen,
adm_3_mo = testdat$adm_3_mos, testdat$adm_4_wks,
testdat$adm_12_wks, testdat$date_entered))
testdat <- data.frame(
patient_location = "NHS Acute Trust",
patient_category = "In-patient",
date_admitted = as.Date("01/01/2017", format = "%d/%m/%Y"),
date_specimen = "01/01/2017",
adm_3_mos = "yes",
adm_4_wks = "yes",
adm_12_wks = "no",
date_entered = as.Date("01/04/2017", format = "%d/%m/%Y"),
stringsAsFactors = FALSE)
expect_error(apportion_prior_healthcare(
patient_location = testdat$patient_location,
patient_category = testdat$patient_category,
testdat$date_admitted, testdat$date_specimen,
adm_3_mo = testdat$adm_3_mos,
testdat$adm_4_wks,
testdat$adm_12_wks, testdat$date_entered))
testdat <- data.frame(
patient_location = "NHS Acute Trust",
patient_category = "In-patient",
date_admitted = as.Date("01/04/2017", format = "%d/%m/%Y"),
date_specimen = as.Date("01/01/2017", format = "%d/%m/%Y"),
adm_3_mos = "yes",
adm_4_wks = "yes",
adm_12_wks = "no",
date_entered = "01/01/2017",
stringsAsFactors = FALSE)
expect_error(apportion_prior_healthcare(
patient_location = testdat$patient_location,
patient_category = testdat$patient_category,
testdat$date_admitted, testdat$date_specimen,
adm_3_mo = testdat$adm_3_mos,
testdat$adm_4_wks,
testdat$adm_12_wks, testdat$date_entered))
})
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