R/ssnap_measures.R
In md0u80c9/SSNAPStats: Stroke Sentinel National Audit Project (SSNAP) Statistics Calculations
#' Define available auditing measures
#'
#' These functions provide a list of all the available auditing
#' measures. The master list is retrieved using \code{ssnap_measures}
#' which is an amalgamation of all lists; lists of measures intended
#' for a particular cohort group are stored using the other functions
#' for code legibility and/or ease of access if you know you only
#' need a subset of the measures.
#' @importFrom rlang ":="
#' @importFrom rlang "!!"
#' @export
ssnap_measures <- list(
# * Casemix ---------------------------------------------------------
# * -----------------------------------------------------------------
# Gender ==========================================================
# F3.1-5 Proportions of men and women.
Gender = audit_measure(
stem_name = "Gender",
description = "Gender",
exclusions = NULL,
numerators = list(
"Male" = rlang::expr(.data[["S1IsMale"]]),
"Female" = rlang::expr(!.data[["S1IsMale"]])),
numerator_descriptors = list(
"Male" = "Male",
"Female" = "Female"),
new_numerators = tibble::tribble(
~numerator, ~fun, ~descriptor,
"Male",
rlang::expr(.data[["S1IsMale"]]),
"Male",
"Female",
rlang::expr(!.data[["S1IsMale"]]),
"Female"
),
csv_columns = "S1IsMale",
measure_type = "discrete"),
# AgeOnArrival ====================================================
# F4.1-3 Age distribution
# G1.3, H1.3 Median age.
AgeOnArrival = audit_measure(
stem_name = "AgeOnArrival",
description = "Age on arrival",
exclusions = NULL,
numerators = rlang::expr(.data[["S1AgeOnArrival"]]),
new_numerators = rlang::expr(.data[["S1AgeOnArrival"]]),
csv_columns = "S1AgeOnArrival",
measure_type = "continuous"),
# AgeOver80 =======================================================
# F4.4-6 Proportion aged > 80
AgeOver80 = audit_measure(
stem_name = "AgeOver80",
description = "Age over 80",
exclusions = NULL,
numerators = rlang::expr(.data[["S1AgeOnArrival"]] > 80),
new_numerators = rlang::expr(.data[["S1AgeOnArrival"]] > 80),
csv_columns = "S1AgeOnArrival",
measure_type = "discrete"),
#TODO Conditional medians for age distribution of men and women
# F4.7-4.9 Female age distribution
# F4.10-4.12 Male age distribution
# FemaleAgeOver80 =================================================
# F4.13-15 Females aged over 80
FemaleAgeOver80 = audit_measure(
stem_name = "FemaleAgeOver80",
description = "Women aged over 80",
exclusions = rlang::expr(!.data[["S1IsMale"]]),
numerators = rlang::expr(.data[["S1AgeOnArrival"]] > 80),
new_numerators = rlang::expr(.data[["S1AgeOnArrival"]] > 80),
csv_columns = c("S1AgeOnArrival", "S1IsMale"),
measure_type = "continuous"),
# MaleAgeOver80 ===================================================
# F4.16-18 Males aged over 80
MaleAgeOver80 = audit_measure(
stem_name = "MaleAgeOver80",
description = "Men aged over 80",
exclusions = rlang::expr(!.data[["S1IsMale"]]),
numerators = rlang::expr(.data[["S1AgeOnArrival"]] > 80),
new_numerators = rlang::expr(.data[["S1AgeOnArrival"]] > 80),
csv_columns = c("S1AgeOnArrival", "S1IsMale"),
measure_type = "continuous"),
# AgeOnArrivalGrouped =============================================
# F4.19-29 Age breakdown
AgeOnArrivalGrouped = audit_measure(
stem_name = "AgeOnArrivalGrouped",
description = "Age on arrival (grouped)",
exclusions = NULL,
numerators = rlang::exprs(
"LessThan60" = .data[["S1AgeOnArrival"]] < 60,
"60To69" = dplyr::between(.data[["S1AgeOnArrival"]], 60, 69),
"70To79" = dplyr::between(.data[["S1AgeOnArrival"]], 70, 79),
"80To89" = dplyr::between(.data[["S1AgeOnArrival"]], 80, 89),
"90OrMore" = .data[["S1AgeOnArrival"]] >= 90),
numerator_descriptors = list(
"LessThan60" = "Age less than 60",
"60To69" = "Age 60-69",
"70To79" = "Age 70-79",
"80To89" = "Age 80-89",
"90OrMore" = "Age 90+"),
new_numerators = tibble::tribble(
~numerator, ~fun, ~descriptor,
"LessThan60",
rlang::expr(.data[["S1AgeOnArrival"]] < 60),
"Age less than 60",
"60To69",
rlang::expr(dplyr::between(.data[["S1AgeOnArrival"]], 60, 69)),
"Age 60-69",
"70To79",
rlang::expr(dplyr::between(.data[["S1AgeOnArrival"]], 70, 79)),
"Age 70-79",
"80To89",
rlang::expr(dplyr::between(.data[["S1AgeOnArrival"]], 80, 89)),
"Age 80-89",
"90OrMore",
rlang::expr(.data[["S1AgeOnArrival"]] >= 90),
"Age 90+"),
csv_columns = "S1AgeOnArrival",
measure_type = "discrete"),
# EthnicityKnown ==================================================
# C6.1-6.3 Ethnicity known
EthnicityKnown = audit_measure(
stem_name = "EthnicityKnown",
description = "Ethnicity known",
exclusions = NULL,
numerators = rlang::expr(.data[["S1Ethnicity"]] != "Unknown"),
new_numerators = rlang::expr(.data[["S1Ethnicity"]] != "Unknown"),
csv_columns = "S1Ethnicity",
measure_type = "discrete"),
# * -----------------------------------------------------------------
# * Record creation -------------------------------------------------
ClockStartToRecordCreationHours = audit_measure(
stem_name = "ClockStartToRecordCreationHours",
description = "Clock start to record creation (hours)",
exclusions = NULL,
numerators = ssnap_field[["ClockStartToRecordCreationHours"]],
new_numerators = rlang::expr(ssnap_field[["ClockStartToRecordCreationHours"]]),
csv_columns = c("S1PatientClockStartDateTime", "CreatedDateTime"),
measure_type = "continuous"),
# * -----------------------------------------------------------------
# * Comorbidities ---------------------------------------------------
# * -----------------------------------------------------------------
# ComorbidityCount ================================================
# F5.1-5.13 Comorbidities
ComorbidityCount = audit_measure(
stem_name = "ComorbidityCount",
description = "Comorbidity count",
exclusions = NULL,
numerators = rlang::exprs(
"0" = !! ssnap_field[["Comorbidities"]] == 0,
"1" = !! ssnap_field[["Comorbidities"]] == 1,
"2" = !! ssnap_field[["Comorbidities"]] == 2,
"3" = !! ssnap_field[["Comorbidities"]] == 3,
"4" = !! ssnap_field[["Comorbidities"]] == 4,
"5" = !! ssnap_field[["Comorbidities"]] == 5),
numerator_descriptors = list(
"0" = "0 comorbidities",
"1" = "1 comorbidity",
"2" = "2 comorbidities",
"3" = "3 comorbidities",
"4" = "4 comorbidities",
"5" = "5 comorbidities"),
new_numerators = tibble::tribble(
~numerator, ~fun, ~descriptor,
"0",
rlang::expr(!! ssnap_field[["Comorbidities"]] == 0),
"0 comorbidities",
"1",
rlang::expr(!! ssnap_field[["Comorbidities"]] == 1),
"1 comorbidity",
"2",
rlang::expr(!! ssnap_field[["Comorbidities"]] == 2),
"2 comorbidities",
"3",
rlang::expr(!! ssnap_field[["Comorbidities"]] == 3),
"3 comorbidities",
"4",
rlang::expr(!! ssnap_field[["Comorbidities"]] == 4),
"4 comorbidities",
"5",
rlang::expr(!! ssnap_field[["Comorbidities"]] == 5),
"5 comorbidities"),
csv_columns = c("S2CoMCongestiveHeartFailure",
"S2CoMHypertension",
"S2CoMAtrialFibrillation",
"S2CoMDiabetes",
"S2CoMStrokeTIA"),
measure_type = "discrete"),
# CongestiveHeartFailure ==========================================
# F5.14-16 CHF before stroke
CongestiveHeartFailure = audit_measure(
stem_name = "CongestiveHeartFailure",
description = "Congestive heart failure",
exclusions = NULL,
numerators = rlang::expr(.data[["S2CoMCongestiveHeartFailure"]]),
new_numerators = rlang::expr(.data[["S2CoMCongestiveHeartFailure"]]),
csv_columns = "S2CoMCongestiveHeartFailure",
measure_type = "discrete"),
# Hypertension ====================================================
# F5.17-19 Hypertension before stroke
Hypertension = audit_measure(
stem_name = "Hypertension",
description = "Hypertension",
exclusions = NULL,
numerators = rlang::expr(.data[["S2CoMHypertension"]]),
new_numerators = rlang::expr(.data[["S2CoMHypertension"]]),
csv_columns = "S2CoMHypertension",
measure_type = "discrete"),
# Diabetes ========================================================
# F5.20-22 Diabetes before stroke
Diabetes = audit_measure(
stem_name = "Diabetes",
description = "Diabetes",
exclusions = NULL,
numerators = rlang::expr(.data[["S2CoMDiabetes"]]),
new_numerators = rlang::expr(.data[["S2CoMDiabetes"]]),
csv_columns = "S2CoMDiabetes",
measure_type = "discrete"),
# PreviousStrokeTIA ===============================================
# F5.23-25 Stroke or TIA before stroke
PreviousStrokeTIA = audit_measure(
stem_name = "PreviousStrokeTIA",
description = "Previous stroke or TIA",
exclusions = NULL,
numerators = rlang::expr(.data[["S2CoMStrokeTIA"]]),
new_numerators = rlang::expr(.data[["S2CoMStrokeTIA"]]),
csv_columns = "S2CoMStrokeTIA",
measure_type = "discrete"),
# * -----------------------------------------------------------------
# * Atrial fibrillation ---------------------------------------------
# * -----------------------------------------------------------------
# AtrialFibrillation ==============================================
# F6.1-3 Atrial fibrillation (AF) before stroke
AtrialFibrillation = audit_measure(
stem_name = "AtrialFibrillation",
description = "Previously known atrial fibrillation",
exclusions = NULL,
numerators = rlang::expr(.data[["S2CoMAtrialFibrillation"]]),
new_numerators = rlang::expr(.data[["S2CoMAtrialFibrillation"]]),
csv_columns = "S2CoMAtrialFibrillation",
measure_type = "discrete"),
# AFOnAntiplatelet ================================================
# F6.4-10 Atrial fibrillation (AF) before stroke
AFOnAntiplatelet = audit_measure(
stem_name = "AFOnAntiplatelet",
description = "Previous atrial fibrillation on antiplatelets",
exclusions = NULL,
numerators = rlang::exprs(
"Yes" = .data[["S2CoMAFAntiplatelet"]] == "Y",
"No" = .data[["S2CoMAFAntiplatelet"]] == "N",
"NoBut" = .data[["S2CoMAFAntiplatelet"]] == "NB"),
numerator_descriptors = list("Yes", "No", "No but"),
new_numerators = tibble::tribble(
~numerator, ~fun, ~descriptor,
"Yes",
rlang::expr(.data[["S2CoMAFAntiplatelet"]] == "Y"),
"Yes",
"No",
rlang::expr(.data[["S2CoMAFAntiplatelet"]] == "N"),
"No",
"NoBut",
rlang::expr(.data[["S2CoMAFAntiplatelet"]] == "NB"),
"No but"),
csv_columns = "S2CoMAFAntiplatelet",
measure_type = "discrete"),
# AFOnAnticoagulant ===============================================
# F6.11-17 Atrial fibrillation (AF) before stroke
AFOnAnticoagulant = audit_measure(
stem_name = "AFOnAnticoagulant",
description = "Previous atrial fibrillation on anticoagulants",
exclusions = NULL,
numerators = rlang::exprs(
"Yes" = .data[["S2CoMAFAnticoagulent"]] == "Y",
"No" = .data[["S2CoMAFAnticoagulent"]] == "N",
"NoBut" = .data[["S2CoMAFAnticoagulent"]] == "NB"),
numerator_descriptors = list("Yes", "No", "No but"),
new_numerators = tibble::tribble(
~numerator, ~fun, ~descriptor,
"Yes",
rlang::expr(.data[["S2CoMAFAnticoagulent"]] == "Y"),
"Yes",
"No",
rlang::expr(.data[["S2CoMAFAnticoagulent"]] == "N"),
"No",
"NoBut",
rlang::expr(.data[["S2CoMAFAnticoagulent"]] == "NB"),
"No but"),
csv_columns = "S2CoMAFAnticoagulent",
measure_type = "discrete"),
# AFMeds ==========================================================
# F6.18-26 Atrial fibrillation (AF) before stroke
AFMeds = audit_measure(
stem_name = "AFMeds",
description = "Atrial fibrillation medication",
exclusions = NULL,
numerators = rlang::exprs(
"Both" = (.data[["S2CoMAFAnticoagulent"]] == "Y")
& (.data[["S2CoMAFAntiplatelet"]] == "Y"),
"Anticoagulant" = (.data[["S2CoMAFAnticoagulent"]] == "Y")
& (.data[["S2CoMAFAntiplatelet"]] != "Y"),
"Antiplatelet" = (.data[["S2CoMAFAnticoagulent"]] != "Y")
& (.data[["S2CoMAFAntiplatelet"]] == "Y"),
"None" = (.data[["S2CoMAFAnticoagulent"]] != "Y")
& (.data[["S2CoMAFAntiplatelet"]] != "Y")),
numerator_descriptors = list(
"Both" = "Both anticoagulant and antiplatelet medication",
"Anticoagulant" = "Anticoagulant medication only",
"Antiplatelet" = "Antiplatelet medication only",
"None" = "Neither medication"),
new_numerators = tibble::tribble(
~numerator, ~fun, ~descriptor,
"Both",
rlang::expr((.data[["S2CoMAFAnticoagulent"]] == "Y")
& (.data[["S2CoMAFAntiplatelet"]] == "Y")),
"Both anticoagulant and antiplatelet medication",
"Anticoagulant",
rlang::expr((.data[["S2CoMAFAnticoagulent"]] == "Y")
& (.data[["S2CoMAFAntiplatelet"]] != "Y")),
"Anticoagulant medication only",
"Antiplatelet",
rlang::expr((.data[["S2CoMAFAnticoagulent"]] != "Y")
& (.data[["S2CoMAFAntiplatelet"]] == "Y")),
"Antiplatelet medication only",
"None",
rlang::expr((.data[["S2CoMAFAnticoagulent"]] != "Y")
& (.data[["S2CoMAFAntiplatelet"]] != "Y")),
"Neither medication"),
csv_columns = c("S2CoMAFAnticoagulent", "S2CoMAFAntiplatelet"),
measure_type = "discrete"),
# * -----------------------------------------------------------------
# * StrokeType ------------------------------------------------------
# * -----------------------------------------------------------------
# F7.1-7 Stroke type
# G1.9-10 Infarction / PIH
# H1.9-10 Infarction / PIH
StrokeType = audit_measure(
stem_name = "StrokeType",
description = "Stroke type",
exclusions = NULL,
numerators = rlang::exprs(
"Infarct" = .data[["S2StrokeTypeIsInfarct"]],
"PIH" = !.data[["S2StrokeTypeIsInfarct"]]),
numerator_descriptors = list(
"Infarct" = "Infarction",
"PIH" = "Primary intracerebral haemorrhage"),
new_numerators = tibble::tribble(
~numerator, ~fun, ~descriptor,
"Infarct",
rlang::expr(.data[["S2StrokeTypeIsInfarct"]]),
"Infarction",
"PIH",
rlang::expr(!.data[["S2StrokeTypeIsInfarct"]]),
"Primary intracerebral haemorrhage"
),
csv_columns = "S2StrokeTypeIsInfarct",
measure_type = "discrete"),
# * Modified Rankin Score -------------------------------------------
# * -----------------------------------------------------------------
# F8.1-13 mRS before stroke
RankinBeforeStroke = audit_measure(
stem_name = "RankinBeforeStroke",
description = "Pre-stroke Rankin score",
exclusions = NULL,
numerators = rlang::exprs(
"0" = .data[["S2RankinBeforeStroke"]] == 0,
"1" = .data[["S2RankinBeforeStroke"]] == 1,
"2" = .data[["S2RankinBeforeStroke"]] == 2,
"3" = .data[["S2RankinBeforeStroke"]] == 3,
"4" = .data[["S2RankinBeforeStroke"]] == 4,
"5" = .data[["S2RankinBeforeStroke"]] == 5),
numerator_descriptors = list(
"0" = "0", "1" = "1", "2" = "2", "3" = "3",
"4" = "4", "5" = "5"),
new_numerators = tibble::tribble(
~numerator, ~fun, ~descriptor,
"0",
rlang::expr(.data[["S2RankinBeforeStroke"]] == 0),
"0",
"1",
rlang::expr(.data[["S2RankinBeforeStroke"]] == 1),
"1",
"2",
rlang::expr(.data[["S2RankinBeforeStroke"]] == 2),
"2",
"3",
rlang::expr(.data[["S2RankinBeforeStroke"]] == 3),
"3",
"4",
rlang::expr(.data[["S2RankinBeforeStroke"]] == 4),
"4",
"5",
rlang::expr(.data[["S2RankinBeforeStroke"]] == 5),
"5"),
csv_columns = "S2RankinBeforeStroke",
measure_type = "discrete"),
# * Modified Rankin Score Grouped -----------------------------------
# * -----------------------------------------------------------------
# G1.11-13 mRS grouping before stroke
# H1.11-13 mRS grouping before stroke
RankinBeforeStrokeGrouped = audit_measure(
stem_name = "RankinBeforeStrokeGrouped",
description = "Pre-stroke Rankin score",
exclusions = NULL,
numerators = rlang::exprs(
"0" = .data[["S2RankinBeforeStroke"]] == 0,
"1Or2" = (.data[["S2RankinBeforeStroke"]] == 1) |
(.data[["S2RankinBeforeStroke"]] == 2),
"3OrMore" = .data[["S2RankinBeforeStroke"]] > 2),
numerator_descriptors = list(
"0" = "Modified Rankin Scale (mRS) score before stroke: 0",
"1Or2" =
"Modified Rankin Scale (mRS) score before stroke: 1 or 2",
"3OrMore" =
"Modified Rankin Scale (mRS) score before stroke: 3, 4 or 5"),
new_numerators = tibble::tribble(
~numerator, ~fun, ~descriptor,
"0",
rlang::expr(.data[["S2RankinBeforeStroke"]] == 0),
"Modified Rankin Scale (mRS) score before stroke: 0",
"1Or2",
rlang::expr((.data[["S2RankinBeforeStroke"]] == 1) |
(.data[["S2RankinBeforeStroke"]] == 2)),
"Modified Rankin Scale (mRS) score before stroke: 1 or 2",
"3OrMore",
rlang::expr(.data[["S2RankinBeforeStroke"]] > 2),
"Modified Rankin Scale (mRS) score before stroke: 3, 4 or 5"),
csv_columns = "S2RankinBeforeStroke",
measure_type = "discrete"),
# * NIHSS -----------------------------------------------------------
# * -----------------------------------------------------------------
# LOCArrival ======================================================
# F9.1-9 NIHSS Level of consciousness at arrival
# Expressed as discrete values (ie. broken down by value)
LOCArrival = audit_measure(
stem_name = "LOCArrival",
description = "Level of consciousness on arrival",
exclusions = NULL,
numerators = rlang::exprs(
"0" = .data[["S2NihssArrivalLoc"]] == 0,
"1" = .data[["S2NihssArrivalLoc"]] == 1,
"2" = .data[["S2NihssArrivalLoc"]] == 2,
"3" = .data[["S2NihssArrivalLoc"]] == 3),
numerator_descriptors = list(
"0" = "0", "1" = "1", "2" = "2", "3" = "3"),
new_numerators = tibble::tribble(
~numerator, ~fun, ~descriptor,
"0", rlang::expr(.data[["S2NihssArrivalLoc"]] == 0), "0",
"1", rlang::expr(.data[["S2NihssArrivalLoc"]] == 1), "1",
"2", rlang::expr(.data[["S2NihssArrivalLoc"]] == 2), "2",
"3", rlang::expr(.data[["S2NihssArrivalLoc"]] == 3), "3"),
csv_columns = "S2NihssArrivalLoc",
measure_type = "discrete"),
# LOCArrivalGrouped ===============================================
# G1.14-16 LOC at arrival
# H1.14-16 LOC at arrival
LOCArrivalGrouped = audit_measure(
stem_name = "LOCArrivalGrouped",
description = "Level of consciousness on arrival",
exclusions = NULL,
numerators = rlang::exprs(
"0" = .data[["S2NihssArrivalLoc"]] == 0,
"1Or2" = (.data[["S2NihssArrivalLoc"]] == 1) |
(.data[["S2NihssArrivalLoc"]] == 2),
"3" = .data[["S2NihssArrivalLoc"]] == 3),
numerator_descriptors = list(
"0" = "Alert upon arrival",
"1Or2" = "Responds to voice or pain on arrival",
"3" = "Unresponsive on arrival"),
new_numerators = tibble::tribble(
~numerator, ~fun, ~descriptor,
"0",
rlang::expr(.data[["S2NihssArrivalLoc"]] == 0),
"Alert upon arrival",
"1Or2",
rlang::expr((.data[["S2NihssArrivalLoc"]] == 1) |
(.data[["S2NihssArrivalLoc"]] == 2)),
"Responds to voice or pain on arrival",
"3",
rlang::expr(.data[["S2NihssArrivalLoc"]] == 3),
"Unresponsive on arrival"),
csv_columns = "S2NihssArrivalLoc",
measure_type = "discrete"),
# WorstLOCFirst7Days ==============================================
# K4.1-9 Worst LOC in first 7 days
WorstLOCFirst7Days = audit_measure(
stem_name = "WorstLOCFirst7Days",
description = "Worst level of consciousness in the first 7 days from clock start",
exclusions = NULL,
numerators = rlang::exprs(
"0" = .data[["S5LocWorst7Days"]] == 0,
"1" = .data[["S5LocWorst7Days"]] == 1,
"2" = .data[["S5LocWorst7Days"]] == 2,
"3" = .data[["S5LocWorst7Days"]] == 3),
numerator_descriptors = list(
"0" = "Alert upon arrival",
"1" = "Responds to voice",
"2" = "Responds to pain",
"3" = "Unresponsive on arrival"),
new_numerators = tibble::tribble(
~numerator, ~fun, ~descriptor,
"0",
rlang::expr(.data[["S5LocWorst7Days"]] == 0),
"Alert upon arrival",
"1",
rlang::expr(.data[["S5LocWorst7Days"]] == 1),
"Responds to voice",
"2",
rlang::expr(.data[["S5LocWorst7Days"]] == 2),
"Responds to pain",
"3",
rlang::expr(.data[["S5LocWorst7Days"]] == 3),
"Unresponsive on arrival"),
csv_columns = "S5LocWorst7Days",
measure_type = "discrete"),
# NihssCompletion =================================================
# F9.10-16 Completeness of NIHSS score
NihssCompletion = audit_measure(
stem_name = "NihssCompletion",
description = "Completion of NIHSS score",
exclusions = NULL,
numerators = rlang::exprs(
"LOCOnly" = !!ssnap_field[["NihssComponentsComplete"]] == 1,
"Incomplete" = dplyr::between(
!!ssnap_field[["NihssComponentsComplete"]], 2, 14),
"Complete" = !!ssnap_field[["NihssComponentsComplete"]] == 15),
numerator_descriptors = list(
"LOCOnly" = "Level of consciousness (AVPU) only",
"Incomplete" = "Incomplete",
"Complete" = "Complete"),
new_numerators = tibble::tribble(
~numerator, ~fun, ~descriptor,
"LOCOnly",
rlang::expr(!!ssnap_field[["NihssComponentsComplete"]] == 1),
"Level of consciousness (AVPU) only",
"Incomplete",
rlang::expr(dplyr::between(
!!ssnap_field[["NihssComponentsComplete"]], 2, 14)),
"Incomplete",
"Complete",
rlang::expr(!!ssnap_field[["NihssComponentsComplete"]] == 15),
"Complete"),
csv_columns = c("S2NihssArrivalLoc",
"S2NihssArrivalLocQuestions",
"S2NihssArrivalLocCommands",
"S2NihssArrivalBestGaze",
"S2NihssArrivalVisual",
"S2NihssArrivalFacialPalsy",
"S2NihssArrivalMotorArmLeft",
"S2NihssArrivalMotorArmRight",
"S2NihssArrivalMotorLegLeft",
"S2NihssArrivalMotorLegRight",
"S2NihssArrivalLimbAtaxia",
"S2NihssArrivalSensory",
"S2NihssArrivalBestLanguage",
"S2NihssArrivalDysarthria",
"S2NihssArrivalExtinctionInattention"),
measure_type = "discrete"),
# NihssOnArrival ==================================================
# F9.28-30 NIHSS spread
# G1.17 Median NIHSS on arrival
# H1.17 Median NIHSS on arrival
NihssOnArrival = audit_measure(
stem_name = "NihssOnArrival",
description = "NIHSS score on arrival",
exclusions = NULL,
numerators = rlang::expr(.data[["S2NihssArrival"]]),
new_numerators = rlang::expr(.data[["S2NihssArrival"]]),
csv_columns = "S2NihssArrival",
# numerator_descriptors = list(
# "NIHSS at arrival if fully completed"),
measure_type = "continuous"),
# NihssOnArrivalGrouped ===========================================
# F9.17-27 NIHSS at arrival
NihssOnArrivalGrouped = audit_measure(
stem_name = "NihssOnArrivalGrouped",
description = "NIHSS score on arrival",
exclusions = NULL,
numerators = rlang::exprs(
"0" = .data[["S2NihssArrival"]] == 0,
"1To4" = dplyr::between(.data[["S2NihssArrival"]], 1, 4),
"5To15" = dplyr::between(.data[["S2NihssArrival"]], 5, 15),
"16To20" = dplyr::between(.data[["S2NihssArrival"]], 16, 20),
"21OrMore" = .data[["S2NihssArrival"]] >= 21),
numerator_descriptors = list(
"0" = "0",
"1To4" = "1 - 4",
"5To15" = "5 - 15",
"16To20" = "16 - 20",
"21OrMore" = "21 or more"),
new_numerators = tibble::tribble(
~numerator, ~fun, ~descriptor,
"0",
rlang::expr(.data[["S2NihssArrival"]] == 0),
"0",
"1To4",
rlang::expr(dplyr::between(.data[["S2NihssArrival"]], 1, 4)),
"1 - 4",
"5To15",
rlang::expr(dplyr::between(.data[["S2NihssArrival"]], 5, 15)),
"5 - 15",
"16To20",
rlang::expr(dplyr::between(.data[["S2NihssArrival"]], 16, 20)),
"16 - 20",
"21OrMore",
rlang::expr(.data[["S2NihssArrival"]] >= 21),
"21 or more"),
csv_columns = "S2NihssArrival",
measure_type = "discrete"),
# TODO NIHSS LOC if NIHSS incomplete
# * -----------------------------------------------------------------
# * Palliative Care -------------------------------------------------
# * -----------------------------------------------------------------
# EndOfLifeWithin72hrs ============================================
# F10.1-3 Palliative care in 72hrs
# G1.18 Palliative care in 72hrs
# H1.18 Palliative care in 72hrs
EndOfLifeWithin72hrs = audit_measure(
stem_name = "EndOfLifeWithin72hrs",
description = "End of life care within 72hrs",
exclusions = NULL,
numerators = rlang::expr(!is.na(
.data[["S3PalliativeCareDecisionDate"]])),
new_numerators = rlang::expr(!is.na(
.data[["S3PalliativeCareDecisionDate"]])),
csv_columns = "S3PalliativeCareDecisionDate",
measure_type = "discrete"),
# EndOfLifePathway ================================================
# F10.4-6 End of life pathway use
EndOfLifePathway = audit_measure(
stem_name = "EndOfLifePathway",
description = "Is the patient on an end of life pathway",
exclusions = rlang::expr(is.na(
.data[["S3PalliativeCareDecisionDate"]])),
numerators = rlang::expr(!is.na(
.data[["S3EndOfLifePathway"]])),
new_numerators =
rlang::expr(!is.na(.data[["S3EndOfLifePathway"]])),
csv_columns = c("S3EndOfLifePathway",
"S3PalliativeCareDecisionDate"),
measure_type = "discrete"),
# ClockStartToPalliativeCare72Hours ===============================
# F10.7 Clock start to palliative care decision (days) spread
ClockStartToPalliativeCare72Hours = audit_measure(
stem_name = "ClockStartToPalliativeCare72Hours",
description = "Is the patient on an end of life pathway",
exclusions = NULL,
numerators = ssnap_field[["ClockStartToPalliativeCare72Days"]],
new_numerators =
ssnap_field[["ClockStartToPalliativeCare72Days"]],
csv_columns = c("S1PatientClockStartDateTime",
"S3PalliativeCareDecisionDate"),
measure_type = "continuous"),
# * -----------------------------------------------------------------
# * In hospital stroke ----------------------------------------------
# * -----------------------------------------------------------------
# F11.1-3 Was the stroke in hospital?
OnsetInHospital = audit_measure(
stem_name = "OnsetInHospital",
description = "Onset in hospital",
exclusions = NULL,
numerators = rlang::expr(!is.na(.data[["S1OnsetInHospital"]])),
new_numerators =
rlang::expr(!is.na(.data[["S1OnsetInHospital"]])),
csv_columns = "S1OnsetInHospital",
measure_type = "discrete"),
# * Onset of symptoms -----------------------------------------------
# * -----------------------------------------------------------------
# OnsetDateAccuracy ===============================================
# G2.1-2.7 Date of symptom onset
# H2.1-2.7 Date of symptom onset
OnsetDateAccuracy = audit_measure(
stem_name = "OnsetDate",
description = "Accuracy of onset date",
exclusions = NULL,
numerators = rlang::exprs(
"Precise" = .data[["S1OnsetDateIsPrecise"]],
"Estimate" = !.data[["S1OnsetDateIsPrecise"]],
"DuringSleep" = is.na(.data[["S1OnsetDateIsPrecise"]])),
new_numerators = tibble::tribble(
~numerator, ~fun, ~descriptor,
"Precise",
rlang::expr(.data[["S1OnsetDateIsPrecise"]]),
"Precise",
"Estimate",
rlang::expr(!.data[["S1OnsetDateIsPrecise"]]),
"Best estimate",
"DuringSleep",
rlang::expr(is.na(.data[["S1OnsetDateIsPrecise"]])),
"During sleep"),
csv_columns = "S1OnsetDateIsPrecise",
measure_type = "discrete"),
# OnsetTimeAccuracy ===============================================
# G2.8-14 Time of symptom onset
# H2.8-14 Time of symptom onset
OnsetTimeAccuracy = audit_measure(
stem_name = "OnsetTime",
description = "Accuracy of onset time",
exclusions = NULL,
numerators = rlang::exprs(
"Precise" = .data[["S1OnsetTimeIsPrecise"]],
"Estimate" = !.data[["S1OnsetTimeIsPrecise"]],
"DuringSleep" = is.na(.data[["S1OnsetTimeIsPrecise"]])),
new_numerators = tibble::tribble(
~numerator, ~fun, ~descriptor,
"Precise",
rlang::expr(.data[["S1OnsetTimeIsPrecise"]]),
"Precise",
"Estimate",
rlang::expr(!.data[["S1OnsetTimeIsPrecise"]]),
"Best estimate",
"DuringSleep",
rlang::expr(is.na(.data[["S1OnsetTimeIsPrecise"]])),
"During sleep"),
csv_columns = "S1OnsetTimeIsPrecise",
measure_type = "discrete"),
# OnsetTimeKnown ==================================================
# G2.15-17 Time of symptom onset known
# H2.15-17 Time of symptom onset known
OnsetTimeKnown = audit_measure(
stem_name = "OnsetTimeKnown",
description = "Onset time is known",
exclusions = NULL,
numerators = rlang::expr(!is.na(.data[["S1OnsetTimeIsPrecise"]])),
new_numerators =
rlang::expr(!is.na(.data[["S1OnsetTimeIsPrecise"]])),
csv_columns = "S1OnsetTimeIsPrecise",
measure_type = "discrete"),
# OnsetToArrivalGrouped ===========================================
# H2.18-28 Onset to arrival times (grouped)
OnsetToArrivalGrouped = audit_measure(
stem_name = "OnsetToArrival",
description = "Onset to arrival",
exclusions = NULL,
numerators = rlang::exprs(
"Within4hrs" = !!ssnap_field[["OnsetToArrivalTimeMins"]]
<= (4 * 60),
"4To12hrs" = dplyr::between(
!!ssnap_field[["OnsetToArrivalTimeMins"]],
(4 * 60), (12 * 60)),
"12To24hrs" = dplyr::between(
!!ssnap_field[["OnsetToArrivalTimeMins"]],
(12 * 60), (24 * 60)),
"24To72hrs" = dplyr::between(
!!ssnap_field[["OnsetToArrivalTimeMins"]],
(24 * 60), (72 * 60)),
"Over72hrs" = !!ssnap_field[["OnsetToArrivalTimeMins"]]
> (72 * 60)),
new_numerators = tibble::tribble(
~numerator, ~fun, ~descriptor,
"Within4hrs",
rlang::expr(
!!ssnap_field[["OnsetToArrivalTimeMins"]] <= (4 * 60)),
"Within 4 hours",
"4To12hrs",
rlang::expr(dplyr::between(
!!ssnap_field[["OnsetToArrivalTimeMins"]],
(4 * 60), (12 * 60))),
"4 to 12 hours",
"12To24hrs",
rlang::expr(dplyr::between(
!!ssnap_field[["OnsetToArrivalTimeMins"]],
(12 * 60), (24 * 60))),
"12 to 24 hours",
"24To72hrs",
rlang::expr(dplyr::between(
!!ssnap_field[["OnsetToArrivalTimeMins"]],
(24 * 60), (72 * 60))),
"24 to 72 hours",
"Over72hrs",
rlang::expr(
!!ssnap_field[["OnsetToArrivalTimeMins"]] > (72 * 60)),
"Over 72 hours"),
csv_columns = c("S1OnsetInHospital",
"S1OnsetDateIsPrecise",
"S1OnsetTimeIsPrecise",
"S1OnsetDateTime",
"S1PatientClockStartDateTime"),
measure_type = "discrete"),
# OnsetToArrivalTimeMins ==========================================
OnsetToArrivalTimeMins = audit_measure(
stem_name = "OnsetToArrivalMins",
description = "Onset to arrival",
exclusions = NULL,
numerators = ssnap_field[["OnsetToArrivalTimeMins"]],
new_numerators = ssnap_field[["OnsetToArrivalTimeMins"]],
csv_columns = c("S1OnsetInHospital",
"S1OnsetDateIsPrecise",
"S1OnsetTimeIsPrecise",
"S1OnsetDateTime",
"S1PatientClockStartDateTime"),
measure_type = "continuous"),
# OnsetToFirstStrokeUnitMins ======================================
OnsetToFirstStrokeUnitMins = audit_measure(
stem_name = "OnsetToFirstStrokeUnitMins",
description = "Onset to first stroke unit",
exclusions = NULL,
numerators = ssnap_field[["OnsetToFirstStrokeUnitMins"]],
new_numerators = ssnap_field[["OnsetToFirstStrokeUnitMins"]],
csv_columns = c("S1OnsetDateTime",
"S1FirstStrokeUnitArrivalDateTime"),
measure_type = "continuous"),
# OnsetToBrainImagingMins =========================================
OnsetToBrainImagingMins = audit_measure(
stem_name = "OnsetToBrainImagingMins",
description = "Onset to brain imaging",
exclusions = NULL,
numerators = ssnap_field[["OnsetToBrainImagingMins"]],
new_numerators = ssnap_field[["OnsetToBrainImagingMins"]],
csv_columns = c("S1OnsetDateTime",
"S2BrainImagingDateTime"),
measure_type = "continuous"),
# OnsetToThrombolysisMins =========================================
OnsetToThrombolysisMins = audit_measure(
stem_name = "OnsetToThrombolysisMins",
description = "Onset to thrombolysis",
exclusions = NULL,
numerators = ssnap_field[["OnsetToThrombolysisMins"]],
new_numerators = ssnap_field[["OnsetToThrombolysisMins"]],
csv_columns = c("S1OnsetDateTime",
"S2ThrombolysisDateTime"),
measure_type = "continuous"),
# * -----------------------------------------------------------------
# * Ambulance -------------------------------------------------------
# * -----------------------------------------------------------------
ArrivalByAmbulance = audit_measure(
stem_name = "ArrivalByAmbulance",
description = "Arrival by ambulance",
exclusions = rlang::expr(.data[["S1OnsetInHospital"]]),
numerators = rlang::expr(.data[["S1ArriveByAmbulance"]]),
new_numerators = rlang::expr(.data[["S1ArriveByAmbulance"]]),
csv_columns = c("S1ArriveByAmbulance",
"S1OnsetInHospital"),
measure_type = "discrete"),
# * Time and day of arrival -----------------------------------------
# * -----------------------------------------------------------------
#TODO Time and day of arrival needs first arrival breaking down to
# In hours, out of hours, weekends and bank holidays
# TODO DayTypeOfArrival needs to also include bank holidays.
# Output also should be a factor rather than character
#DayTypeOfArrival = dplyr::case_when(
# .data[["S1OnsetInHospital"]] ~ NA_character_,
# lubridate::wday(.data[["S1FirstArrivalDateTime"]]) > 5 ~
# "Weekend",
# TRUE ~ "Weekday"),
#TimeRangeOfArrival = dplyr::case_when(
# .data[["S1OnsetInHospital"]] ~ NA_character_,
# dplyr::between(lubridate::hour(.data[["S1FirstArrivalDateTime"]]),
# 8, 18) ~ "In-hours",
# TRUE ~ "Out of hours"
#),
# * Scanning --------------------------------------------------------
# * -----------------------------------------------------------------
# ClockStartToBrainImagingMins ====================================
# G6.4-6 Clock start to first brain imaging
# H6.4-6 Clock start to first brain imaging
ClockStartToBrainImagingMins = audit_measure(
stem_name = "ClockStartToBrainImagingMins",
description = "Clock start to first brain imaging (mins)",
exclusions = NULL,
numerators = ssnap_field[["ClockStartToBrainImagingMins"]],
new_numerators = ssnap_field[["ClockStartToBrainImagingMins"]],
csv_columns = c("S1PatientClockStartDateTime",
"S2BrainImagingDateTime"),
measure_type = "continuous"),
# BrainImagingGrouped =============================================
# G6.1-3 Scanned
# H6.1-3 Scanned
# G6.7-9 Scanned within 1 hour of clock start
# H6.7-9 Scanned within 1 hour of clock start
# G6.10-12 Scanned within 12 hours of clock start
# H6.10-12 Scanned within 12 hours of clock start
# G6.13-15 Scanned within 24 hours of clock start
# H6.13-15 Scanned within 24 hours of clock start
BrainImagingGrouped = audit_measure(
stem_name = "BrainImaging",
description = "Brain imaging",
exclusions = NULL,
numerators = rlang::exprs(
"Scanned" = !is.na(
!! ssnap_field[["ClockStartToBrainImagingMins"]]),
"Within1hr" = !! ssnap_field[["ClockStartToBrainImagingMins"]]
<= 60,
"Within12hrs" = !! ssnap_field[["ClockStartToBrainImagingMins"]]
<= (60 * 12),
"Within24hrs" = !! ssnap_field[["ClockStartToBrainImagingMins"]]
<= (60 * 24)),
new_numerators = tibble::tribble(
~numerator, ~fun, ~descriptor,
"Scanned", rlang::expr(
!is.na(!! ssnap_field[["ClockStartToBrainImagingMins"]])),
"Scanned",
"Within1hr", rlang::expr(
!! ssnap_field[["ClockStartToBrainImagingMins"]] <= 60),
"Scanned within 1hr",
"Within12hrs", rlang::expr(
!! ssnap_field[["ClockStartToBrainImagingMins"]] <= (60 * 12)),
"Scanned within 12hrs",
"Within24hrs", rlang::expr(
!! ssnap_field[["ClockStartToBrainImagingMins"]] <= (60 * 24)),
"Scanned within 24hrs"),
csv_columns = c("S1PatientClockStartDateTime",
"S2BrainImagingDateTime"),
measure_type = "discrete"),
# * -----------------------------------------------------------------
# * Admission to stroke unit -----------------------------------------
# * -----------------------------------------------------------------
# WentToAStrokeUnit ===============================================
# G7.1-3 Patient went to a stroke unit (SU) at any point at the
# first admitting hospital
# H7.1-3 Patient went to a stroke unit (SU) at any point at the
# first admitting hospital
WentToAStrokeUnit = audit_measure(
stem_name = "WentToAStrokeUnit",
description = "Went to a stroke unit",
exclusions = NULL,
numerators = rlang::expr(!is.na(
!! ssnap_field[["ClockStartToFirstStrokeUnitMins"]])),
new_numerators = rlang::expr(!is.na(
!! ssnap_field[["ClockStartToFirstStrokeUnitMins"]])),
csv_columns = c("S1PatientClockStartDateTime",
"S1FirstStrokeUnitArrivalDateTime"),
measure_type = "discrete"),
# ClockStartToFirstStrokeUnitMins =================================
# G7.4-6 Clock start to first stroke unit admission (mins)
# H7.4-6 Clock start to first stroke unit admission (mins)
ClockStartToFirstStrokeUnitMins = audit_measure(
stem_name = "ClockStartToFirstStrokeUnitMins",
description = "Clock start to first stroke unit (mins)",
exclusions = NULL,
numerators = ssnap_field[["ClockStartToFirstStrokeUnitMins"]],
new_numerators =
ssnap_field[["ClockStartToFirstStrokeUnitMins"]],
csv_columns = c("S1PatientClockStartDateTime",
"S1FirstStrokeUnitArrivalDateTime"),
measure_type = "continuous"),
# FirstWard =======================================================
# G7.7-15 First ward of admission
# H7.7-15 First ward of admission
FirstWard = audit_measure(
stem_name = "FirstWard",
description = "First ward",
exclusions = NULL,
numerators = rlang::exprs(
"MAU_AAU_CDU" = (.data[["S1FirstWard"]] == "MAC"),
"StrokeUnit" = (.data[["S1FirstWard"]] == "SU"),
"ICU_CCU_HDU" = (.data[["S1FirstWard"]] == "ICH"),
"Other" = (.data[["S1FirstWard"]] == "O")),
new_numerators = tibble::tribble(
~numerator, ~fun, ~descriptor,
"MAU_AAU_CDU",
rlang::expr(.data[["S1FirstWard"]] == "MAC"),
"Admitted to an assessment area",
"StrokeUnit",
rlang::expr(.data[["S1FirstWard"]] == "SU"),
"Admitted to a stroke unit",
"ICU_CCU_HDU",
rlang::expr(.data[["S1FirstWard"]] == "ICH"),
"Admitted to a high dependency area (ICU, CCU, HDU)",
"Other",
rlang::expr(.data[["S1FirstWard"]] == "O"),
"Other"),
csv_columns = "S1FirstWard",
measure_type = "discrete"),
# FirstSUWithin4hrs ===============================================
# G 7.16.1-18.1 First stroke unit within 4 hours
# H 7.16.1-18.1 First stroke unit within 4 hours
FirstSUWithin4hrs = audit_measure(
stem_name = "FirstSUWithin4hrs",
description = "First stroke unit within 4 hours",
exclusions = rlang::expr( (.data[["S1FirstWard"]] == "ICH") |
(!is.na(.data[["S2IAI"]]) & .data[["S2IAI"]])),
numerators = rlang::expr(.data[["S1FirstWard"]] == "SU" &
(!! ssnap_field[["ClockStartToFirstStrokeUnitMins"]]
<= (4 * 60))),
new_numerators =
rlang::expr(.data[["S1FirstWard"]] == "SU" &
(!! ssnap_field[["ClockStartToFirstStrokeUnitMins"]]
<= (4 * 60))),
csv_columns = c("S1PatientClockStartDateTime",
"S1FirstStrokeUnitArrivalDateTime",
"S1FirstWard",
"S2IAI"),
measure_type = "discrete"),
# TODO Out of hours and SU within 4 hrs.
# * -----------------------------------------------------------------
# * Stroke nurse assessment -----------------------------------------
# * -----------------------------------------------------------------
# StrokeNurseReview ===============================================
# G 8.1-3 Stroke nurse within 24hrs
# H 8.1-3 Stroke nurse within 24hrs
# G 8.4-6 Stroke nurse within 72hrs
# H 8.4-6 Stroke nurse within 72hrs
# G 8.7-13 Stroke nurse review times grouped by time
# H 8.7-13 Stroke nurse review times grouped by time
StrokeNurseReview = audit_measure(
stem_name = "StrokeNurseReview",
description = "Onset to stroke nurse review",
exclusions = NULL,
numerators = rlang::exprs(
"Within12hrs" = !! ssnap_field[["ClockStartToStrokeNurseMins"]]
<= (12 * 60),
"Within24hrs" = !! ssnap_field[["ClockStartToStrokeNurseMins"]]
<= (24 * 60),
"Within72hrs" = !! ssnap_field[["ClockStartToStrokeNurseMins"]]
<= (72 * 60),
"12To24hrs" = dplyr::between(
!! ssnap_field[["ClockStartToStrokeNurseMins"]],
(12 * 60), (24 * 60)),
"24To72hrs" = dplyr::between(
!! ssnap_field[["ClockStartToStrokeNurseMins"]],
(24 * 60), (72 * 60))),
new_numerators = tibble::tribble(
~numerator, ~fun, ~descriptor,
"Within12hrs", rlang::expr(
!! ssnap_field[["ClockStartToStrokeNurseMins"]] <= (12 * 60)),
"Within 12 hours",
"Within24hrs", rlang::expr(
!! ssnap_field[["ClockStartToStrokeNurseMins"]] <= (24 * 60)),
"Within 24 hours",
"Within72hrs", rlang::expr(
!! ssnap_field[["ClockStartToStrokeNurseMins"]] <= (72 * 60)),
"Within 72 hours",
"12To24hrs",
rlang::expr(dplyr::between(
!! ssnap_field[["ClockStartToStrokeNurseMins"]],
(12 * 60), (24 * 60))),
"In 12 to 24 hours",
"24To72hrs",
rlang::expr(dplyr::between(
!! ssnap_field[["ClockStartToStrokeNurseMins"]],
(24 * 60), (72 * 60))),
"In 24 to 72 hours"),
csv_columns = c("S1PatientClockStartDateTime",
"S3StrokeNurseAssessedDateTime"),
measure_type = "discrete"),
# ClockStartToStrokeNurseMins =====================================
# G 8.14-16 Clock start to stroke nurse (minutes)
# H 8.14-16 Clock start to stroke nurse (minutes)
ClockStartToStrokeNurseMins = audit_measure(
stem_name = "ClockStartToStrokeNurseMins",
description = "Clock start to stroke nurse (mins)",
exclusions = NULL,
numerators = ssnap_field[["ClockStartToStrokeNurseMins"]],
new_numerators = ssnap_field[["ClockStartToStrokeNurseMins"]],
csv_columns = c("S1PatientClockStartDateTime",
"S3StrokeNurseAssessedDateTime"),
measure_type = "continuous"),
# * -----------------------------------------------------------------
# * Stroke consultant assessment ------------------------------------
# * -----------------------------------------------------------------
# StrokeConsultantReviewGrouped ===================================
# G 9.1-3 Stroke consultant within 24hrs
# H 9.1-3 Stroke consultant within 24hrs
# G 9.4-6 Stroke consultant within 72hrs
# H 9.4-6 Stroke consultant within 72hrs
# G 9.7-13 Stroke consultant review times grouped by time
# H 9.7-13 Stroke consultant review times grouped by time
# G 9.17-19 Stroke consultant within 14hrs
# H 9.17-19 Stroke consultant within 14hrs
StrokeConsultantReview = audit_measure(
stem_name = "StrokeConsultantReview",
description = "Onset to consultant review",
exclusions = NULL,
numerators = rlang::exprs(
"Within12hrs" = !! ssnap_field[["ClockStartToConsultantMins"]]
<= (12 * 60),
"Within14hrs" = !! ssnap_field[["ClockStartToConsultantMins"]]
<= (14 * 60),
"Within24hrs" = !! ssnap_field[["ClockStartToConsultantMins"]]
<= (24 * 60),
"Within72hrs" = !! ssnap_field[["ClockStartToConsultantMins"]]
<= (72 * 60),
"12To24hrs" = dplyr::between(
!! ssnap_field[["ClockStartToConsultantMins"]],
(12 * 60), (24 * 60)),
"24To72hrs" = dplyr::between(
!! ssnap_field[["ClockStartToConsultantMins"]],
(24 * 60), (72 * 60))),
new_numerators = tibble::tribble(
~numerator, ~fun, ~descriptor,
"Within12hrs",
rlang::expr(!! ssnap_field[["ClockStartToConsultantMins"]] <= (12 * 60)),
"Within 12 hours",
"Within14hrs",
rlang::expr(!! ssnap_field[["ClockStartToConsultantMins"]] <= (14 * 60)),
"Within 14 hours",
"Within24hrs",
rlang::expr(!! ssnap_field[["ClockStartToConsultantMins"]] <= (24 * 60)),
"Within 24 hours",
"Within72hrs",
rlang::expr(!! ssnap_field[["ClockStartToConsultantMins"]] <= (72 * 60)),
"Within 72 hours",
"12To24hrs", rlang::expr(dplyr::between(
!! ssnap_field[["ClockStartToConsultantMins"]], (12 * 60), (24 * 60))),
"12 to 24 hours",
"24To72hrs", rlang::expr(dplyr::between(
!! ssnap_field[["ClockStartToConsultantMins"]], (24 * 60), (72 * 60))),
"24 to 72 hours"),
csv_columns = c("S1PatientClockStartDateTime",
"S3StrokeConsultantAssessedDateTime"),
measure_type = "discrete"),
# ClockStartToConsultantMins ======================================
# G 9.14-16 Clock start to stroke consultant (minutes)
# H 9.14-16 Clock start to stroke consultant (minutes)
ClockStartToConsultantMins = audit_measure(
stem_name = "ClockStartToConsultantMins",
description = "Clock start to consultant review (mins)",
exclusions = NULL,
numerators = ssnap_field[["ClockStartToConsultantMins"]],
new_numerators = ssnap_field[["ClockStartToConsultantMins"]],
csv_columns = c("S1PatientClockStartDateTime",
"S3StrokeConsultantAssessedDateTime"),
measure_type = "continuous"),
# * -----------------------------------------------------------------
# * Occupational therapy --------------------------------------------
# * -----------------------------------------------------------------
# OccTherReviewGrouped ============================================
# G 10.1-15 Occupational therapy assessment breakdown
# H 10.1-15 Occupational therapy assessment breakdown
OccTherReviewGrouped = audit_measure(
stem_name = "OccTherReview",
description = "Onset to occupational therapy initial assessment",
exclusions = NULL,
numerators = rlang::exprs(
"Within24hrs" = !! ssnap_field[["ClockStartToOTMins"]]
<= (24 * 60),
"24To72hrs" = dplyr::between(
!! ssnap_field[["ClockStartToOTMins"]], (24 * 60), (72 * 60)),
"NotDoneOrg" =
.data[["S3OccTherapist72HrsNotAssessedReason"]] == "OR",
"NotDoneRefused" =
.data[["S3OccTherapist72HrsNotAssessedReason"]] == "PR",
"NotDoneUnwell" =
.data[["S3OccTherapist72HrsNotAssessedReason"]] == "MU",
"NotDoneNoDeficit" =
.data[["S3OccTherapist72HrsNotAssessedReason"]] == "ND",
"NotDoneNotKnown" =
.data[["S3OccTherapist72HrsNotAssessedReason"]] == "NK"),
new_numerators = tibble::tribble(
~numerator, ~fun, ~descriptor,
"Within24hrs",
rlang::expr(!! ssnap_field[["ClockStartToOTMins"]] <= (24 * 60)),
"Within 24 hours",
"24To72hrs", rlang::expr(dplyr::between(
!! ssnap_field[["ClockStartToOTMins"]], (24 * 60), (72 * 60))),
"24 to 72 hours",
"NotDoneOrg", rlang::expr(
.data[["S3OccTherapist72HrsNotAssessedReason"]] == "OR"),
"Not done (organisational reasons)",
"NotDoneRefused", rlang::expr(
.data[["S3OccTherapist72HrsNotAssessedReason"]] == "PR"),
"Not done (patient refused)",
"NotDoneUnwell", rlang::expr(
.data[["S3OccTherapist72HrsNotAssessedReason"]] == "MU"),
"Not done (unwell)",
"NotDoneNoDeficit", rlang::expr(
.data[["S3OccTherapist72HrsNotAssessedReason"]] == "ND"),
"Not done (no deficit)",
"NotDoneNotKnown", rlang::expr(
.data[["S3OccTherapist72HrsNotAssessedReason"]] == "NK"),
"Not done (not known)"),
csv_columns = c("S1PatientClockStartDateTime",
"S3OccTherapist72HrsDateTime",
"S3OccTherapist72HrsNotAssessedReason"),
measure_type = "discrete"),
# ClockStartToOTMins ==============================================
# G 10.16-18 Clock start to occupational therapy assessment (mins)
# H 10.16-18 Clock start to occupational therapy assessment (mins)
ClockStartToOTMins = audit_measure(
stem_name = "ClockStartToOTMins",
description = "Clock start to initial OT assessment (mins)",
exclusions = NULL,
numerators = ssnap_field[["ClockStartToOTMins"]],
new_numerators = ssnap_field[["ClockStartToOTMins"]],
csv_columns = c("S1PatientClockStartDateTime",
"S3OccTherapist72HrsDateTime"),
measure_type = "continuous"),
# OccTherApplicability ============================================
# G 10.19-21 Applicability for occupational therapy
# H 10.19-21 Applicability for occupational therapy
OccTherApplicability = audit_measure(
stem_name = "OccTherApplicability",
description = "Applicability for occupational therapy",
exclusions = NULL,
numerators = rlang::expr(!(
.data[["S3OccTherapist72HrsNotAssessedReason"]]
%in% c("PR", "PU", "ND"))),
new_numerators = rlang::expr(!(
.data[["S3OccTherapist72HrsNotAssessedReason"]]
%in% c("PR", "PU", "ND"))),
csv_columns = "S3OccTherapist72HrsNotAssessedReason",
measure_type = "discrete"),
# OccTherApplicableWithin72hrs ====================================
# G 10.22-24 If applicable, OT assessment within 72 hours
# H 10.22-24 If applicable, OT assessment within 72 hours
OccTherApplicableWithin72hrs = audit_measure(
stem_name = "OccTherApplicableWithin72hrs",
description = "Applicability for occupational therapy",
exclusions = rlang::expr(
.data[["S3OccTherapist72HrsNotAssessedReason"]]
%in% c("PR", "PU", "ND")),
numerators = rlang::expr(!! ssnap_field[["ClockStartToOTMins"]]
<= (72 * 60)),
new_numerators =
rlang::expr(!! ssnap_field[["ClockStartToOTMins"]] <= (72 * 60)),
csv_columns = c("S1PatientClockStartDateTime",
"S3OccTherapist72HrsDateTime",
"S3OccTherapist72HrsNotAssessedReason"),
measure_type = "discrete"),
# OccTherApplicableWithin24hrs ====================================
# G 10.25-27 If applicable, OT assessment within 24 hours
# H 10.25-27 If applicable, OT assessment within 24 hours
OccTherApplicableWithin24hrs = audit_measure(
stem_name = "OccTherApplicableWithin24hrs",
description = "Applicability for occupational therapy",
exclusions = rlang::expr(
.data[["S3OccTherapist72HrsNotAssessedReason"]]
%in% c("PR", "PU", "ND")),
numerators = rlang::expr(!! ssnap_field[["ClockStartToOTMins"]]
<= (24 * 60)),
new_numerators =
rlang::expr(!! ssnap_field[["ClockStartToOTMins"]] <= (24 * 60)),
csv_columns = c("S1PatientClockStartDateTime",
"S3OccTherapist72HrsDateTime",
"S3OccTherapist72HrsNotAssessedReason"),
measure_type = "discrete"),
# OTAssessment72HrsComplete =======================================
# C6.4-6.6 Reason for no OT assessment within 72hrs is known
OTAssessment72HrsComplete = audit_measure(
stem_name = "OTAssessment72HrsComplete",
description = "OT assessment within 72hrs known",
exclusions = NULL,
numerators = rlang::expr(
(.data[["S3OccTherapist72HrsNotAssessedReason"]] != "NK") |
is.na(.data[["S3OccTherapist72HrsNotAssessedReason"]])),
new_numerators = rlang::expr(
(.data[["S3OccTherapist72HrsNotAssessedReason"]] != "NK") |
is.na(.data[["S3OccTherapist72HrsNotAssessedReason"]])),
csv_columns = "S3OccTherapist72HrsNotAssessedReason",
measure_type = "discrete"),
# * -----------------------------------------------------------------
# * Physiotherapy ---------------------------------------------------
# * -----------------------------------------------------------------
# PhysioReviewGrouped =============================================
# G 11.1-15 Physiotherapy assessment breakdown
# H 11.1-15 Physiotherapy assessment breakdown
PhysioReviewGrouped = audit_measure(
stem_name = "PhysioReview",
description = "Onset to physiotherapy initial assessment",
exclusions = NULL,
numerators = rlang::exprs(
"Within24hrs" = !! ssnap_field[["ClockStartToPTMins"]]
<= (24 * 60),
"24To72hrs" = dplyr::between(
!! ssnap_field[["ClockStartToPTMins"]], (24 * 60), (72 * 60)),
"NotDoneOrg" =
.data[["S3Physio72HrsNotAssessedReason"]] == "OR",
"NotDoneRefused" =
.data[["S3Physio72HrsNotAssessedReason"]] == "PR",
"NotDoneUnwell" =
.data[["S3Physio72HrsNotAssessedReason"]] == "MU",
"NotDoneNoDeficit" =
.data[["S3Physio72HrsNotAssessedReason"]] == "ND",
"NotDoneNotKnown" =
.data[["S3Physio72HrsNotAssessedReason"]] == "NK"),
new_numerators = tibble::tribble(
~numerator, ~fun, ~descriptor,
"Within24hrs", rlang::expr(
!! ssnap_field[["ClockStartToPTMins"]] <= (24 * 60)),
"Within 24 hours",
"24To72hrs", rlang::expr(dplyr::between(
!! ssnap_field[["ClockStartToPTMins"]], (24 * 60), (72 * 60))),
"24 to 72 hours",
"NotDoneOrg", rlang::expr(
.data[["S3Physio72HrsNotAssessedReason"]] == "OR"),
"Not done (organisational reasons)",
"NotDoneRefused", rlang::expr(
.data[["S3Physio72HrsNotAssessedReason"]] == "PR"),
"Not done (patient refused)",
"NotDoneUnwell", rlang::expr(
.data[["S3Physio72HrsNotAssessedReason"]] == "MU"),
"Not done (medically unwell)",
"NotDoneNoDeficit", rlang::expr(
.data[["S3Physio72HrsNotAssessedReason"]] == "ND"),
"Not done (no deficits)",
"NotDoneNotKnown", rlang::expr(
.data[["S3Physio72HrsNotAssessedReason"]] == "NK"),
"Not done (not known)"),
csv_columns = c("S1PatientClockStartDateTime",
"S3Physio72HrsDateTime",
"S3Physio72HrsNotAssessedReason"),
measure_type = "discrete"),
# ClockStartToPTMins ==============================================
# G 11.16-18 Clock start to physiotherapy assessment (mins)
# H 11.16-18 Clock start to physiotherapy assessment (mins)
ClockStartToPTMins = audit_measure(
stem_name = "ClockStartToPTMins",
description = "Clock start to initial PT assessment (mins)",
exclusions = NULL,
numerators = ssnap_field[["ClockStartToPTMins"]],
new_numerators = ssnap_field[["ClockStartToPTMins"]],
csv_columns = c("S1PatientClockStartDateTime",
"S3Physio72HrsDateTime"),
measure_type = "continuous"),
# PhysioApplicability =============================================
# G 11.19-21 Applicability for physiotherapy
# H 11.19-21 Applicability for physiotherapy
PhysioApplicability = audit_measure(
stem_name = "PhysioApplicability",
description = "Applicability for physiotherapy",
exclusions = NULL,
numerators = rlang::expr(!(
.data[["S3Physio72HrsNotAssessedReason"]]
%in% c("PR", "PU", "ND"))),
new_numerators = rlang::expr(!(
.data[["S3Physio72HrsNotAssessedReason"]]
%in% c("PR", "PU", "ND"))),
csv_columns = "S3Physio72HrsNotAssessedReason",
measure_type = "discrete"),
# PhysioApplicableWithin72hrs =====================================
# G 11.22-24 If applicable, PT assessment within 72 hours
# H 11.22-24 If applicable, PT assessment within 72 hours
PhysioApplicableWithin72hrs = audit_measure(
stem_name = "PhysioApplicableWithin72hrs",
description = "Applicability for physiotherapy",
exclusions = rlang::expr(.data[["S3Physio72HrsNotAssessedReason"]]
%in% c("PR", "PU", "ND")),
numerators = rlang::expr(!! ssnap_field[["ClockStartToPTMins"]]
<= (72 * 60)),
new_numerators = rlang::expr(!! ssnap_field[["ClockStartToPTMins"]]
<= (72 * 60)),
csv_columns = c("S1PatientClockStartDateTime",
"S3Physio72HrsDateTime",
"S3Physio72HrsNotAssessedReason"),
measure_type = "discrete"),
# PhysioApplicableWithin24hrs =====================================
# G 11.25-27 If applicable, PT assessment within 24 hours
# H 11.25-27 If applicable, PT assessment within 24 hours
PhysioApplicableWithin24hrs = audit_measure(
stem_name = "PhysioApplicableWithin24hrs",
description = "Applicability for physiotherapy",
exclusions = rlang::expr(.data[["S3Physio72HrsNotAssessedReason"]]
%in% c("PR", "PU", "ND")),
numerators = rlang::expr(!! ssnap_field[["ClockStartToPTMins"]]
<= (24 * 60)),
new_numerators = rlang::expr(!! ssnap_field[["ClockStartToPTMins"]]
<= (24 * 60)),
csv_columns = c("S1PatientClockStartDateTime",
"S3Physio72HrsDateTime",
"S3Physio72HrsNotAssessedReason"),
measure_type = "discrete"),
# PTAssessment72HrsComplete =======================================
# C6.13-15 Reason for no PT assessment within 72hrs is known
PTAssessment72HrsComplete = audit_measure(
stem_name = "PTAssessment72HrsComplete",
description = "PT assessment within 72hrs known",
exclusions = NULL,
numerators = rlang::expr(
(.data[["S3Physio72HrsNotAssessedReason"]] != "NK") |
is.na(.data[["S3Physio72HrsNotAssessedReason"]])),
new_numerators = rlang::expr(
(.data[["S3Physio72HrsNotAssessedReason"]] != "NK") |
is.na(.data[["S3Physio72HrsNotAssessedReason"]])),
csv_columns = "S3Physio72HrsNotAssessedReason",
measure_type = "discrete"),
# * -----------------------------------------------------------------
# * Speech and language therapy (communication) ---------------------
# * -----------------------------------------------------------------
# SLTCommReviewGrouped ==============================================
# G 12.1-15 Speech and language communication assessment breakdown
# H 12.1-15 Speech and language communication assessment breakdown
SLTCommReviewGrouped = audit_measure(
stem_name = "SLTCommReview",
description = "Onset to SLT communication initial assessment",
exclusions = NULL,
numerators = rlang::exprs(
"Within24hrs" = !! ssnap_field[["ClockStartToSLTCommMins"]]
<= (24 * 60),
"24To72hrs" = dplyr::between(
!! ssnap_field[["ClockStartToSLTCommMins"]],
(24 * 60), (72 * 60)),
"NotDoneOrg" =
.data[["S3SpLangTherapistComm72HrsNotAssessedReason"]] == "OR",
"NotDoneRefused" =
.data[["S3SpLangTherapistComm72HrsNotAssessedReason"]] == "PR",
"NotDoneUnwell" =
.data[["S3SpLangTherapistComm72HrsNotAssessedReason"]] == "MU",
"NotDoneNoDeficit" =
.data[["S3SpLangTherapistComm72HrsNotAssessedReason"]] == "ND",
"NotDoneNotKnown" =
.data[["S3SpLangTherapistComm72HrsNotAssessedReason"]] == "NK"),
new_numerators = tibble::tribble(
~numerator, ~fun, ~descriptor,
"Within24hrs", rlang::expr(
!! ssnap_field[["ClockStartToSLTCommMins"]] <= (24 * 60)),
"Within 24 hours",
"24To72hrs", rlang::expr(dplyr::between(
!! ssnap_field[["ClockStartToSLTCommMins"]],
(24 * 60), (72 * 60))),
"24 to 72 hours",
"NotDoneOrg", rlang::expr(
.data[["S3SpLangTherapistComm72HrsNotAssessedReason"]] == "OR"),
"Not done (organisational reasons)",
"NotDoneRefused", rlang::expr(
.data[["S3SpLangTherapistComm72HrsNotAssessedReason"]] == "PR"),
"Not done (patient refused)",
"NotDoneUnwell", rlang::expr(
.data[["S3SpLangTherapistComm72HrsNotAssessedReason"]] == "MU"),
"Not done (patient unwell)",
"NotDoneNoDeficit", rlang::expr(
.data[["S3SpLangTherapistComm72HrsNotAssessedReason"]] == "ND"),
"Not done (no deficit)",
"NotDoneNotKnown", rlang::expr(
.data[["S3SpLangTherapistComm72HrsNotAssessedReason"]] == "NK"),
"Not done (not known)"),
csv_columns = c("S1PatientClockStartDateTime",
"S3SpLangTherapistComm72HrsDateTime",
"S3SpLangTherapistComm72HrsNotAssessedReason"),
measure_type = "discrete"),
# ClockStartToSLTCommMins =========================================
# G 12.16-18 Clock start to SLT communication assessment (mins)
# H 12.16-18 Clock start to SLT communication assessment (mins)
ClockStartToSLTCommMins = audit_measure(
stem_name = "ClockStartToSLTCommMins",
description =
"Clock start to initial SLT communication assessment (mins)",
exclusions = NULL,
numerators = ssnap_field[["ClockStartToSLTCommMins"]],
new_numerators = ssnap_field[["ClockStartToSLTCommMins"]],
csv_columns = c("S1PatientClockStartDateTime",
"S3SpLangTherapistComm72HrsDateTime"),
measure_type = "continuous"),
# SLTCommApplicability ============================================
# G 12.19-21 Applicability for SLT communication therapy
# H 12.19-21 Applicability for SLT communication therapy
SLTCommApplicability = audit_measure(
stem_name = "SLTCommApplicability",
description = "Applicability for SLT communication therapy",
exclusions = NULL,
numerators = rlang::expr(!(
.data[["S3SpLangTherapistComm72HrsNotAssessedReason"]]
%in% c("PR", "PU", "ND"))),
new_numerators = rlang::expr(!(
.data[["S3SpLangTherapistComm72HrsNotAssessedReason"]]
%in% c("PR", "PU", "ND"))),
csv_columns = "S3SpLangTherapistComm72HrsNotAssessedReason",
measure_type = "discrete"),
# SLTCommApplicableWithin72hrs ====================================
# G 12.22-24 If applicable, SLT Comm assessment within 72 hours
# H 12.22-24 If applicable, SLT Comm assessment within 72 hours
SLTCommApplicableWithin72hrs = audit_measure(
stem_name = "SLTCommApplicableWithin72hrs",
description = "Applicability for SLT communication therapy",
exclusions = rlang::expr(
.data[["S3SpLangTherapistComm72HrsNotAssessedReason"]]
%in% c("PR", "PU", "ND")),
numerators = rlang::expr(!! ssnap_field[["ClockStartToSLTCommMins"]]
<= (72 * 60)),
new_numerators = rlang::expr(!! ssnap_field[["ClockStartToSLTCommMins"]]
<= (72 * 60)),
csv_columns = c("S1PatientClockStartDateTime",
"S3SpLangTherapistComm72HrsDateTime",
"S3SpLangTherapistComm72HrsNotAssessedReason"),
measure_type = "discrete"),
# SLTCommApplicableWithin24hrs ====================================
# G 12.25-27 If applicable, SLT Comm assessment within 24 hours
# H 12.25-27 If applicable, SLT Comm assessment within 24 hours
SLTCommApplicableWithin24hrs = audit_measure(
stem_name = "SLTCommApplicableWithin24hrs",
description = "Applicability for SLT communication therapy",
exclusions = rlang::expr(
.data[["S3SpLangTherapistComm72HrsNotAssessedReason"]]
%in% c("PR", "PU", "ND")),
numerators = rlang::expr(ssnap_field[["ClockStartToSLTCommMins"]]
<= (24 * 60)),
new_numerators = rlang::expr(ssnap_field[["ClockStartToSLTCommMins"]]
<= (24 * 60)),
csv_columns = "S3SpLangTherapistComm72HrsNotAssessedReason",
measure_type = "discrete"),
# SLTCommAssessment72HrsComplete ==================================
# C6.16-18 Reason for no SLT Comm assessment within 72hrs is known
SLTCommAssessment72HrsComplete = audit_measure(
stem_name = "SLTCommAssessment72HrsComplete",
description = "SLT Comm assessment within 72hrs known",
exclusions = NULL,
numerators = rlang::expr(
(.data[["S3SpLangTherapistComm72HrsNotAssessedReason"]]
!= "NK") | is.na(
.data[["S3SpLangTherapistComm72HrsNotAssessedReason"]])),
new_numerators = rlang::expr(
(.data[["S3SpLangTherapistComm72HrsNotAssessedReason"]]
!= "NK") | is.na(
.data[["S3SpLangTherapistComm72HrsNotAssessedReason"]])),
csv_columns = "S3SpLangTherapistComm72HrsNotAssessedReason",
measure_type = "discrete"),
# * -----------------------------------------------------------------
# * First 72hrs Bundle ----------------------------------------------
# * -----------------------------------------------------------------
# G 13.1-3 Seen by nurse in 24hrs, one therapist in 24hrs and all
# therapists in 72hrs.
# H 13.1-3 Seen by nurse in 24hrs, one therapist in 24hrs and all
# therapists in 72hrs.
# TODO This needs to be implemented
# * Swallow Screening -----------------------------------------------
# * -----------------------------------------------------------------
# SwallowScreen4hrsGrouped ========================================
# G 14.1-11 Swallow screening within 4 hours breakdown
# H 14.1-11 Swallow screening within 4 hours breakdown
SwallowScreen4hrsGrouped = audit_measure(
stem_name = "SwallowScreen4hrs",
description = "Swallow screen within 4hrs",
exclusions = NULL,
numerators = rlang::exprs(
"Within4hrs" =
!! ssnap_field[["ClockStartToSwallowScreen4hrsMins"]]
<= (4 * 60),
"NotDoneOrg" =
.data[["S2SwallowScreening4HrsNotPerformedReason"]] == "OR",
"NotDoneRefused" =
.data[["S2SwallowScreening4HrsNotPerformedReason"]] == "PR",
"NotDoneUnwell" =
.data[["S2SwallowScreening4HrsNotPerformedReason"]] == "MU",
"NotDoneNotKnown" =
.data[["S2SwallowScreening4HrsNotPerformedReason"]] == "NK"),
new_numerators = tibble::tribble(
~numerator, ~fun, ~descriptor,
"Within4hrs",
!! ssnap_field[["ClockStartToSwallowScreen4hrsMins"]] <= (4 * 60),
"Within 4 hours",
"NotDoneOrg",
.data[["S2SwallowScreening4HrsNotPerformedReason"]] == "OR",
"Not done (organisational reasons)",
"NotDoneRefused",
.data[["S2SwallowScreening4HrsNotPerformedReason"]] == "PR",
"Not done (refused)",
"NotDoneUnwell",
.data[["S2SwallowScreening4HrsNotPerformedReason"]] == "MU",
"Not done (unwell)",
"NotDoneNotKnown",
.data[["S2SwallowScreening4HrsNotPerformedReason"]] == "NK",
"Not done (not known)"),
csv_columns = c("S1PatientClockStartDateTime",
"S2SwallowScreening4HrsDateTime",
"S2SwallowScreening4HrsNotPerformedReason"),
measure_type = "discrete"),
# ClockStartToSwallowScreen4hrsMins ===============================
# G 14.12-14 Clock start to swallow screening if done within 4hrs
# H 14.12-14 Clock start to swallow screening if done within 4hrs
ClockStartToSwallowScreen4hrsMins = audit_measure(
stem_name = "ClockStartToSwallowScreen4hrsMins",
description =
"Clock start to swallow screening if done within 4hrs (mins)",
exclusions = NULL,
numerators = ssnap_field[["ClockStartToSwallowScreen4hrsMins"]],
new_numerators = ssnap_field[["ClockStartToSwallowScreen4hrsMins"]],
csv_columns = c("S1PatientClockStartDateTime",
"S2SwallowScreening4HrsDateTime"),
measure_type = "continuous"),
# SwallowScreen4hrsApplicability ==================================
# G 14.15-17 Applicability for swallow screening within 4hrs
# H 14.15-17 Applicability for swallow screening within 4hrs
SwallowScreen4hrsApplicability = audit_measure(
stem_name = "SwallowScreen4hrsApplicability",
description = "Applicability for swallow screening within 4hrs",
exclusions = NULL,
numerators = rlang::expr(!(
.data[["S2SwallowScreening4HrsNotPerformedReason"]] %in%
c("PR", "PU"))),
new_numerators = rlang::expr(!(
.data[["S2SwallowScreening4HrsNotPerformedReason"]] %in%
c("PR", "PU"))),
csv_columns = "S2SwallowScreening4HrsNotPerformedReason",
measure_type = "discrete"),
# SwallowScreenWithin4hrs =========================================
# G 14.18-20 Swallow screen done if applicable within 4hrs
# H 14.18-20 Swallow screen done if applicable within 4hrs
SwallowScreenWithin4hrs = audit_measure(
stem_name = "SwallowScreenWithin4hrs",
description = "Swallow screen within 4 hours",
exclusions = rlang::expr(
.data[["S2SwallowScreening4HrsNotPerformedReason"]] %in%
c("PR", "PU")),
numerators = rlang::expr(
!! ssnap_field[["ClockStartToSwallowScreen4hrsMins"]] <= (4 * 60)),
new_numerators = rlang::expr(
!! ssnap_field[["ClockStartToSwallowScreen4hrsMins"]] <= (4 * 60)),
csv_columns = c("S1PatientClockStartDateTime",
"S2SwallowScreening4HrsDateTime",
"S2SwallowScreening4HrsNotPerformedReason"),
measure_type = "discrete"),
# SwallowScreen4hrsComplete =======================================
# C6.4-6 Reason for no swallow screening within 4hrs is known
SwallowScreen4hrsComplete = audit_measure(
stem_name = "SwallowScreen4hrsComplete",
description = "Swallow screening at 4 hrs known",
exclusions = NULL,
numerators = rlang::expr(
(.data[["S2SwallowScreening4HrsNotPerformedReason"]] != "NK") |
is.na(.data[["S2SwallowScreening4HrsNotPerformedReason"]])),
new_numerators = rlang::expr(
(.data[["S2SwallowScreening4HrsNotPerformedReason"]] != "NK") |
is.na(.data[["S2SwallowScreening4HrsNotPerformedReason"]])),
csv_columns = "S2SwallowScreening4HrsNotPerformedReason",
measure_type = "discrete"),
# ClockStartToSwallowScreen72hrsMins ==============================
# G 14.21-23 Clock start to swallow screening if done within 72hrs
# H 14.21-23 Clock start to swallow screening if done within 72hrs
ClockStartToSwallowScreen72hrsMins = audit_measure(
stem_name = "ClockStartToSwallowScreen72hrsMins",
description =
"Clock start to swallow screening if done within 72hrs (mins)",
exclusions = NULL,
numerators = ssnap_field[["ClockStartToSwallowScreen72hrsMins"]],
new_numerators = ssnap_field[["ClockStartToSwallowScreen72hrsMins"]],
csv_columns = c("S2SwallowScreening4HrsDateTime",
"S1PatientClockStartDateTime",
"S3SwallowScreening72HrsDateTime"),
measure_type = "continuous"),
# SwallowScreen72hrsGrouped ========================================
# G 14.24-40 Swallow screening within 72 hours breakdown
# H 14.24-40 Swallow screening within 72 hours breakdown
SwallowScreen72hrsGrouped = audit_measure(
stem_name = "SwallowScreen72hrs",
description = "Swallow screen within 72hrs",
exclusions = NULL,
numerators = rlang::exprs(
"Within4hrs" =
!! ssnap_field[["ClockStartToSwallowScreen72hrsMins"]]
<= (4 * 60),
"4To12hrs" = dplyr::between(
!! ssnap_field[["ClockStartToSwallowScreen72hrsMins"]],
(4 * 60), (12 * 60)),
"12To24hrs" = dplyr::between(
!! ssnap_field[["ClockStartToSwallowScreen72hrsMins"]],
(12 * 60), (24 * 60)),
"24To72hrs" = dplyr::between(
!! ssnap_field[["ClockStartToSwallowScreen72hrsMins"]],
(24 * 60), (72 * 60)),
"NotDoneOrg" =
.data[["S3SwallowScreening72HrsNotPerformedReason"]] == "OR",
"NotDoneRefused" =
.data[["S3SwallowScreening72HrsNotPerformedReason"]] == "PR",
"NotDoneUnwell" =
.data[["S3SwallowScreening72HrsNotPerformedReason"]] == "MU",
"NotDoneNotKnown" =
.data[["S3SwallowScreening72HrsNotPerformedReason"]] == "NK"),
new_numerators = tibble::tribble(
~numerator, ~fun, ~descriptor,
"Within4hrs", rlang::expr(
!! ssnap_field[["ClockStartToSwallowScreen72hrsMins"]] <= (4 * 60)),
"Within 4 hours",
"4To12hrs", rlang::expr(dplyr::between(
!! ssnap_field[["ClockStartToSwallowScreen72hrsMins"]],
(4 * 60), (12 * 60))),
"4 to 12 hours",
"12To24hrs", rlang::expr(dplyr::between(
!! ssnap_field[["ClockStartToSwallowScreen72hrsMins"]],
(12 * 60), (24 * 60))),
"12 to 24 hours",
"24To72hrs", rlang::expr(dplyr::between(
!! ssnap_field[["ClockStartToSwallowScreen72hrsMins"]],
(24 * 60), (72 * 60))),
"24 to 72 hours",
"NotDoneOrg", rlang::expr(
.data[["S3SwallowScreening72HrsNotPerformedReason"]] == "OR"),
"Not done (organisational reasons)",
"NotDoneRefused", rlang::expr(
.data[["S3SwallowScreening72HrsNotPerformedReason"]] == "PR"),
"Not done (refused)",
"NotDoneUnwell", rlang::expr(
.data[["S3SwallowScreening72HrsNotPerformedReason"]] == "MU"),
"Not done (medically unwell)",
"NotDoneNotKnown", rlang::expr(
.data[["S3SwallowScreening72HrsNotPerformedReason"]] == "NK"),
"Not done (not known)"),
csv_columns = c("S2SwallowScreening4HrsDateTime",
"S1PatientClockStartDateTime",
"S3SwallowScreening72HrsDateTime",
"S3SwallowScreening72HrsNotPerformedReason"),
measure_type = "discrete"),
# SwallowScreen72hrsApplicability =================================
# G 14.41-43 Applicability for swallow screening within 72hrs
# H 14.41-43 Applicability for swallow screening within 72hrs
SwallowScreen72hrsApplicability = audit_measure(
stem_name = "SwallowScreen72hrsApplicability",
description = "Applicability for swallow screening within 72hrs",
exclusions = NULL,
numerators = rlang::expr(!(
.data[["S3SwallowScreening72HrsNotPerformedReason"]] %in%
c("PR", "PU"))),
new_numerators = rlang::expr(!(
.data[["S3SwallowScreening72HrsNotPerformedReason"]] %in%
c("PR", "PU"))),
csv_columns = "S3SwallowScreening72HrsNotPerformedReason",
measure_type = "discrete"),
# SwallowScreenWithin72hrs ========================================
# G 14.44-46 Swallow screen done if applicable within 72hrs
# H 14.44-46 Swallow screen done if applicable within 72hrs
SwallowScreenWithin72hrs = audit_measure(
stem_name = "SwallowScreenWithin72hrs",
description = "Swallow screen within 72 hours",
exclusions = rlang::expr(
.data[["S3SwallowScreening72HrsNotPerformedReason"]] %in%
c("PR", "PU")),
numerators = rlang::expr(
!! ssnap_field[["ClockStartToSwallowScreen72hrsMins"]]
<= (72 * 60)),
new_numerators = rlang::expr(
!! ssnap_field[["ClockStartToSwallowScreen72hrsMins"]]
<= (72 * 60)),
csv_columns = c("S2SwallowScreening4HrsDateTime",
"S1PatientClockStartDateTime",
"S3SwallowScreening72HrsDateTime",
"S3SwallowScreening72HrsNotPerformedReason"),
measure_type = "discrete"),
# SwallowScreen72hrsComplete ======================================
# C6/7-9 Swallow screening at 72hrs is known.
SwallowScreen72hrsComplete = audit_measure(
stem_name = "SwallowScreen72hrsComplete",
description = "Swallow screening at 72hrs known",
exclusions = NULL,
numerators = rlang::expr(
(.data[["S3SwallowScreening72HrsNotPerformedReason"]] != "NK") |
is.na(.data[["S3SwallowScreening72HrsNotPerformedReason"]])),
new_numerators = rlang::expr(
(.data[["S3SwallowScreening72HrsNotPerformedReason"]] != "NK") |
is.na(.data[["S3SwallowScreening72HrsNotPerformedReason"]])),
csv_columns = "S3SwallowScreening72HrsNotPerformedReason",
measure_type = "discrete"),
# * -----------------------------------------------------------------
# * Formal swallow assessment ---------------------------------------
# * -----------------------------------------------------------------
# ClockStartToSpLangTherapistSwallowMins ==========================
# G 15.1-3 Clock start to formal swallow assessment
# H 15.1-3 Clock start to formal swallow assessment
ClockStartToSpLangTherapistSwallowMins = audit_measure(
stem_name = "ClockStartToSpLangTherapistSwallowMins",
description =
"Clock start to formal swallow assessment (mins)",
exclusions = NULL,
numerators =
ssnap_field[["ClockStartToSpLangTherapistSwallowMins"]],
new_numerators =
ssnap_field[["ClockStartToSpLangTherapistSwallowMins"]],
csv_columns = c("S1PatientClockStartDateTime",
"S3SpLangTherapistSwallow72HrsDateTime"),
measure_type = "continuous"),
# SpLangTherapistSwallow72hrsGrouped ==============================
# G 15.4-18 SLT Swallow assessment breakdown
# H 15.4-18 SLT Swallow assessment breakdown
SpLangTherapistSwallow72hrsGrouped = audit_measure(
stem_name = "SpLangTherapistSwallow72hrs",
description = "Speech and language swallow within 72hrs",
exclusions = NULL,
numerators = rlang::exprs(
"Within12hrs" =
!! ssnap_field[["ClockStartToSpLangTherapistSwallowMins"]]
<= (12 * 60),
"12To24hrs" = dplyr::between(
!! ssnap_field[["ClockStartToSpLangTherapistSwallowMins"]],
(12 * 60), (24 * 60)),
"24To72hrs" = dplyr::between(
!! ssnap_field[["ClockStartToSpLangTherapistSwallowMins"]],
(24 * 60), (72 * 60)),
"NotDoneOrg" =
.data[["S3SpLangTherapistSwallow72HrsNotAssessedReason"]]
== "OR",
"NotDoneRefused" =
.data[["S3SpLangTherapistSwallow72HrsNotAssessedReason"]]
== "PR",
"NotDoneUnwell" =
.data[["S3SpLangTherapistSwallow72HrsNotAssessedReason"]]
== "PU",
"NotDonePassedSwallow" =
.data[["S3SpLangTherapistSwallow72HrsNotAssessedReason"]]
== "PS",
"NotDoneNotKnown" =
.data[["S3SpLangTherapistSwallow72HrsNotAssessedReason"]]
== "NK"),
new_numerators = tibble::tribble(
~numerator, ~fun, ~descriptor,
"Within12hrs", rlang::expr(
!! ssnap_field[["ClockStartToSpLangTherapistSwallowMins"]] <= (12 * 60)),
"Within 12 hours",
"12To24hrs", rlang::expr(dplyr::between(
!! ssnap_field[["ClockStartToSpLangTherapistSwallowMins"]],
(12 * 60), (24 * 60))),
"12 to 24 hours",
"24To72hrs", rlang::expr(dplyr::between(
!! ssnap_field[["ClockStartToSpLangTherapistSwallowMins"]],
(24 * 60), (72 * 60))),
"24 to 72 hours",
"NotDoneOrg", rlang::expr(
.data[["S3SpLangTherapistSwallow72HrsNotAssessedReason"]] == "OR"),
"Not done (organisational reasons)",
"NotDoneRefused", rlang::expr(
.data[["S3SpLangTherapistSwallow72HrsNotAssessedReason"]] == "PR"),
"Not done (refused)",
"NotDoneUnwell", rlang::expr(
.data[["S3SpLangTherapistSwallow72HrsNotAssessedReason"]] == "PU"),
"Not done (medically unwell)",
"NotDonePassedSwallow", rlang::expr(
.data[["S3SpLangTherapistSwallow72HrsNotAssessedReason"]] == "PS"),
"Not done (passed swallow)",
"NotDoneNotKnown", rlang::expr(
.data[["S3SpLangTherapistSwallow72HrsNotAssessedReason"]] == "NK"),
"Not done (not known)"),
csv_columns = c("S1PatientClockStartDateTime",
"S3SpLangTherapistSwallow72HrsDateTime",
"S3SpLangTherapistSwallow72HrsNotAssessedReason"),
measure_type = "discrete"),
# SpLangTherapistSwallowApplicability =============================
# G 15.19-22 Applicability for swallow assessment
# H 15.19-22 Applicability for swallow assessment
SpLangTherapistSwallowApplicability = audit_measure(
stem_name = "SpLangTherapistSwallowApplicability",
description = "Applicability for swallow assessment",
exclusions = NULL,
numerators = rlang::expr(!(
.data[["S3SpLangTherapistSwallow72HrsNotAssessedReason"]] %in%
c("PR", "PU", "PS"))),
new_numerators = rlang::expr(!(
.data[["S3SpLangTherapistSwallow72HrsNotAssessedReason"]] %in%
c("PR", "PU", "PS"))),
csv_columns = "S3SpLangTherapistSwallow72HrsNotAssessedReason",
measure_type = "discrete"),
# SpLangTherapistSwallowWithin72hrs ===============================
# G 15.23-25 Swallow assessment done if applicable within 72hrs
# H 14.23-25 Swallow assessment done if applicable within 72hrs
SpLangTherapistSwallowWithin72hrs = audit_measure(
stem_name = "SpLangTherapistSwallowWithin72hrs",
description = "Swallow assessment if applicable within 72 hours",
exclusions = rlang::expr(
.data[["S3SpLangTherapistSwallow72HrsNotAssessedReason"]] %in%
c("PR", "PU", "PS")),
numerators = rlang::expr(
!! ssnap_field[["ClockStartToSpLangTherapistSwallowMins"]]
<= (72 * 60)),
new_numerators = rlang::expr(
!! ssnap_field[["ClockStartToSpLangTherapistSwallowMins"]]
<= (72 * 60)),
csv_columns = c("S1PatientClockStartDateTime",
"S3SpLangTherapistSwallow72HrsDateTime",
"S3SpLangTherapistSwallow72HrsNotAssessedReason"),
measure_type = "discrete"),
# SwallowAssessment72hrsComplete ==================================
# C 6.19.-21 Reason for formal swallow assessment known
SwallowAssessment72hrsComplete = audit_measure(
stem_name = "SwallowAssessment72hrsComplete",
description = "Swallow assessment within 72hrs known",
exclusions = NULL,
numerators = rlang::expr(
(.data[["S3SpLangTherapistSwallow72HrsNotAssessedReason"]] !=
"NK") | is.na(
.data[["S3SpLangTherapistSwallow72HrsNotAssessedReason"]])
),
new_numerators = rlang::expr(
(.data[["S3SpLangTherapistSwallow72HrsNotAssessedReason"]] !=
"NK") | is.na(
.data[["S3SpLangTherapistSwallow72HrsNotAssessedReason"]])),
csv_columns = "S3SpLangTherapistSwallow72HrsNotAssessedReason",
measure_type = "discrete"),
# * -----------------------------------------------------------------
# * Thrombolysis ----------------------------------------------------
# * -----------------------------------------------------------------
# Thrombolysis ====================================================
# G 16.1-41 Was thrombolysis given
# H 16.1-41 Was thrombolysis given
# G 16.66-68 Thrombolysed?
# H 16.66-68 Thrombolysed?
Thrombolysis = audit_measure(
stem_name = "Thrombolysis",
description = "Thrombolysis",
exclusions = NULL,
numerators = rlang::exprs(
"Yes" = .data[["S2Thrombolysis"]] == "Y",
"No" = .data[["S2Thrombolysis"]] == "N",
"NoUnavailable" = (.data[["S2Thrombolysis"]] == "N") &
(.data[["S2ThrombolysisNoReason"]] == "TNA"),
"NoUnableToScanInTime" = (.data[["S2Thrombolysis"]] == "N") &
(.data[["S2ThrombolysisNoReason"]] == "USQE"),
"NoOutsideServiceHours" = (.data[["S2Thrombolysis"]] == "N") &
(.data[["S2ThrombolysisNoReason"]] == "OTSH"),
"NoReasonUnknown" = (.data[["S2Thrombolysis"]] == "N") &
(.data[["S2ThrombolysisNoReason"]] == "N"),
"NoBut" = .data[["S2Thrombolysis"]] == "NB",
"NoButHaemorrhagic" = (.data[["S2Thrombolysis"]] == "NB") &
bitwAnd(.data[["S2ThrombolysisNoBut"]],
ssnapinterface::tpa_no_but["Haemorrhagic"]),
"NoButImproving" = (.data[["S2Thrombolysis"]] == "NB") &
bitwAnd(.data[["S2ThrombolysisNoBut"]],
ssnapinterface::tpa_no_but["Improving"]),
"NoButComorbidity" = (.data[["S2Thrombolysis"]] == "NB") &
bitwAnd(.data[["S2ThrombolysisNoBut"]],
ssnapinterface::tpa_no_but["Comorbidity"]),
"NoButMedication" = (.data[["S2Thrombolysis"]] == "NB") &
bitwAnd(.data[["S2ThrombolysisNoBut"]],
ssnapinterface::tpa_no_but["Medication"]),
"NoButRefusal" = (.data[["S2Thrombolysis"]] == "NB") &
bitwAnd(.data[["S2ThrombolysisNoBut"]],
ssnapinterface::tpa_no_but["Refusal"]),
"NoButOtherMedical" = (.data[["S2Thrombolysis"]] == "NB") &
bitwAnd(.data[["S2ThrombolysisNoBut"]],
ssnapinterface::tpa_no_but["OtherMedical"]),
"NoButAge" = (.data[["S2Thrombolysis"]] == "NB") &
bitwAnd(.data[["S2ThrombolysisNoBut"]],
ssnapinterface::tpa_no_but["Age"]),
"NoButTooMildSevere" = (.data[["S2Thrombolysis"]] == "NB") &
bitwAnd(.data[["S2ThrombolysisNoBut"]],
ssnapinterface::tpa_no_but["TooMildSevere"]),
"NoButTimeUnknownWakeUp" = (.data[["S2Thrombolysis"]] == "NB") &
bitwAnd(.data[["S2ThrombolysisNoBut"]],
ssnapinterface::tpa_no_but["TimeUnknownWakeUp"]),
"NoButTimeWindow" = (.data[["S2Thrombolysis"]] == "NB") &
bitwAnd(.data[["S2ThrombolysisNoBut"]],
ssnapinterface::tpa_no_but["TimeWindow"])),
new_numerators = tibble::tribble(
~numerator, ~fun, ~descriptor,
"Yes",
rlang::expr(.data[["S2Thrombolysis"]] == "Y"),
"Yes",
"No",
rlang::expr(.data[["S2Thrombolysis"]] == "N"),
"No",
"NoUnavailable", rlang::expr((.data[["S2Thrombolysis"]] == "N") &
(.data[["S2ThrombolysisNoReason"]] == "TNA")),
"No (unavailable)",
"NoUnableToScanInTime", rlang::expr((.data[["S2Thrombolysis"]] == "N") &
(.data[["S2ThrombolysisNoReason"]] == "USQE")),
"No (unable to scan in time)",
"NoOutsideServiceHours", rlang::expr((.data[["S2Thrombolysis"]] == "N") &
(.data[["S2ThrombolysisNoReason"]] == "OTSH")),
"No (outside service hours)",
"NoReasonUnknown", rlang::expr((.data[["S2Thrombolysis"]] == "N") &
(.data[["S2ThrombolysisNoReason"]] == "N")),
"No (reason unknown)",
"NoBut",
rlang::expr( .data[["S2Thrombolysis"]] == "NB"),
"No but",
"NoButHaemorrhagic", rlang::expr((.data[["S2Thrombolysis"]] == "NB") &
bitwAnd(.data[["S2ThrombolysisNoBut"]],
ssnapinterface::tpa_no_but["Haemorrhagic"])),
"No but (haemorrhagic stroke)",
"NoButImproving", rlang::expr((.data[["S2Thrombolysis"]] == "NB") &
bitwAnd(.data[["S2ThrombolysisNoBut"]],
ssnapinterface::tpa_no_but["Improving"])),
"No but (improving)",
"NoButComorbidity", rlang::expr((.data[["S2Thrombolysis"]] == "NB") &
bitwAnd(.data[["S2ThrombolysisNoBut"]],
ssnapinterface::tpa_no_but["Comorbidity"])),
"No but (comorbidity)",
"NoButMedication", rlang::expr((.data[["S2Thrombolysis"]] == "NB") &
bitwAnd(.data[["S2ThrombolysisNoBut"]],
ssnapinterface::tpa_no_but["Medication"])),
"No but (medication)",
"NoButRefusal", rlang::expr((.data[["S2Thrombolysis"]] == "NB") &
bitwAnd(.data[["S2ThrombolysisNoBut"]],
ssnapinterface::tpa_no_but["Refusal"])),
"No but (refusal)",
"NoButOtherMedical", rlang::expr((.data[["S2Thrombolysis"]] == "NB") &
bitwAnd(.data[["S2ThrombolysisNoBut"]],
ssnapinterface::tpa_no_but["OtherMedical"])),
"No but (other medical)",
"NoButAge", rlang::expr((.data[["S2Thrombolysis"]] == "NB") &
bitwAnd(.data[["S2ThrombolysisNoBut"]],
ssnapinterface::tpa_no_but["Age"])),
"No but (age)",
"NoButTooMildSevere", rlang::expr((.data[["S2Thrombolysis"]] == "NB") &
bitwAnd(.data[["S2ThrombolysisNoBut"]],
ssnapinterface::tpa_no_but["TooMildSevere"])),
"No but (too mild)",
"NoButTimeUnknownWakeUp", rlang::expr((.data[["S2Thrombolysis"]] == "NB") &
bitwAnd(.data[["S2ThrombolysisNoBut"]],
ssnapinterface::tpa_no_but["TimeUnknownWakeUp"])),
"No but (unknown onset time or wake-up stroke)",
"NoButTimeWindow", rlang::expr((.data[["S2Thrombolysis"]] == "NB") &
bitwAnd(.data[["S2ThrombolysisNoBut"]],
ssnapinterface::tpa_no_but["TimeWindow"])),
"No but (outside time window)"),
csv_columns = c("S2Thrombolysis",
"S2ThrombolysisNoReason",
"S2ThrombolysisNoBut"),
measure_type = "discrete"),
# ClockStartToThrombolysisMins ====================================
# G 16.1-42-4 Clock start to thrombolysis (mins)
# H 16.1-42-4 Clock start to thrombolysis (mins)
ClockStartToThrombolysisMins = audit_measure(
stem_name = "ClockStartToThrombolysisMins",
description = "Clock start to thrombolysis (mins)",
exclusions = NULL,
numerators = ssnap_field[["ClockStartToThrombolysisMins"]],
new_numerators = ssnap_field[["ClockStartToThrombolysisMins"]],
csv_columns = c("S1PatientClockStartDateTime",
"S2ThrombolysisDateTime"),
measure_type = "continuous"),
# ThrombolysedOnsetToClockStartMins ===============================
# G 16.45 If thrombolysed, time from onset to clock start (mins)
# H 16.45 If thrombolysed, time from onset to clock start (mins)
ThrombolysedOnsetToClockStartMins = audit_measure(
stem_name = "ThrombolysedOnsetToClockStartMins",
description = "If thrombolysed, onset to clock start (mins)",
exclusions = rlang::expr(.data[["S2Thrombolysis"]] != "Y"),
numerators = ssnap_field[["OnsetToArrivalTimeMins"]],
new_numerators = ssnap_field[["OnsetToArrivalTimeMins"]],
csv_columns = c("S1OnsetInHospital",
"S1OnsetDateIsPrecise",
"S1OnsetTimeIsPrecise",
"S1OnsetDateTime",
"S1PatientClockStartDateTime",
"S2Thrombolysis"),
measure_type = "continuous"),
# ThrombolysedClockStartToBrainImagingMins ========================
# G 16.46 If thrombolysed, clock start to brain imaging (mins)
# H 16.46 If thrombolysed, clock start to brain imaging (mins)
ThrombolysedClockStartToBrainImagingMins = audit_measure(
stem_name = "ThrombolysedClockStartToBrainImagingMins",
description = "If thrombolysed, clock start to scan (mins)",
exclusions = rlang::expr(.data[["S2Thrombolysis"]] != "Y"),
numerators = ssnap_field[["ClockStartToBrainImagingMins"]],
new_numerators = ssnap_field[["ClockStartToBrainImagingMins"]],
csv_columns = c("S1PatientClockStartDateTime",
"S2BrainImagingDateTime",
"S2Thrombolysis"),
measure_type = "continuous"),
# ThrombolysedBrainImagingToNeedleMins ============================
# G 16.47 If thrombolysed, brain imaging to needle (mins)
# H 16.47 If thrombolysed, brain imaging to needle (mins)
ThrombolysedBrainImagingToNeedleMins = audit_measure(
stem_name = "ThrombolysedBrainImagingToNeedleMins",
description = "If thrombolysed, brain imaging to needle (mins)",
exclusions = rlang::expr(.data[["S2Thrombolysis"]] != "Y"),
numerators = ssnap_field[["BrainImagingToNeedleMins"]],
new_numerators = ssnap_field[["BrainImagingToNeedleMins"]],
csv_columns = "S2Thrombolysis",
measure_type = "continuous"),
# EligibleFortPAByRCPCriteria =====================================
# G 16.48-52 Eligible for tPA by RCP criteria
# H 16.48-52 Eligible for tPA by RCP criteria
EligibleFortPAByRCPCriteria = audit_measure(
stem_name = "EligibleFortPAByRCPCriteria",
description = "Eligible for tPA by RCP criteria",
exclusions = NULL,
numerators = rlang::exprs(
"Eligible" = !! ssnap_field[["EligibleFortPAByRCPCriteria"]],
"NotEligible" =
!(!! ssnap_field[["EligibleFortPAByRCPCriteria"]])),
new_numerators = tibble::tribble(
~numerator, ~fun, ~descriptor,
"Eligible",
rlang::expr(!! ssnap_field[["EligibleFortPAByRCPCriteria"]]),
"Eligible",
"NotEligible",
rlang::expr(!(!! ssnap_field[["EligibleFortPAByRCPCriteria"]])),
"Not eligible"),
csv_columns = c("S1OnsetInHospital",
"S1OnsetTimeIsPrecise",
"S1OnsetDateTime",
"S1PatientClockStartDateTime",
"S1AgeOnArrival"),
measure_type = "discrete"),
# tPAIfMeetsRCPCriteria ===========================================
# G 16.53-57 If eligible for tPA, was thrombolysis received?
# H 16.53-57 If eligible for tPA, was thrombolysis received?
tPAIfMeetsRCPCriteria = audit_measure(
stem_name = "tPAIfMeetsRCPCriteria",
description = "Thrombolysis meeting RCP criteria",
exclusions = rlang::expr(
!! ssnap_field[["ThrombolysisNoButConsistent"]] != 0),
numerators = rlang::exprs(
"Yes" = .data[["S2Thrombolysis"]] == "Y",
"No" = .data[["S2Thrombolysis"]] != "Y"),
new_numerators = tibble::tribble(
~numerator, ~fun, ~descriptor,
"Yes",
rlang::expr(.data[["S2Thrombolysis"]] == "Y"),
"Yes",
"No",
rlang::expr(.data[["S2Thrombolysis"]] != "Y"),
"No"),
csv_columns = c("S2Thrombolysis",
"S2ThrombolysisNoBut",
"S1AgeOnArrival",
"S1OnsetTimeIsPrecise",
"S1OnsetInHospital",
"S1OnsetDateTime",
"S1PatientClockStartDateTime",
"S2NihssArrival",
"S1OnsetDateIsPrecise"),
measure_type = "discrete"),
# tPAIfDoesntMeetRCPCriteria ======================================
# G 16.58-62 If not eligible for tPA, was thrombolysis received?
# H 16.58-62 If not eligible for tPA, was thrombolysis received?
tPAIfDoesntMeetRCPCriteria = audit_measure(
stem_name = "tPAIfDoesntMeetRCPCriteria",
description = "If not eligible for tPA, was tPA given?",
exclusions = rlang::expr(
!! ssnap_field[["ThrombolysisNoButConsistent"]] == 0),
numerators = rlang::exprs(
"Yes" = .data[["S2Thrombolysis"]] == "Y",
"No" = .data[["S2Thrombolysis"]] != "Y"),
new_numerators = tibble::tribble(
~numerator, ~fun, ~descriptor,
"Yes",
rlang::expr(.data[["S2Thrombolysis"]] == "Y"),
"Yes",
"No",
rlang::expr(.data[["S2Thrombolysis"]] != "Y"),
"No"),
csv_columns = c("S2Thrombolysis",
"S2ThrombolysisNoBut",
"S1AgeOnArrival",
"S1OnsetTimeIsPrecise",
"S1OnsetInHospital",
"S1OnsetDateTime",
"S1PatientClockStartDateTime",
"S2NihssArrival",
"S1OnsetDateIsPrecise"),
measure_type = "discrete"),
# EligibleOrThrombolysed ==========================================
# G 16.63-65 Was tPA given (measuring either those eligible by RCP
# criteria or those thrombolysed outside RCP criteria
# H 16.63-65 Was tPA given (measuring either those eligible by RCP
# criteria or those thrombolysed outside RCP criteria
EligibleOrThrombolysed = audit_measure(
stem_name = "EligibleOrThrombolysed",
description = paste0("Was tPA given (measuring either those ",
"eligible by RCP criteria or those thrombolysed outside RCP ",
"criteria"),
exclusions = rlang::expr(
(!(!! ssnap_field[["EligibleFortPAByRCPCriteria"]])) &
(.data[["S2Thrombolysis"]] != "Y")),
numerators = rlang::exprs(
"Yes" = .data[["S2Thrombolysis"]] == "Y",
"No" = .data[["S2Thrombolysis"]] != "Y"),
new_numerators = tibble::tribble(
~numerator, ~fun, ~descriptor,
"Yes",
rlang::expr(.data[["S2Thrombolysis"]] == "Y"),
"Yes",
"No",
rlang::expr(.data[["S2Thrombolysis"]] != "Y"),
"No"),
csv_columns = c("S2Thrombolysis",
"S1OnsetInHospital",
"S1OnsetTimeIsPrecise",
"S1OnsetDateTime",
"S1PatientClockStartDateTime",
"S1AgeOnArrival",
"S2Thrombolysis"),
measure_type = "discrete"),
# EligibleExcludingNoButs =========================================
# G 16.69-71 If eligible, patient thrombolysed (excludes "no but"s)
# H 16.69-71 If eligible, patient thrombolysed (excludes "no but"s)
EligibleExcludingNoButs = audit_measure(
stem_name = "EligibleExcludingNoButs",
description = paste0("If eligible, patient thrombolysed ",
"(excludes 'no but's)"),
exclusions = rlang::expr(
(!(!! ssnap_field[["EligibleFortPAByRCPCriteria"]])) |
(.data[["S2Thrombolysis"]] == "NB")),
numerators = rlang::exprs(
"Yes" = .data[["S2Thrombolysis"]] == "Y",
"No" = .data[["S2Thrombolysis"]] != "Y"),
new_numerators = tibble::tribble(
~numerator, ~fun, ~descriptor,
"Yes",
rlang::expr(.data[["S2Thrombolysis"]] == "Y"),
"Yes",
"No",
rlang::expr(.data[["S2Thrombolysis"]] != "Y"),
"No"),
csv_columns = c("S2Thrombolysis",
"S1OnsetInHospital",
"S1OnsetTimeIsPrecise",
"S1OnsetDateTime",
"S1PatientClockStartDateTime",
"S1AgeOnArrival",
"S2Thrombolysis"),
measure_type = "discrete"),
# tPAWithin1hr ====================================================
# G 16.72-74 Thrombolysis given within 1 hour
# H 16.72-74 Thrombolysis given within 1 hour
tPAWithin1hr = audit_measure(
stem_name = "tPAWithin1hr",
description = "Thrombolysis within 1 hour",
exclusions = rlang::expr(.data[["S2Thrombolysis"]] != "Y"),
numerators = rlang::expr(
!! ssnap_field[["ClockStartToThrombolysisMins"]] <= 60),
new_numerators = rlang::expr(
!! ssnap_field[["ClockStartToThrombolysisMins"]] <= 60),
csv_columns = c("S1PatientClockStartDateTime",
"S2ThrombolysisDateTime",
"S2Thrombolysis"),
measure_type = "discrete"),
# tPAAndSUIn4hrs ==================================================
# G 16.75.1-77.1 Thrombolysis if needed and stroke unit within 4hrs
# H 16.75.1-77.1 Thrombolysis if needed and stroke unit within 4hrs
tPAAndSUIn4hrs = audit_measure(
stem_name = "tPAAndSUIn4hrs",
description = "Thrombolysis and stroke unit in 4 hours",
exclusions = rlang::expr( (.data[["S1FirstWard"]] == "ICH") |
(!is.na(.data[["S2IAI"]]) & .data[["S2IAI"]])),
numerators = rlang::expr( (.data[["S2Thrombolysis"]] != "N") &
!! ssnap_field[["ClockStartToFirstStrokeUnitMins"]]
<= (4 * 60)),
new_numerators = rlang::expr( (.data[["S2Thrombolysis"]] != "N") &
!! ssnap_field[["ClockStartToFirstStrokeUnitMins"]]
<= (4 * 60)),
csv_columns = c("S2Thrombolysis",
"S1PatientClockStartDateTime",
"S1FirstStrokeUnitArrivalDateTime",
"S1FirstWard",
"S2IAI"),
measure_type = "discrete"),
# * -----------------------------------------------------------------
# * Thrombolysis complications --------------------------------------
# * -----------------------------------------------------------------
# ThrombolysisComplications =========================================
# G 17.1-3 Patient had complications following thrombolysis
# H 17.1-3 Patient had complications following thrombolysis
ThrombolysisComplications = audit_measure(
stem_name = "ThrombolysisComplications",
description = "Complications following thrombolysis",
exclusions = rlang::expr(.data[["S2Thrombolysis"]] != "Y"),
numerators = rlang::expr(.data[["S2ThrombolysisComplications"]]
>= 0),
new_numerators = rlang::expr(.data[["S2ThrombolysisComplications"]]
>= 0),
csv_columns = c("S2ThrombolysisComplications",
"S2Thrombolysis"),
measure_type = "discrete"),
# ThrombolysisComplicationsGrouped ==================================
# G 17.4-12 Number of each type of thrombolysis complication
# H 17.4-12 Number of each type of thrombolysis complication
ThrombolysisComplicationsGrouped = audit_measure(
stem_name = "ThrombolysisComplications",
description = "Thrombolysis complications grouped by type",
exclusions = rlang::expr(.data[["S2Thrombolysis"]] != "Y"),
numerators = rlang::exprs(
"SymptomaticICH" =
bitwAnd(.data[["S2ThrombolysisComplications"]],
ssnapinterface::tpa_complications["SymptomaticICH"]) ==
ssnapinterface::tpa_complications["SymptomaticICH"],
"Angiooedema" =
bitwAnd(.data[["S2ThrombolysisComplications"]],
ssnapinterface::tpa_complications["Angiooedema"]) ==
ssnapinterface::tpa_complications["Angiooedema"],
"ExtracranialBleed" =
bitwAnd(.data[["S2ThrombolysisComplications"]],
ssnapinterface::tpa_complications["ExtracranialBleed"]) ==
ssnapinterface::tpa_complications["ExtracranialBleed"],
"Other" = bitwAnd(.data[["S2ThrombolysisComplications"]],
ssnapinterface::tpa_complications["Other"]) ==
ssnapinterface::tpa_complications["Other"]),
new_numerators = tibble::tribble(
~numerator, ~fun, ~descriptor,
"SymptomaticICH",
rlang::expr(bitwAnd(.data[["S2ThrombolysisComplications"]],
ssnapinterface::tpa_complications["SymptomaticICH"]) ==
ssnapinterface::tpa_complications["SymptomaticICH"]),
"Symptomatic intracerebral haemorrhage",
"Angiooedema",
rlang::expr(bitwAnd(.data[["S2ThrombolysisComplications"]],
ssnapinterface::tpa_complications["Angiooedema"]) ==
ssnapinterface::tpa_complications["Angiooedema"]),
"Angiooedema",
"ExtracranialBleed",
rlang::expr(bitwAnd(.data[["S2ThrombolysisComplications"]],
ssnapinterface::tpa_complications["ExtracranialBleed"]) ==
ssnapinterface::tpa_complications["ExtracranialBleed"]),
"Extracranial bleed",
"Other",
rlang::expr(bitwAnd(.data[["S2ThrombolysisComplications"]],
ssnapinterface::tpa_complications["Other"]) ==
ssnapinterface::tpa_complications["Other"]),
"Other"),
csv_columns = c("S2ThrombolysisComplications",
"S2Thrombolysis"),
measure_type = "discrete"),
# * -----------------------------------------------------------------
# * NIHSS following thrombolysis ------------------------------------
# * -----------------------------------------------------------------
# Nihss24HrsKnown =================================================
# G 18.1-3 NIHSS at 24hrs is known
# H 18.1-3 NIHSS at 24hrs is known
# C 3.1-3 NIHSS at 24hrs is known
Nihss24HrsKnown = audit_measure(
stem_name = "Nihss24HrsKnown",
description = "NIHSS at 24 hrs known",
exclusions = rlang::expr(!( (.data[["S2Thrombolysis"]] == "Y") |
.data[["S2IAI"]])),
numerators = rlang::expr(!.data[["S2Nihss24HrsNK"]]),
new_numerators = rlang::expr(!.data[["S2Nihss24HrsNK"]]),
csv_columns = c("S2Nihss24HrsNK",
"S2Thrombolysis",
"S2IAI"),
measure_type = "discrete"),
# Nihss24hrsSeverity ==============================================
# G 18.4-14 Severity groups of NIHSS 24 hours after thrombolysis
# H 18.4-14 Severity groups of NIHSS 24 hours after thrombolysis
Nihss24hrsSeverity = audit_measure(
stem_name = "Nihss24hrsSeverity",
description = "NIHSS Severity at 24hrs",
exclusions = rlang::expr( (.data[["S2Thrombolysis"]] != "Y") |
.data[["S2Nihss24HrsNK"]]),
numerators = rlang::exprs(
"0" = .data[["S2Nihss24Hrs"]] == 0,
"1To4" = dplyr::between(.data[["S2Nihss24Hrs"]], 1, 4),
"5To15" = dplyr::between(.data[["S2Nihss24Hrs"]], 5, 15),
"16To20" = dplyr::between(.data[["S2Nihss24Hrs"]], 16, 20),
"21To42" = dplyr::between(.data[["S2Nihss24Hrs"]], 21, 42)),
new_numerators = tibble::tribble(
~numerator, ~fun, ~descriptor,
"0",
rlang::expr(.data[["S2Nihss24Hrs"]] == 0),
"0",
"1To4",
rlang::expr(dplyr::between(.data[["S2Nihss24Hrs"]], 1, 4)),
"1 to 4",
"5To15",
rlang::expr(dplyr::between(.data[["S2Nihss24Hrs"]], 5, 15)),
"5 to 15",
"16To20",
rlang::expr(dplyr::between(.data[["S2Nihss24Hrs"]], 16, 20)),
"16 to 20",
"21To42",
rlang::expr(dplyr::between(.data[["S2Nihss24Hrs"]], 21, 42)),
"21 to 42"),
csv_columns = c("S2Nihss24Hrs",
"S2Thrombolysis",
"S2Nihss24HrsNK"),
measure_type = "discrete"),
# ChangeInNIHSSAt24hrs ============================================
# G 18.15-21 Change in NIHSS from arrival to 24 hours after
# thrombolysis
# H 18.15-21 Change in NIHSS from arrival to 24 hours after
# thrombolysis
ChangeInNIHSSAt24hrs = audit_measure(
stem_name = "ChangeInNIHSSAt24hrs",
description = "Change in NIHSS at 24hrs",
exclusions = rlang::expr( (.data[["S2Thrombolysis"]] != "Y") |
.data[["S2Nihss24HrsNK"]]),
numerators = rlang::exprs(
"Improved" = .data[["S2Nihss24Hrs"]] <
.data[["S2NihssArrival"]],
"NoChange" = .data[["S2Nihss24Hrs"]] ==
.data[["S2NihssArrival"]],
"Worsened" = .data[["S2Nihss24Hrs"]] >
.data[["S2NihssArrival"]]),
new_numerators = tibble::tribble(
~numerator, ~fun, ~descriptor,
"Improved",
rlang::expr(.data[["S2Nihss24Hrs"]] <
.data[["S2NihssArrival"]]),
"Improved",
"NoChange",
rlang::expr(.data[["S2Nihss24Hrs"]] ==
.data[["S2NihssArrival"]]),
"No change",
"Worsened",
rlang::expr(.data[["S2Nihss24Hrs"]] >
.data[["S2NihssArrival"]]),
"Worsened"),
csv_columns = c("S2Nihss24Hrs",
"S2NihssArrival",
"S2Thrombolysis",
"S2Nihss24HrsNK"),
measure_type = "discrete"),
# Nihss24hrsScoreChange ===========================================
# G 18.22-44 Change in NIHSS from arrival to 24 hours after
# thrombolysis
# H 18.22-44 Change in NIHSS from arrival to 24 hours after
# thrombolysis
Nihss24hrsScoreChange = audit_measure(
stem_name = "Nihss24hrsScoreChange",
description = "Change in NIHSS score at 24 hrs",
exclusions = rlang::expr( (.data[["S2Thrombolysis"]] != "Y") |
.data[["S2Nihss24HrsNK"]]),
numerators = rlang::exprs(
"Minus13OrMore" = (.data[["S2NihssArrival"]] -
.data[["S2Nihss24Hrs"]]) < -12,
"Minus9To12" = dplyr::between( (.data[["S2NihssArrival"]] -
.data[["S2Nihss24Hrs"]]), -12, -9),
"Minus5To8" = dplyr::between( (.data[["S2NihssArrival"]] -
.data[["S2Nihss24Hrs"]]), -8, -5),
"Minus3To4" = dplyr::between( (.data[["S2NihssArrival"]] -
.data[["S2Nihss24Hrs"]]), -4, -3),
"Minus1To2" = dplyr::between( (.data[["S2NihssArrival"]] -
.data[["S2Nihss24Hrs"]]), -2, -1),
"NoChange" = .data[["S2NihssArrival"]] ==
.data[["S2Nihss24Hrs"]],
"1To2" = dplyr::between( (.data[["S2NihssArrival"]] -
.data[["S2Nihss24Hrs"]]), 1, 2),
"3To4" = dplyr::between( (.data[["S2NihssArrival"]] -
.data[["S2Nihss24Hrs"]]), 3, 4),
"5To8" = dplyr::between( (.data[["S2NihssArrival"]] -
.data[["S2Nihss24Hrs"]]), 5, 8),
"9To12" = dplyr::between( (.data[["S2NihssArrival"]] -
.data[["S2Nihss24Hrs"]]), 9, 12),
"13OrMore" = (.data[["S2NihssArrival"]] -
.data[["S2Nihss24Hrs"]]) > 12),
new_numerators = tibble::tribble(
~numerator, ~fun, ~descriptor,
"Minus13OrMore",
rlang::expr((.data[["S2NihssArrival"]] -
.data[["S2Nihss24Hrs"]]) < -12),
"-13 or better",
"Minus9To12",
rlang::expr(dplyr::between( (.data[["S2NihssArrival"]] -
.data[["S2Nihss24Hrs"]]), -12, -9)),
"-9 to -12",
"Minus5To8",
rlang::expr(dplyr::between( (.data[["S2NihssArrival"]] -
.data[["S2Nihss24Hrs"]]), -8, -5)),
"-5 to -8",
"Minus3To4",
rlang::expr(dplyr::between( (.data[["S2NihssArrival"]] -
.data[["S2Nihss24Hrs"]]), -4, -3)),
"-3 to -4",
"Minus1To2",
rlang::expr(dplyr::between( (.data[["S2NihssArrival"]] -
.data[["S2Nihss24Hrs"]]), -2, -1)),
"-2 to -1",
"NoChange",
rlang::expr(.data[["S2NihssArrival"]] == .data[["S2Nihss24Hrs"]]),
"No change",
"1To2",
rlang::expr(dplyr::between( (.data[["S2NihssArrival"]] -
.data[["S2Nihss24Hrs"]]), 1, 2)),
"+1 to +2",
"3To4",
rlang::expr(dplyr::between( (.data[["S2NihssArrival"]] -
.data[["S2Nihss24Hrs"]]), 3, 4)),
"+3 to +4",
"5To8",
rlang::expr(dplyr::between( (.data[["S2NihssArrival"]] -
.data[["S2Nihss24Hrs"]]), 5, 8)),
"+5 to +8",
"9To12",
rlang::expr(dplyr::between( (.data[["S2NihssArrival"]] -
.data[["S2Nihss24Hrs"]]), 9, 12)),
"+9 to +12",
"13OrMore",
rlang::expr((.data[["S2NihssArrival"]] -
.data[["S2Nihss24Hrs"]]) > 12),
"+13 or worse"),
csv_columns = c("S2NihssArrival",
"S2Nihss24Hrs",
"S2Thrombolysis",
"S2Nihss24HrsNK"),
measure_type = "discrete"),
# * -----------------------------------------------------------------
# * Onset to arrival ------------------------------------------------
# * -----------------------------------------------------------------
# G 19.1-11 Days from onset to arrival
# H 19.1-11 Days from onset to arrival
DaysOnsetToArrival = audit_measure(
stem_name = "DaysOnsetToArrival",
description = "Days from onset to arrival",
exclusions = rlang::expr(is.na(.data[["S1OnsetDateIsPrecise"]]) |
.data[["S1OnsetInHospital"]]),
numerators = rlang::exprs(
"SameDay" = !! ssnap_field[["DaysOnsetToArrival"]] == 0,
"PreviousDay" = !! ssnap_field[["DaysOnsetToArrival"]] == 1,
"2Days" = !! ssnap_field[["DaysOnsetToArrival"]] == 2,
"3To7Days" = dplyr::between(
!! ssnap_field[["DaysOnsetToArrival"]], 3, 7),
"Over7Days" = !! ssnap_field[["DaysOnsetToArrival"]] > 7),
new_numerators = tibble::tribble(
~numerator, ~fun, ~descriptor,
"SameDay",
rlang::expr(!! ssnap_field[["DaysOnsetToArrival"]] == 0),
"Same day",
"PreviousDay",
rlang::expr(!! ssnap_field[["DaysOnsetToArrival"]] == 1),
"Previous day",
"2Days",
rlang::expr(!! ssnap_field[["DaysOnsetToArrival"]] == 2),
"2 days",
"3To7Days",
rlang::expr(dplyr::between(
!! ssnap_field[["DaysOnsetToArrival"]], 3, 7)),
"3 to 7 days",
"Over7Days",
rlang::expr(!! ssnap_field[["DaysOnsetToArrival"]] > 7),
"Over 7 days"),
csv_columns = c("S1FirstArrivalDateTime",
"S1OnsetDateTime",
"S1OnsetDateIsPrecise",
"S1OnsetInHospital"),
measure_type = "discrete"),
# * Thrombectomy ----------------------------------------------------
# * -----------------------------------------------------------------
# Thrombectomy ====================================================
# G 20.1-3 Thrombectomy performed
# H 20.1-3 Thrombectomy performed
Thrombectomy = audit_measure(
stem_name = "Thrombectomy",
description = "Thrombectomy performed",
exclusions = NULL,
numerators = rlang::expr(.data[["S2IAI"]]),
new_numerators = rlang::expr(.data[["S2IAI"]]),
csv_columns = "S2IAI",
measure_type = "discrete"),
# OnsetToIAIPunctureMins ==========================================
# G 20.4-6 Onset to groin puncture (mins)
# H 20.4-6 Onset to groin puncture (mins)
OnsetToIAIPunctureMins = audit_measure(
stem_name = "OnsetToIAIPunctureMins",
description = "Onset to groin puncture (mins)",
exclusions = NULL,
numerators = ssnap_field[["OnsetToIAIPunctureMins"]],
new_numerators = ssnap_field[["OnsetToIAIPunctureMins"]],
csv_columns = c("S1OnsetDateTime",
"S2IAIArterialPunctureDateTime"),
measure_type = "continuous"),
# OnsetToIAICompletionMins ========================================
# G 20.7-9 Onset to thrombectomy completion (mins)
# H 20.7-9 Onset to thrombectomy completion (mins)
OnsetToIAICompletionMins = audit_measure(
stem_name = "OnsetToIAICompletionMins",
description = "Onset to thrombectomy completion (mins)",
exclusions = NULL,
numerators = ssnap_field[["OnsetToIAICompletionMins"]],
new_numerators = ssnap_field[["OnsetToIAICompletionMins"]],
csv_columns = c("S1OnsetDateTime",
"S2IAIEndOfProcedureDateTime"),
measure_type = "continuous"),
# ClockStartToIAIPunctureMins =====================================
# G 20.10-12 Clock start to groin puncture (mins)
# G 20.10-12 Clock start to groin puncture (mins)
ClockStartToIAIPunctureMins = audit_measure(
stem_name = "ClockStartToIAIPunctureMins",
description = "Clock start to groin puncture (mins)",
exclusions = NULL,
numerators = ssnap_field[["ClockStartToIAIPunctureMins"]],
new_numerators = ssnap_field[["ClockStartToIAIPunctureMins"]],
csv_columns = c("S1PatientClockStartDateTime",
"S2IAIArterialPunctureDateTime"),
measure_type = "continuous"),
# PunctureToDeploymentMins ========================================
# G 20.13-15 Groin puncture to stent retriever deployment (mins)
# H 20.13-15 Groin puncture to stent retriever deployment (mins)
PunctureToDeploymentMins = audit_measure(
stem_name = "PunctureToDeploymentMins",
description = "Groin puncture to stent deployment (mins)",
exclusions = NULL,
numerators = ssnap_field[["PunctureToDeploymentMins"]],
new_numerators = ssnap_field[["PunctureToDeploymentMins"]],
csv_columns = c("S2IAIArterialPunctureDateTime",
"S2IAIThrombectomyAspirationDeviceDateTime"),
measure_type = "continuous"),
# PunctureToIAICompletionMins =====================================
# G 20.16-18 Groin puncture to procedure completion (mins)
# H 20.16-18 Groin puncture to procedure completion (mins)
PunctureToIAICompletionMins = audit_measure(
stem_name = "PunctureToIAICompletionMins",
description = "Groin puncture to procedure completion (mins)",
exclusions = NULL,
numerators = ssnap_field[["PunctureToIAICompletionMins"]],
new_numerators = ssnap_field[["PunctureToIAICompletionMins"]],
csv_columns = c("S2IAIArterialPunctureDateTime",
"S2IAIEndOfProcedureDateTime"),
measure_type = "continuous"),
# * -----------------------------------------------------------------
# * NIHSS after Thrombectomy ----------------------------------------
# * -----------------------------------------------------------------
# G 21.1-3 NIHSS 24hrs after thrombectomy is known
# H 21.1-3 NIHSS 24hrs after thrombectomy is known
Nihss24hrsAfterIAIKnown = audit_measure(
stem_name = "Thrombectomy",
description = "Thrombectomy performed",
exclusions = rlang::expr(!.data[["S2IAI"]]),
numerators = rlang::expr(.data[["S2Nihss24HrsNK"]]),
new_numerators = rlang::expr(.data[["S2Nihss24HrsNK"]]),
csv_columns = c("S2Nihss24HrsNK",
"S2IAI"),
measure_type = "discrete"),
# * -----------------------------------------------------------------
# * Occupational therapy --------------------------------------------
# * -----------------------------------------------------------------
# OccTherApplicable ===============================================
# J 3.1-3 Applicability for patients to receive occupational
# therapy at least once during their inpatient stay
OccTherApplicable = audit_measure(
stem_name = "OccTherApplicable",
description = "Occupational Therapy applicability",
exclusions = NULL,
numerators = rlang::expr(.data[["S4OccTher"]]),
new_numerators = rlang::expr(.data[["S4OccTher"]]),
csv_columns = "S4OccTher",
measure_type = "discrete"),
# PCOccTherDays ===================================================
# J 3.4 Percentage of days of occupational therapy delivered of
# those where it is needed
PCOccTherDays = audit_measure(
stem_name = "PCOccTherDays",
description = "Percent of days occupational therapy received",
exclusions = NULL,
numerators = ssnap_field[["PCOccTherDays"]],
new_numerators = ssnap_field[["PCOccTherDays"]],
csv_columns = c("S4OccTher",
"S4OccTherDays",
"S1TeamClockStartDateTime",
"S4OccTherEndDate"),
measure_type = "continuous"),
# OccTherMinutes ==================================================
# J 3.5-7 Minutes of occupational therapy received
OccTherMinutes = audit_measure(
stem_name = "OccTherMinutes",
description = "Minutes of occupational therapy received",
exclusions = NULL,
numerators = ssnap_field[["OccTherMinutesPerDay"]],
new_numerators = ssnap_field[["PCOccTherDays"]],
csv_columns = c("S4OccTherDays",
"S4OccTherMinutes"),
measure_type = "continuous"),
# OccTherComplianceMinutes ========================================
# J 3.8 Average number of minutes of OT per day across all patients
# (Proportion of patients applicable for OT*Median percentage of
# days in hospital that OT is received*Median number of minutes per
# day on which OT is received)
OccTherComplianceMinutes = audit_measure(
stem_name = "OccTherComplianceMinutes",
description = "Minutes of occupational therapy received",
exclusions = NULL,
numerators = rlang::expr( (.data[["S4OccTher"]] / 100) *
!! ssnap_field[["OccTherMinutesPerDay"]] *
(!! ssnap_field[["PCOccTherDays"]] / 100)),
new_numerators = rlang::expr( (.data[["S4OccTher"]] / 100) *
!! ssnap_field[["OccTherMinutesPerDay"]] *
(!! ssnap_field[["PCOccTherDays"]] / 100)),
csv_columns = c("S4OccTher",
"S4OccTherDays",
"S4OccTherMinutes",
"S1TeamClockStartDateTime",
"S4OccTherEndDate"),
measure_type = "continuous"),
# OccTherComplianceTarget =========================================
# J 3.9 Occupational therapy compliance target
OccTherComplianceTarget = audit_measure(
stem_name = "OccTherComplianceTarget",
description = "Occupational therapy compliance target",
exclusions = NULL,
numerators = rlang::expr(0.8 * 45 * 5 / 7),
new_numerators = rlang::expr(0.8 * 45 * 5 / 7),
measure_type = "continuous"),
# OccTherCompliance ===============================================
# J 3.10 Occupational therapy compliance
OccTherCompliance = audit_measure(
stem_name = "OccTherCompliance",
description = "Occupational therapy compliance",
exclusions = NULL,
numerators = rlang::expr(
( (.data[["S4OccTher"]] / 100) *
!! ssnap_field[["OccTherMinutesPerDay"]] *
(!! ssnap_field[["PCOccTherDays"]] / 100)) /
(0.8 * 45 * 5 / 7) * 100),
new_numerators = rlang::expr(
( (.data[["S4OccTher"]] / 100) *
!! ssnap_field[["OccTherMinutesPerDay"]] *
(!! ssnap_field[["PCOccTherDays"]] / 100)) /
(0.8 * 45 * 5 / 7) * 100),
csv_columns = c("S4OccTher",
"S4OccTherDays",
"S4OccTherMinutes",
"S1TeamClockStartDateTime",
"S4OccTherEndDate"),
measure_type = "continuous"),
# OccTherEquivalentMinutes ========================================
# J 3.11 Average number of minutes of OT per day as equivalent to
# 45 minutes on 5 days per week for 80% of patients
OccTherEquivalentMinutes = audit_measure(
stem_name = "OccTherEquivalentMinutes",
description = "Occupational therapy equivalent minutes",
exclusions = NULL,
numerators = rlang::expr( ( (.data[["S4OccTher"]] / 100) *
!! ssnap_field[["OccTherMinutesPerDay"]] *
(!! ssnap_field[["PCOccTherDays"]] / 100)) /
(0.8 * 5 / 7)),
new_numerators = rlang::expr( ( (.data[["S4OccTher"]] / 100) *
!! ssnap_field[["OccTherMinutesPerDay"]] *
(!! ssnap_field[["PCOccTherDays"]] / 100)) /
(0.8 * 5 / 7)),
csv_columns = c("S4OccTher",
"S4OccTherDays",
"S4OccTherMinutes",
"S1TeamClockStartDateTime",
"S4OccTherEndDate"),
measure_type = "continuous"),
# TODO J 3.12-18 for All Teams
# * -----------------------------------------------------------------
# * Physiotherapy ---------------------------------------------------
# * -----------------------------------------------------------------
# PhysioApplicable ===============================================
# J 4.1-3 Applicability for patients to receive physiotherapy at
# least once during their inpatient stay
PhysioApplicable = audit_measure(
stem_name = "PhysioApplicable",
description = "Physiotherapy applicability",
exclusions = NULL,
numerators = rlang::expr(.data[["S4Physio"]]),
new_numerators = rlang::expr(.data[["S4Physio"]]),
csv_columns = "S4Physio",
measure_type = "discrete"),
# PCPhysioDays ====================================================
# J 4.4 Percentage of days of physiotherapy delivered of those
# where it is needed
PCPhysioDays = audit_measure(
stem_name = "PCPhysioDays",
description = "Percent of days physio received",
exclusions = NULL,
numerators = ssnap_field[["PCPhysioDays"]],
new_numerators = ssnap_field[["PCPhysioDays"]],
csv_columns = c("S4Physio",
"S4PhysioDays",
"S1TeamClockStartDateTime",
"S4PhysioEndDate"),
measure_type = "continuous"),
# PhysioMinutes ==================================================
# J 4.5-7 Minutes of physiotherapy received
PhysioMinutes = audit_measure(
stem_name = "PhysioMinutes",
description = "Minutes of physio received",
exclusions = NULL,
numerators = ssnap_field[["PhysioMinutesPerDay"]],
new_numerators = ssnap_field[["PhysioMinutesPerDay"]],
csv_columns = c("S4PhysioDays",
"S4PhysioMinutes"),
measure_type = "continuous"),
# PhysioComplianceMinutes =========================================
# J 4.8 Average number of minutes of OT per day across all patients
# (Proportion of patients applicable for PT*Median percentage of
# days in hospital that PT is received*Median number of minutes per
# day on which PT is received)
PhysioComplianceMinutes = audit_measure(
stem_name = "PhysioComplianceMinutes",
description = "Minutes of physiotherapy received",
exclusions = NULL,
numerators = rlang::expr( (.data[["S4Physio"]] / 100) *
!! ssnap_field[["PhysioMinutesPerDay"]] *
(!! ssnap_field[["PCPhysioDays"]] / 100)),
new_numerators = rlang::expr( (.data[["S4Physio"]] / 100) *
!! ssnap_field[["PhysioMinutesPerDay"]] *
(!! ssnap_field[["PCPhysioDays"]] / 100)),
csv_columns = c("S4Physio",
"S4PhysioDays",
"S4PhysioMinutes",
"S1TeamClockStartDateTime",
"S4PhysioEndDate"),
measure_type = "continuous"),
# PhysioComplianceTarget ==========================================
# J 4.9 Physiotherapy compliance target
PhysioComplianceTarget = audit_measure(
stem_name = "PhysioComplianceTarget",
description = "Physiotherapy compliance target",
exclusions = NULL,
numerators = rlang::expr(0.85 * 45 * 5 / 7),
new_numerators = rlang::expr(0.85 * 45 * 5 / 7),
measure_type = "continuous"),
# PhysioCompliance ================================================
# J 4.10 Physiotherapy compliance
PhysioCompliance = audit_measure(
stem_name = "PhysioCompliance",
description = "Physiotherapy compliance",
exclusions = NULL,
numerators = rlang::expr(
( (.data[["S4Physio"]] / 100) *
!! ssnap_field[["PhysioMinutesPerDay"]] *
(!! ssnap_field[["PCPhysioDays"]] / 100)) /
(0.85 * 45 * 5 / 7) * 100),
new_numerators = rlang::expr(
( (.data[["S4Physio"]] / 100) *
!! ssnap_field[["PhysioMinutesPerDay"]] *
(!! ssnap_field[["PCPhysioDays"]] / 100)) /
(0.85 * 45 * 5 / 7) * 100),
csv_columns = c("S4Physio",
"S4PhysioDays",
"S4PhysioMinutes",
"S1TeamClockStartDateTime",
"S4PhysioEndDate"),
measure_type = "continuous"),
# PhysioEquivalentMinutes ========================================
# J 4.11 Average number of minutes of PT per day as equivalent to
# 45 minutes on 5 days per week for 85% of patients
PhysioEquivalentMinutes = audit_measure(
stem_name = "PhysioEquivalentMinutes",
description = "Physiotherapy equivalent minutes",
exclusions = NULL,
numerators = rlang::expr( ( (.data[["S4Physio"]] / 100) *
!! ssnap_field[["PhysioMinutesPerDay"]] *
(!! ssnap_field[["PCPhysioDays"]] / 100)) /
(0.85 * 5 / 7)),
new_numerators = rlang::expr( ( (.data[["S4Physio"]] / 100) *
!! ssnap_field[["PhysioMinutesPerDay"]] *
(!! ssnap_field[["PCPhysioDays"]] / 100)) /
(0.85 * 5 / 7)),
csv_columns = c("S4Physio",
"S4PhysioDays",
"S4PhysioMinutes",
"S1TeamClockStartDateTime",
"S4PhysioEndDate"),
measure_type = "continuous"),
# TODO J 4.12-18 for All Teams
# * -----------------------------------------------------------------
# * Speech and language therapy -------------------------------------
# * -----------------------------------------------------------------
# SpeechLangApplicable ============================================
# J 5.1-3 Applicability for patients to receive speech and language
# therapy at least once during their inpatient stay
SpeechLangApplicable = audit_measure(
stem_name = "SpeechLangApplicable",
description = "Speech and language Therapy applicability",
exclusions = NULL,
numerators = rlang::expr(.data[["S4SpeechLang"]]),
new_numerators = rlang::expr(.data[["S4SpeechLang"]]),
csv_columns = "S4SpeechLang",
measure_type = "discrete"),
# PCSpeechLangDays ================================================
# J 5.4 Percentage of days of physiotherapy delivered of those
# where it is needed
PCSpeechLangDays = audit_measure(
stem_name = "PCSpeechLangDays",
description = "Percent of days speech and language received",
exclusions = NULL,
numerators = ssnap_field[["PCSpeechLangDays"]],
new_numerators = ssnap_field[["PCSpeechLangDays"]],
csv_columns = c("S4SpeechLang",
"S4SpeechLangDays",
"S1TeamClockStartDateTime",
"S4SpeechLangEndDate"),
measure_type = "continuous"),
# SpeechLangMinutes ===============================================
# J 5.5-7 Minutes of physiotherapy received
SpeechLangMinutes = audit_measure(
stem_name = "SpeechLangMinutes",
description = "Minutes of speech and language therapy received",
exclusions = NULL,
numerators = ssnap_field[["SpeechLangMinutesPerDay"]],
new_numerators = ssnap_field[["SpeechLangMinutesPerDay"]],
csv_columns = c("S4SpeechLangDays",
"S4SpeechLangMinutes"),
measure_type = "continuous"),
# SpeechLangComplianceMinutes =====================================
# J 4.8 Average number of minutes of SLT per day across all patients
# (Proportion of patients applicable for SLT*Median percentage of
# days in hospital that SLT is received*Median number of minutes per
# day on which PT is received)
SpeechLangComplianceMinutes = audit_measure(
stem_name = "SpeechLangComplianceMinutes",
description = "Minutes of speech and language therapy received",
exclusions = NULL,
numerators = rlang::expr( (.data[["S4SpeechLang"]] / 100) *
!! ssnap_field[["SpeechLangMinutesPerDay"]] *
(!! ssnap_field[["PCSpeechLangDays"]] / 100)),
new_numerators = rlang::expr( (.data[["S4SpeechLang"]] / 100) *
!! ssnap_field[["SpeechLangMinutesPerDay"]] *
(!! ssnap_field[["PCSpeechLangDays"]] / 100)),
csv_columns = c("S4SpeechLang",
"S4SpeechLangDays",
"S4SpeechLangMinutes",
"S1TeamClockStartDateTime",
"S4SpeechLangEndDate"),
measure_type = "continuous"),
# SpeechLangComplianceTarget ======================================
# J 5.9 Speech and language therapy compliance target
SpeechLangComplianceTarget = audit_measure(
stem_name = "SpeechLangComplianceTarget",
description = "Speech and language therapy compliance target",
exclusions = NULL,
numerators = rlang::expr(0.5 * 45 * 5 / 7),
new_numerators = rlang::expr(0.5 * 45 * 5 / 7),
measure_type = "continuous"),
# SpeechLangCompliance ============================================
# J 5.10 Speech and language therapy compliance
SpeechLangCompliance = audit_measure(
stem_name = "SpeechLangCompliance",
description = "Speech and language therapy compliance",
exclusions = NULL,
numerators = rlang::expr(
( (.data[["S4SpeechLang"]] / 100) *
!! ssnap_field[["SpeechLangMinutesPerDay"]] *
(!! ssnap_field[["PCSpeechLangDays"]] / 100)) /
(0.5 * 45 * 5 / 7) * 100),
new_numerators = rlang::expr(
( (.data[["S4SpeechLang"]] / 100) *
!! ssnap_field[["SpeechLangMinutesPerDay"]] *
(!! ssnap_field[["PCSpeechLangDays"]] / 100)) /
(0.5 * 45 * 5 / 7) * 100),
csv_columns = c("S4SpeechLang",
"S4SpeechLangDays",
"S4SpeechLangMinutes",
"S1TeamClockStartDateTime",
"S4SpeechLangEndDate"),
measure_type = "continuous"),
# SpeechLangEquivalentMinutes =====================================
# J 5.11 Average number of minutes of SLT per day as equivalent to
# 45 minutes on 5 days per week for 50% of patients
SpeechLangEquivalentMinutes = audit_measure(
stem_name = "SpeechLangEquivalentMinutes",
description = "Speech and language therapy equivalent minutes",
exclusions = NULL,
numerators = rlang::expr( ( (.data[["S4SpeechLang"]] / 100) *
!! ssnap_field[["SpeechLangMinutesPerDay"]] *
(!! ssnap_field[["PCSpeechLangDays"]] / 100)) /
(0.5 * 5 / 7)),
new_numerators = rlang::expr( ( (.data[["S4SpeechLang"]] / 100) *
!! ssnap_field[["SpeechLangMinutesPerDay"]] *
(!! ssnap_field[["PCSpeechLangDays"]] / 100)) /
(0.5 * 5 / 7)),
csv_columns = c("S4SpeechLang",
"S4SpeechLangDays",
"S4SpeechLangMinutes",
"S1TeamClockStartDateTime",
"S4SpeechLangEndDate"),
measure_type = "continuous"),
# TODO J 5.12-18 for All Teams
# * -----------------------------------------------------------------
# * All therapies ---------------------------------------------------
# * -----------------------------------------------------------------
# AnyTherapyApplicable ============================================
# J 6.1-3 Applicability for patients to receive any therapy
# discipline at least once during their inpatient stay
AnyTherapyApplicable = audit_measure(
stem_name = "AnyTherapyApplicable",
description = "Any therapy applicability",
exclusions = NULL,
numerators = rlang::expr(.data[["S4OccTher"]] |
.data[["S4Physio"]] |
.data[["S4SpeechLang"]]),
new_numerators = rlang::expr(.data[["S4OccTher"]] |
.data[["S4Physio"]] |
.data[["S4SpeechLang"]]),
csv_columns = c("S4OccTher",
"S4Physio",
"S4SpeechLang"),
measure_type = "discrete"),
# AllTherapyMinutesMet ==============================================
# J 6.4-6 For all therapy disciplines applicable, did the patient
# receive 45 mins therapy/day for at least 5 days/week?
AllTherapyMinutesMet = audit_measure(
stem_name = "AllTherapyMinutesMet",
description = "Any therapy applicability",
exclusions = rlang::expr( (!(.data[["S4OccTher"]])) &
(!(.data[["S4Physio"]])) &
(!(.data[["S4SpeechLang"]]))),
numerators = rlang::expr(
( !(.data[["S4OccTher"]]) |
( (!! ssnap_field[["OccTherMinutesPerDay"]] *
!! ssnap_field[["PCOccTherDays"]] / 100) >=
(45 * 5 / 7))) &
( !(.data[["S4Physio"]]) |
( (!! ssnap_field[["PhysioMinutesPerDay"]] *
!! ssnap_field[["PCPhysioDays"]] / 100) >=
(45 * 5 / 7))) &
( !(.data[["S4SpeechLang"]]) |
( (!! ssnap_field[["SpeechLangMinutesPerDay"]] *
!! ssnap_field[["PCSpeechLangDays"]] / 100) >=
(45 * 5 / 7)))
),
new_numerators = rlang::expr(
( !(.data[["S4OccTher"]]) |
( (!! ssnap_field[["OccTherMinutesPerDay"]] *
!! ssnap_field[["PCOccTherDays"]] / 100) >=
(45 * 5 / 7))) &
( !(.data[["S4Physio"]]) |
( (!! ssnap_field[["PhysioMinutesPerDay"]] *
!! ssnap_field[["PCPhysioDays"]] / 100) >=
(45 * 5 / 7))) &
( !(.data[["S4SpeechLang"]]) |
( (!! ssnap_field[["SpeechLangMinutesPerDay"]] *
!! ssnap_field[["PCSpeechLangDays"]] / 100) >=
(45 * 5 / 7)))
),
csv_columns = c("S4OccTher",
"S4OccTherDays",
"S4OccTherMinutes",
"S1TeamClockStartDateTime",
"S4OccTherEndDate",
"S4Physio",
"S4PhysioDays",
"S4PhysioMinutes",
"S4PhysioEndDate",
"S4SpeechLang",
"S4SpeechLangDays",
"S4SpeechLangMinutes",
"S4SpeechLangEndDate",
"S4OccTher",
"S4Physio",
"S4SpeechLang"),
measure_type = "discrete"),
# * -----------------------------------------------------------------
# * Psychology ------------------------------------------------------
# * -----------------------------------------------------------------
# PsychologyApplicable ==============================================
# J 7.1-3 Applicability for patients to receive psychology at
# least once during their inpatient stay
PsychologyApplicable = audit_measure(
stem_name = "PsychologyApplicable",
description = "Psychology applicability",
exclusions = NULL,
numerators = rlang::expr(.data[["S4Psychology"]]),
new_numerators = rlang::expr(.data[["S4Psychology"]]),
csv_columns = "S4Psychology",
measure_type = "discrete"),
# PCPsychologyDays ================================================
# J 7.4 Percentage of days of psychology delivered of those
# where it is needed
PCPsychologyDays = audit_measure(
stem_name = "PCPsychologyDays",
description = "Percent of days psychology received",
exclusions = NULL,
numerators = ssnap_field[["PCPsychologyDays"]],
new_numerators = ssnap_field[["PCPsychologyDays"]],
csv_columns = c("S4Psychology",
"S4PsychologyDays",
"S1TeamClockStartDateTime",
"S4PsychologyEndDate"),
measure_type = "continuous"),
# PsychologyMinutes ===============================================
# J 4.5-7 Minutes of psychology received
PsychologyMinutes = audit_measure(
stem_name = "PsychologyMinutes",
description = "Minutes of psychology received",
exclusions = NULL,
numerators = ssnap_field[["PsychologyMinutesPerDay"]],
new_numerators = ssnap_field[["PsychologyMinutesPerDay"]],
csv_columns = c("S4PsychologyDays",
"S4PsychologyMinutes"),
measure_type = "continuous"),
# TODO Length of stay
# * -----------------------------------------------------------------
# * Discharge destination -------------------------------------------
# * -----------------------------------------------------------------
# DischargeDestinationGrouped =====================================
# J 9.1-11.4 Discharge destination (grouped)
DischargeDestinationGrouped = audit_measure(
stem_name = "Discharge",
description = "Discharge destination",
exclusions = NULL,
numerators = rlang::exprs(
"Died" = .data[["S7DischargeType"]] == "D",
"CareHome" = .data[["S7DischargeType"]] == "CH",
"Home" = .data[["S7DischargeType"]] == "H",
"SomewhereElse" = .data[["S7DischargeType"]] == "SE",
"InpatientTransfer" = .data[["S7DischargeType"]] == "T",
"CommunityTransfer" = .data[["S7DischargeType"]] == "TC",
"InpatientTransferNonSSNAP" =
.data[["S7DischargeType"]] == "TN",
"CommunityTransferNonSSNAP" =
.data[["S7DischargeType"]] == "TCN"),
new_numerators = tibble::tribble(
~numerator, ~fun, ~descriptor,
"Died",
rlang::expr(.data[["S7DischargeType"]] == "D"),
"Died",
"CareHome",
rlang::expr(.data[["S7DischargeType"]] == "CH"),
"Care home",
"Home",
rlang::expr(.data[["S7DischargeType"]] == "H"),
"Home",
"SomewhereElse",
rlang::expr(.data[["S7DischargeType"]] == "SE"),
"Somewhere else",
"InpatientTransfer",
rlang::expr(.data[["S7DischargeType"]] == "T"),
"Inpatient transfer",
"CommunityTransfer",
rlang::expr(.data[["S7DischargeType"]] == "TC"),
"Community transfer",
"InpatientTransferNonSSNAP",
rlang::expr(.data[["S7DischargeType"]] == "TN"),
"Inpatient transfer (to a team not on SSNAP)",
"CommunityTransferNonSSNAP",
rlang::expr(.data[["S7DischargeType"]] == "TCN"),
"Community transfer (to a team not on SSNAP)"),
csv_columns = "S7DischargeType",
measure_type = "discrete"),
# DeathByDischarge ================================================
# J 9.12-18 Death by discharge
DeathByDischarge = audit_measure(
stem_name = "DeathByDischarge",
description = "Death by discharge",
exclusions = NULL,
numerators = rlang::exprs(
"No" = is.na(.data[["S7StrokeUnitDeath"]]),
"StrokeUnit" = (.data[["S7StrokeUnitDeath"]] == TRUE),
"NotStrokeUnit" = (.data[["S7StrokeUnitDeath"]] == FALSE)),
new_numerators = tibble::tribble(
~numerator, ~fun, ~descriptor,
"No",
rlang::expr(is.na(.data[["S7StrokeUnitDeath"]])),
"No",
"StrokeUnit",
rlang::expr(.data[["S7StrokeUnitDeath"]] == TRUE),
"On a stroke unit",
"NotStrokeUnit",
rlang::expr(.data[["S7StrokeUnitDeath"]] == FALSE),
"Not on a stroke unit"),
csv_columns = "S7StrokeUnitDeath",
measure_type = "discrete"),
# DischargedHome ====================================================
# J 9.19-25 Discharged home
DischargedHome = audit_measure(
stem_name = "DischargedHome",
description = "Discharged home",
exclusions = rlang::expr(is.na(.data[["S7HomeDischargeType"]])),
numerators = rlang::exprs(
"Alone" = .data[["S7HomeDischargeType"]] == "LA",
"NotAlone" = .data[["S7HomeDischargeType"]] == "NLA",
"NotKnown" = .data[["S7HomeDischargeType"]] == "NK"),
new_numerators = tibble::tribble(
~numerator, ~fun, ~descriptor,
"Alone",
rlang::expr(.data[["S7HomeDischargeType"]] == "LA"),
"Alone",
"NotAlone",
rlang::expr(.data[["S7HomeDischargeType"]] == "NLA"),
"Not alone",
"NotKnown",
rlang::expr(.data[["S7HomeDischargeType"]] == "NK"),
"Not known"),
csv_columns = c("S7HomeDischargeType",
"S7HomeDischargeType"),
measure_type = "discrete"),
# DischargedCareHome ==============================================
# J 9.26-30 Discharged to a care home
DischargedCareHome = audit_measure(
stem_name = "DischargedCareHome",
description = "Discharged to a care home",
exclusions = rlang::expr(is.na(
.data[["S7CareHomeDischargePermanentResidence"]])),
numerators = rlang::exprs(
"New" =
(.data[["S7CareHomeDischargePermanentResidence"]] == TRUE),
"NotNew" =
(.data[["S7CareHomeDischargePermanentResidence"]] == FALSE)),
new_numerators = tibble::tribble(
~numerator, ~fun, ~descriptor,
"New",
rlang::expr(.data[["S7CareHomeDischargePermanentResidence"]] == TRUE),
"New",
"NotNew",
rlang::expr(.data[["S7CareHomeDischargePermanentResidence"]] == FALSE),
"Not new"),
csv_columns = c("S7CareHomeDischargePermanentResidence",
"S7CareHomeDischargePermanentResidence"),
measure_type = "discrete"),
# NewlyInstitutionalised ==========================================
# J 9.31-33 Newly institutionalised
NewlyInstitutionalised = audit_measure(
stem_name = "NewlyInstitutionalised",
description = "Newly institutionalised following stroke",
exclusions = rlang::expr(.data[["S7DischargeType"]] == "D"),
numerators = rlang::expr(
.data[["S7CareHomeDischargeToNewResidence"]] == TRUE),
new_numerators = rlang::expr(
.data[["S7CareHomeDischargeToNewResidence"]] == TRUE),
csv_columns = c("S7CareHomeDischargeToNewResidence",
"S7DischargeType"),
measure_type = "discrete"),
# NewTemporaryInstitution =========================================
# J 9.34-38 If newly institutionalised, temporary or permanent?
NewTemporaryInstitution = audit_measure(
stem_name = "NewTemporaryInstitution",
description = "Is new institutionalisation temporary?",
exclusions = rlang::expr(
.data[["S7CareHomeDischargeToNewResidence"]] != TRUE),
numerators = rlang::exprs(
"Temporary" =
(.data[["S7CareHomeDischargePermanentResidence"]] == FALSE),
"Permanent" =
(.data[["S7CareHomeDischargePermanentResidence"]] == TRUE)),
new_numerators = tibble::tribble(
~numerator, ~fun, ~descriptor,
"Temporary",
rlang::expr(.data[["S7CareHomeDischargePermanentResidence"]] == FALSE),
"Temporary",
"Permanent",
rlang::expr(.data[["S7CareHomeDischargePermanentResidence"]] == TRUE),
"Permanent"),
csv_columns = c("S7CareHomeDischargePermanentResidence",
"S7CareHomeDischargeToNewResidence"),
measure_type = "discrete"),
# * -----------------------------------------------------------------
# * ESD -------------------------------------------------------------
# * -----------------------------------------------------------------
# DischargedESD ===================================================
# J 10.1-7 If discharged alive, discharged with early supported
# discharge (ESD) team:
DischargedESD = audit_measure(
stem_name = "DischargedESD",
description = "Discharged with ESD?",
exclusions = rlang::expr(.data[["S7DischargeType"]] == "D"),
numerators = rlang::exprs(
"Specialist" =
(.data[["S7DischargedSpecialistEsdmt"]] == TRUE),
"NotSpecialist" =
(.data[["S7DischargedSpecialistEsdmt"]] == FALSE),
"No" = is.na(.data[["S7DischargedSpecialistEsdmt"]])),
new_numerators = tibble::tribble(
~numerator, ~fun, ~descriptor,
"Specialist",
rlang::expr(.data[["S7DischargedSpecialistEsdmt"]] == TRUE),
"Specialist",
"NotSpecialist",
rlang::expr(.data[["S7DischargedSpecialistEsdmt"]] == FALSE),
"Not specialist",
"No",
rlang::expr(is.na(.data[["S7DischargedSpecialistEsdmt"]])),
"No"),
csv_columns = c("S7DischargedSpecialistEsdmt",
"S7DischargeType"),
measure_type = "discrete"),
# * -----------------------------------------------------------------
# * CRT -------------------------------------------------------------
# * -----------------------------------------------------------------
# DischargedCRT ===================================================
# J 11.1-7 If discharged alive, discharged with community rehab
# team (CRT):
DischargedCRT = audit_measure(
stem_name = "DischargedCRT",
description = "Discharged with CRT?",
exclusions = rlang::expr(.data[["S7DischargeType"]] == "D"),
numerators = rlang::exprs(
"Specialist" =
(.data[["S7DischargedSpecialistMcrt"]] == TRUE),
"NotSpecialist" =
(.data[["S7DischargedSpecialistMcrt"]] == FALSE),
"No" = is.na(.data[["S7DischargedSpecialistMcrt"]])),
new_numerators = tibble::tribble(
~numerator, ~fun, ~descriptor,
"Specialist",
rlang::expr(.data[["S7DischargedSpecialistMcrt"]] == TRUE),
"Specialist",
"NotSpecialist",
rlang::expr(.data[["S7DischargedSpecialistMcrt"]] == FALSE),
"Not specialist",
"No",
rlang::expr(is.na(.data[["S7DischargedSpecialistMcrt"]])),
"No"),
csv_columns = c("S7DischargedSpecialistMcrt",
"S7DischargeType"),
measure_type = "discrete"),
# * -----------------------------------------------------------------
# * ESD or CRT ------------------------------------------------------
# * -----------------------------------------------------------------
# DischargedSpecialistESDOrCRT ====================================
# J 12.1-3 If discharged alive, discharged with a stroke/neurology
# specific service (ESD and/or CRT)
DischargedSpecialistESDOrCRT = audit_measure(
stem_name = "DischargedSpecialistESDOrCRT",
description = "Discharged with speclist ESD or CRT?",
exclusions = rlang::expr(.data[["S7DischargeType"]] == "D"),
numerators = rlang::expr(
(.data[["S7DischargedSpecialistEsdmt"]] == TRUE) |
(.data[["S7DischargedSpecialistMcrt"]] == TRUE)),
new_numerators = rlang::expr(
(.data[["S7DischargedSpecialistEsdmt"]] == TRUE) |
(.data[["S7DischargedSpecialistMcrt"]] == TRUE)),
csv_columns = c("S7DischargedSpecialistEsdmt",
"S7DischargedSpecialistMcrt",
"S7DischargeType"),
measure_type = "discrete"),
# * -----------------------------------------------------------------
# * Rehab goals -----------------------------------------------------
# * -----------------------------------------------------------------
# RehabGoals ======================================================
# J 13.1-9 Rehabilitation goals by discharge from inpatient care
RehabGoals = audit_measure(
stem_name = "RehabGoals",
description = "Rehabilitation goals by inpatient discharge?",
exclusions = rlang::expr(.data[["S7DischargeType"]] == "D"),
numerators = rlang::exprs(
"Within5Days" =
(!!ssnap_field[["ClockStartToRehabGoalsDays"]] <= 5),
"Over5Days" =
(!!ssnap_field[["ClockStartToRehabGoalsDays"]] > 5),
"ApplicableNotSet" = is.na(.data[["S4RehabGoalsDate"]]) &
( (.data[["S4RehabGoalsNoneReason"]] == "OR") |
(.data[["S4RehabGoalsNoneReason"]] == "NK")),
"NotApplicable" = is.na(.data[["S4RehabGoalsDate"]]) &
(.data[["S4RehabGoalsNoneReason"]] != "OR") &
(.data[["S4RehabGoalsNoneReason"]] != "NK")),
new_numerators = tibble::tribble(
~numerator, ~fun, ~descriptor,
"Within5Days",
rlang::expr(!!ssnap_field[["ClockStartToRehabGoalsDays"]] <= 5),
"Within 5 days",
"Over5Days",
rlang::expr(!!ssnap_field[["ClockStartToRehabGoalsDays"]] > 5),
"Over 5 days",
"ApplicableNotSet",
rlang::expr(is.na(.data[["S4RehabGoalsDate"]]) &
( (.data[["S4RehabGoalsNoneReason"]] == "OR") |
(.data[["S4RehabGoalsNoneReason"]] == "NK"))),
"Applicable but not set",
"NotApplicable",
rlang::expr(is.na(.data[["S4RehabGoalsDate"]]) &
(.data[["S4RehabGoalsNoneReason"]] != "OR") &
(.data[["S4RehabGoalsNoneReason"]] != "NK")),
"Not applicable"),
csv_columns = c("S1PatientClockStartDateTime",
"S4RehabGoalsDate",
"S4RehabGoalsNoneReason",
"S7DischargeType"),
measure_type = "discrete"),
# RehabGoalsApplicable ============================================
# J 13.10-12 Applicability for rehabilitation goals within 5 days of
# clock start
RehabGoalsApplicable = audit_measure(
stem_name = "RehabGoalsApplicable",
description = "Applicability for rehab goals within 5 days",
exclusions = rlang::expr(.data[["S7DischargeType"]] == "D"),
numerators = rlang::expr(
(.data[["S4RehabGoalsNoneReason"]] != "OR") &
(.data[["S4RehabGoalsNoneReason"]] != "NK")),
new_numerators = rlang::expr(
(.data[["S4RehabGoalsNoneReason"]] != "OR") &
(.data[["S4RehabGoalsNoneReason"]] != "NK")),
csv_columns = c("S4RehabGoalsNoneReason",
"S7DischargeType"),
measure_type = "discrete"),
# RehabGoalsSetIfApplicable ============================================
# J 13.13-15 Rehab goals set if applicable
RehabGoalsSetIfApplicable = audit_measure(
stem_name = "RehabGoalsSetIfApplicable",
description = "Rehab goals set within 5 days if applicable",
exclusions = rlang::expr( (.data[["S7DischargeType"]] == "D") |
(.data[["S4RehabGoalsNoneReason"]] != "OR") |
(.data[["S4RehabGoalsNoneReason"]] != "NK")),
numerators = rlang::expr(
!!ssnap_field[["ClockStartToRehabGoalsDays"]] <= 5),
new_numerators = rlang::expr(
!!ssnap_field[["ClockStartToRehabGoalsDays"]] <= 5),
csv_columns = c("S1PatientClockStartDateTime",
"S4RehabGoalsDate",
"S7DischargeType",
"S4RehabGoalsNoneReason"),
measure_type = "discrete"),
# TODO J14 - composite measure.
# * -----------------------------------------------------------------
# * Post-stroke infection -------------------------------------------
# * -----------------------------------------------------------------
# UrinaryTractInfection =============================================
# K5.1-7 Urinary tract infection in first 7 days
UrinaryTractInfection = audit_measure(
stem_name = "UrinaryTractInfection",
description =
"Urinary tract infection in the first 7 days from clock start",
exclusions = NULL,
numerators = rlang::exprs(
"Yes" = (.data[["S5UrinaryTractInfection7Days"]] == TRUE),
"No" = (.data[["S5UrinaryTractInfection7Days"]] == FALSE),
"Not known" = is.na(.data[["S5UrinaryTractInfection7Days"]])),
new_numerators = tibble::tribble(
~numerator, ~fun, ~descriptor,
"Yes",
rlang::expr(.data[["S5UrinaryTractInfection7Days"]] == TRUE),
"Yes",
"No",
rlang::expr(.data[["S5UrinaryTractInfection7Days"]] == FALSE),
"No",
"Not known",
rlang::expr(is.na(.data[["S5UrinaryTractInfection7Days"]])),
"Not known"
),
csv_columns = "S5UrinaryTractInfection7Days",
measure_type = "discrete"),
# PneumoniaAntibiotics =============================================
# K6.1-7 Antibiotics for newly acquired pneumonia in first 7 days
PneumoniaAntibiotics = audit_measure(
stem_name = "PneumoniaAntibiotics",
description =
"Antibiotics for newly acquired pneumonia in the first 7 days from clock start",
exclusions = NULL,
numerators = rlang::exprs(
"Yes" = (.data[["S5PneumoniaAntibiotics7Days"]] == TRUE),
"No" = (.data[["S5PneumoniaAntibiotics7Days"]] == FALSE),
"Not known" = is.na(.data[["S5PneumoniaAntibiotics7Days"]]),
),
new_numerators = tibble::tribble(
~numerator, ~fun, ~descriptor,
"Yes",
rlang::expr(.data[["S5PneumoniaAntibiotics7Days"]] == TRUE),
"Yes",
"No",
rlang::expr(.data[["S5PneumoniaAntibiotics7Days"]] == FALSE),
"No",
"Not known",
rlang::expr(is.na(.data[["S5PneumoniaAntibiotics7Days"]])),
"Not known"),
csv_columns = "S5PneumoniaAntibiotics7Days",
measure_type = "discrete"),
# * -----------------------------------------------------------------
# * Continence plan -------------------------------------------------
# * -----------------------------------------------------------------
# ContinencePlanGrouped ===========================================
# J 15.1-11 Urinary continence plan by discharge from inpatient care
# K 2.1-11 Urinary continence plan by discharge from inpatient care
ContinencePlanGrouped = audit_measure(
stem_name = "ContinencePlanGrouped",
description = "Continence plan if applicable",
exclusions = NULL,
numerators = rlang::exprs(
"PlanDrawnUp" = !is.na(.data[["S6UrinaryContinencePlanDate"]]),
"NoPlanOrg" =
.data[["S6UrinaryContinencePlanNoPlanReason"]] == "OR",
"NoPlanRefused" =
.data[["S6UrinaryContinencePlanNoPlanReason"]] == "PR",
"NoPlanContinent" =
.data[["S6UrinaryContinencePlanNoPlanReason"]] == "PC",
"NoPlanNotKnown" =
.data[["S6UrinaryContinencePlanNoPlanReason"]] == "NK"),
new_numerators = tibble::tribble(
~numerator, ~fun, ~descriptor,
"PlanDrawnUp",
rlang::expr(!is.na(.data[["S6UrinaryContinencePlanDate"]])),
"Plan drawn up",
"NoPlanOrg",
rlang::expr(.data[["S6UrinaryContinencePlanNoPlanReason"]] == "OR"),
"No plan (organisational reasons)",
"NoPlanRefused",
rlang::expr(.data[["S6UrinaryContinencePlanNoPlanReason"]] == "PR"),
"No plan (patient refused)",
"NoPlanContinent",
rlang::expr(.data[["S6UrinaryContinencePlanNoPlanReason"]] == "PC"),
"No plan (patient continent)",
"NoPlanNotKnown",
rlang::expr(.data[["S6UrinaryContinencePlanNoPlanReason"]] == "NK"),
"No plan (reason not known)"),
csv_columns = c("S6UrinaryContinencePlanDate",
"S6UrinaryContinencePlanNoPlanReason"),
measure_type = "discrete"),
# ClockStartToContinencePlanHours =================================
# J 15.12-14 Time from clock start to continence plan drawn up (hrs)
# K 2.12-14 Time from clock start to continence plan drawn up (hrs)
ClockStartToContinencePlanHours = audit_measure(
stem_name = "ClockStartToContinencePlanHours",
description = "Clock start to continence plan (hours)",
exclusions = NULL,
numerators = ssnap_field[["ClockStartToContinencePlanHours"]],
new_numerators = ssnap_field[["ClockStartToContinencePlanHours"]],
csv_columns = c("S1PatientClockStartDateTime",
"S6UrinaryContinencePlanDate"),
measure_type = "continuous"),
# ContinencePlanApplicability =====================================
# J 15.15-17 Patient applicability for continence plan
# K 2.15-17 Patient applicability for continence plan
ContinencePlanApplicability = audit_measure(
stem_name = "ContinencePlanApplicability",
description = "Continence plan applicability",
exclusions = NULL,
numerators = rlang::expr(!(
.data[["S6UrinaryContinencePlanNoPlanReason"]] %in%
c("PC", "PR"))),
new_numerators = rlang::expr(!(
.data[["S6UrinaryContinencePlanNoPlanReason"]] %in%
c("PC", "PR"))),
csv_columns = "S6UrinaryContinencePlanNoPlanReason",
measure_type = "discrete"),
# ContinencePlanIfApplicable ======================================
# J 15.18-20 Patient applicability for continence plan
# K 2.18-20 Patient applicability for continence plan
ContinencePlanIfApplicable = audit_measure(
stem_name = "ContinencePlanIfApplicable",
description = "Continence plan if applicable",
exclusions = rlang::expr(
.data[["S6UrinaryContinencePlanNoPlanReason"]] %in%
c("PC", "PR")),
numerators = rlang::expr(
!is.null(.data[["S6UrinaryContinencePlanDate"]])),
new_numerators = rlang::expr(
!is.null(.data[["S6UrinaryContinencePlanDate"]])),
csv_columns = c("S6UrinaryContinencePlanDate",
"S6UrinaryContinencePlanNoPlanReason"),
measure_type = "discrete"),
# ContinencePlanIfApplicableIn21Days ==============================
# J 15.21-23 Continence plan completed within 21 days if applicable
ContinencePlanIfApplicableIn21Days = audit_measure(
stem_name = "ContinencePlanIfApplicableIn21Days",
description = "Continence plan if applicable",
exclusions = rlang::expr(
.data[["S6UrinaryContinencePlanNoPlanReason"]] %in%
c("PC", "PR")),
numerators = rlang::expr(
!! ssnap_field[["ClockStartToContinencePlanHours"]] <=
(21 * 24)),
new_numerators = rlang::expr(
!! ssnap_field[["ClockStartToContinencePlanHours"]] <=
(21 * 24)),
csv_columns = c("S1PatientClockStartDateTime",
"S6UrinaryContinencePlanDate",
"S6UrinaryContinencePlanNoPlanReason"),
measure_type = "discrete"),
# * -----------------------------------------------------------------
# * Nutrition -------------------------------------------------------
# * -----------------------------------------------------------------
# NutritionalScreeningByDischarge =================================
# J 16.1-3 Nutritional screening by discharge from inpatient care
# K 3.1-3 Nutritional screening by discharge from inpatient care
NutritionalScreeningByDischarge = audit_measure(
stem_name = "NutritionScreened",
description = "Nutritional screening by discharge",
exclusions = NULL,
numerators = rlang::expr(
!is.na(.data[["S6MalnutritionScreening"]])),
new_numerators = rlang::expr(
!is.na(.data[["S6MalnutritionScreening"]])),
csv_columns = "S6MalnutritionScreening",
measure_type = "discrete"),
# NutritionalScreeningHighRisk ====================================
# J 16.4-6 If received nutritional screening, were they high risk?
# K 3.4-6 If received nutritional screening, were they high risk?
NutritionalScreeningHighRisk = audit_measure(
stem_name = "NutritionScreeningHighRisk",
description = "High risk on nutritional screening",
exclusions = rlang::expr(
is.na(.data[["S6MalnutritionScreening"]])),
numerators = rlang::expr(.data[["S6MalnutritionScreening"]]),
new_numerators = rlang::expr(.data[["S6MalnutritionScreening"]]),
csv_columns = c("S6MalnutritionScreening",
"S6MalnutritionScreening"),
measure_type = "discrete"),
# NutritionSeenDietitian ==========================================
# J 16.7-9 If high risk on nutritional screening, seen dietitian?
# K 3.7-9 If high risk on nutritional screening, seen dietitian?
NutritionSeenDietitian = audit_measure(
stem_name = "NutritionScreened",
description = "High risk on nutritional screening",
exclusions = rlang::expr(
.data[["S6MalnutritionScreening"]] != TRUE),
numerators = rlang::expr(
!is.na(.data[["S6MalnutritionScreeningDietitianDate"]])),
new_numerators = rlang::expr(
!is.na(.data[["S6MalnutritionScreeningDietitianDate"]])),
csv_columns = c("S6MalnutritionScreeningDietitianDate",
"S6MalnutritionScreening"),
measure_type = "discrete"),
# NutritionalApplicability ========================================
# J 16.10.1-12.1 Applicability for nutritional screening?
# K 3.10.1-12.1 Applicability for nutritional screening?
NutritionalApplicability = audit_measure(
stem_name = "NutritionalApplicability",
description = "High risk on nutritional screening",
exclusions = rlang::expr(
!is.na(.data[["S3PalliativeCareDecisionDate"]]) |
!is.na(.data[["S6PalliativeCareByDischargeDate"]])),
numerators = rlang::expr(
.data[["S6MalnutritionScreening"]] |
is.na(.data[["S6MalnutritionScreening"]])),
new_numerators = rlang::expr(
.data[["S6MalnutritionScreening"]] |
is.na(.data[["S6MalnutritionScreening"]])),
csv_columns = c("S6MalnutritionScreening",
"S3PalliativeCareDecisionDate",
"S6PalliativeCareByDischargeDate"),
measure_type = "discrete"),
# SeenDietitianIfApplicable =======================================
# J 16.13.1-15.1 Seen dietitian if applicable?
# K 3.13.1-15.1 Seen dietitian if applicable?
SeenDietitianIfApplicable = audit_measure(
stem_name = "SeenDietitianIfApplicable",
description = "Seen dietitian if applicable?",
exclusions = rlang::expr(
!is.na(.data[["S3PalliativeCareDecisionDate"]]) |
!is.na(.data[["S6PalliativeCareByDischargeDate"]])),
numerators = rlang::expr(
(.data[["S6MalnutritionScreening"]] |
is.na(.data[["S6MalnutritionScreening"]])) &
!is.na(.data[["S6MalnutritionScreeningDietitianDate"]])),
new_numerators = rlang::expr(
(.data[["S6MalnutritionScreening"]] |
is.na(.data[["S6MalnutritionScreening"]])) &
!is.na(.data[["S6MalnutritionScreeningDietitianDate"]])),
csv_columns = c("S6MalnutritionScreening",
"S6MalnutritionScreeningDietitianDate",
"S3PalliativeCareDecisionDate",
"S6PalliativeCareByDischargeDate"),
measure_type = "discrete"),
# * -----------------------------------------------------------------
# * Mood screen -----------------------------------------------------
# * -----------------------------------------------------------------
# MoodScreenGrouped =================================================
# J 17.1-11 Mood screening by discharge from inpatient care
# K 12.1-11 Mood screening by discharge from inpatient care
MoodScreenGrouped = audit_measure(
stem_name = "MoodScreenGrouped",
description = "Mood screened if applicable",
exclusions = NULL,
numerators = rlang::exprs(
"Screened" = !is.na(.data[["S6MoodScreeningDate"]]),
"NoOrg" =
.data[["S6MoodScreeningNoScreeningReason"]] == "OR",
"NoRefused" =
.data[["S6MoodScreeningNoScreeningReason"]] == "PR",
"NoMedicallyUnwell" =
.data[["S6MoodScreeningNoScreeningReason"]] == "MU",
"NoNotKnown" =
.data[["S6MoodScreeningNoScreeningReason"]] == "NK"),
new_numerators = tibble::tribble(
~numerator, ~fun, ~descriptor,
"Screened",
rlang::expr(!is.na(.data[["S6MoodScreeningDate"]])),
"Screened",
"NoOrg",
rlang::expr(.data[["S6MoodScreeningNoScreeningReason"]] == "OR"),
"No (organisational reasons)",
"NoRefused",
rlang::expr(.data[["S6MoodScreeningNoScreeningReason"]] == "PR"),
"No (patient refused)",
"NoMedicallyUnwell",
rlang::expr(.data[["S6MoodScreeningNoScreeningReason"]] == "MU"),
"No (patient medically unwell)",
"NoNotKnown",
rlang::expr(.data[["S6MoodScreeningNoScreeningReason"]] == "NK"),
"No (reason not known)"),
csv_columns = c("S6MoodScreeningDate",
"S6MoodScreeningNoScreeningReason"),
measure_type = "discrete"),
# MoodScreenApplicability =========================================
# K12.12 Patient applicability for mood screening by discharge
# (excludes patients whose total length of stay was less than 7
# days)
# MoodScreenApplicability = audit_measure(
# stem_name = "MoodScreenApplicability",
# description = glue::glue(
# "Patient applicability for mood screening by discharge
# (excludes patients whose total length of stay was less than 7
# days)"),
# exclusions = NULL,
# numerators = rlang::expr(
# !! ssnap_field[["LengthOfFirstInptStayHrs"]] >
# (7 * 24)),
# csv_columns = c("S1PatientClockStartDateTime",
# "S7FirstInptEpisodeClockStopDateTime"),
# measure_type = "discrete"),
# CognitiveScreenApplicability ====================================
# K12.12 Patient applicability for mood screening by discharge
# (excludes patients whose total length of stay was less than 7
# days)
# CognitiveScreenApplicability = audit_measure(
# stem_name = "CognitiveScreenApplicability",
# description = glue::glue(
# "Patient applicability for cognition screening by discharge
# (excludes patients whose total length of stay was less than 7
# days)"),
# exclusions = NULL,
# numerators = rlang::expr(
# !! ssnap_field[["LengthOfFirstInptStayHrs"]] >
# (7 * 24)),
# csv_columns = c("S1PatientClockStartDateTime",
# "S7FirstInptEpisodeClockStopDateTime"),
# measure_type = "discrete"),
CognitionAndMoodAssessed = audit_measure(
stem_name = "CognitionAndMoodAssessed",
description = "Cognition and mood assessed",
exclusions = rlang::expr(
# Exclude anyone who refuses or is unwell (mood)
(.data[["S6MoodScreeningNoScreeningReason"]]
%in% c("MU", "PR")) |
# Exclude anyone who refuses or is unwell (cognition)
(.data[["S6CognitionScreeningNoScreeningReason"]]
%in% c("MU", "PR")) |
# Exclude anyone whose total length of stay is < 7 days AND
# had one or both screens omitted
( (.data[["S7TeamClockStopDateTime"]] <
(as.Date(.data[["S1PatientClockStartDateTime"]]) + 7)) &
is.na(.data[["S6MoodScreeningDate"]]) &
is.na(.data[["S6CognitionScreeningDate"]]))),
numerators = rlang::expr( (.data[["S6MoodScreeningDate"]] <
(as.Date(.data[["S1PatientClockStartDateTime"]]) + 42)) &
(.data[["S6CognitionScreeningDate"]] <
(as.Date(.data[["S1PatientClockStartDateTime"]]) + 42))),
new_numerators = rlang::expr( (.data[["S6MoodScreeningDate"]] <
(as.Date(.data[["S1PatientClockStartDateTime"]]) + 42)) &
(.data[["S6CognitionScreeningDate"]] <
(as.Date(.data[["S1PatientClockStartDateTime"]]) + 42))),
csv_columns = c("S6MoodScreeningDate",
"S1PatientClockStartDateTime",
"S6CognitionScreeningDate",
"S6MoodScreeningNoScreeningReason",
"S6CognitionScreeningNoScreeningReason",
"S7TeamClockStopDateTime",
"S1PatientClockStartDateTime",
"S6MoodScreeningDate",
"S6CognitionScreeningDate"),
measure_type = "discrete"),
StayOver90PCInStrokeUnit = audit_measure(
stem_name = "StayOver90PCInStrokeUnit",
description = "Stay over 90% on stroke unit",
exclusions = rlang::expr( (.data[["S1FirstWard"]] == "ICH") |
(!is.na(.data[["S7DeathDate"]]) &
(lubridate::day(.data[["S7DeathDate"]]) ==
lubridate::day(!! ssnap_field[["TeamClockStart"]])) &
(lubridate::month(.data[["S7DeathDate"]]) ==
lubridate::month(!! ssnap_field[["TeamClockStart"]])) &
(lubridate::year(.data[["S7DeathDate"]]) ==
lubridate::year(!! ssnap_field[["TeamClockStart"]])))
),
numerators = rlang::expr(!! ssnap_field[["StayPercent"]] >= 90),
new_numerators = rlang::expr(!! ssnap_field[["StayPercent"]] >= 90),
csv_columns = c("S1TeamClockStartDateTime",
"S7TeamClockStopDateTime",
"S4StrokeUnitArrivalDateTime",
"S7StrokeUnitDischargeDateTime",
"S1FirstWard",
"S7DeathDate"),
measure_type = "discrete"),
JointCarePlanning = audit_measure(
stem_name = "JointCarePlanning",
description = "Joint care planning",
exclusions = rlang::expr(
# Exclude patients who die or whose last known records
# indicates transfer to another inpatient team.
.data[["S7DischargeType"]] %in% c("D", "T")),
numerators = rlang::expr(.data[["S7DischargeJointCarePlanning"]]),
new_numerators = rlang::expr(.data[["S7DischargeJointCarePlanning"]]),
csv_columns = c("S7DischargeJointCarePlanning",
"S7DischargeType"),
measure_type = "discrete"),
DischargedWithESD = audit_measure(
stem_name = "DischargedWithESD",
description = "Discharged with ESD",
exclusions = rlang::expr(
# Exclude patients who die or whose last known records
# indicates transfer to another inpatient team.
.data[["S7DischargeType"]] %in% c("D", "T")),
numerators = rlang::expr(dplyr::case_when(
(is.na(.data[["S7DischargedSpecialistEsdmt"]]) &
is.na(.data[["S7DischargedSpecialistMcrt"]])) ~ FALSE,
TRUE ~ (.data[["S7DischargedSpecialistEsdmt"]] |
.data[["S7DischargedSpecialistMcrt"]]))),
new_numerators = rlang::expr(dplyr::case_when(
(is.na(.data[["S7DischargedSpecialistEsdmt"]]) &
is.na(.data[["S7DischargedSpecialistMcrt"]])) ~ FALSE,
TRUE ~ (.data[["S7DischargedSpecialistEsdmt"]] |
.data[["S7DischargedSpecialistMcrt"]]))),
csv_columns = c("S7DischargedSpecialistEsdmt",
"S7DischargedSpecialistMcrt",
"S7DischargeType"),
measure_type = "discrete"),
AFWithAnticoagulation = audit_measure(
stem_name = "AFWithAnticoagulation",
description = "AF discharged with anticoagulation plan",
exclusions = rlang::expr(
# Exclude patients who die or whose last known records indicates
# transfer to another inpatient team.
# Exclude patients who are not in atrial fibrillation
# Patients with "no but" for anticoagulation are excluded
(.data[["S7DischargeType"]] %in% c("D", "T")) |
(!.data[["S7DischargeAtrialFibrillation"]]) |
(is.na(
.data[["S7DischargeAtrialFibrillationAnticoagulation"]]))),
numerators = rlang::expr(
.data[["S7DischargeAtrialFibrillationAnticoagulation"]]),
new_numerators = rlang::expr(
.data[["S7DischargeAtrialFibrillationAnticoagulation"]]),
csv_columns = c("S7DischargeAtrialFibrillationAnticoagulation",
"S7DischargeType",
"S7DischargeAtrialFibrillation",
"S7DischargeAtrialFibrillationAnticoagulation"),
measure_type = "discrete"),
DischargeNamedContact = audit_measure(
stem_name = "DischargeNamedContact",
description = "Discharged with named contact",
exclusions = rlang::expr(
# Exclude patients who die or whose last known records
# indicates transfer to another inpatient team.
.data[["S7DischargeType"]] %in% c("D", "T")),
numerators = rlang::expr(.data[["S7DischargeNamedContact"]]),
new_numerators = rlang::expr(.data[["S7DischargeNamedContact"]]),
csv_columns = c("S7DischargeNamedContact",
"S7DischargeType"),
measure_type = "discrete"),
SixMonthFollowUp = audit_measure(
stem_name = "SixMonthFollowUp",
description = "Breakdown of six month follow-up provision",
exclusions = NULL,
numerators = rlang::exprs(
"Yes" = .data[["S8FollowUp"]] == "Y",
"DiedOnAcutePathway" = is.null(.data[["S8FollowUp"]]) &
(.data[["S7DischargeType"]] == "D"),
"DiedWithin6Months" = .data[["S8FollowUp"]] == "ND",
"NoBut" = .data[["S8FollowUp"]] == "NB",
"No" = .data[["S8FollowUp"]] == "N",
"Blank" = is.null(.data[["S8FollowUp"]]) &
(.data[["S7DischargeType"]] != "D")),
new_numerators = tibble::tribble(
~numerator, ~fun, ~descriptor,
"Yes",
rlang::expr(.data[["S8FollowUp"]] == "Y"),
"Yes",
"DiedOnAcutePathway",
rlang::expr(is.null(.data[["S8FollowUp"]]) &
(.data[["S7DischargeType"]] == "D")),
"Died on acute pathway",
"DiedWithin6Months",
rlang::expr(.data[["S8FollowUp"]] == "ND"),
"Died within 6 months",
"NoBut",
rlang::expr(.data[["S8FollowUp"]] == "NB"),
"No (but reason given)",
"No",
rlang::expr(.data[["S8FollowUp"]] == "N"),
"No (no reason given)",
"Blank",
rlang::expr(is.null(.data[["S8FollowUp"]]) &
(.data[["S7DischargeType"]] != "D")),
"Blank"),
csv_columns = c("S8FollowUp",
"S7DischargeType"),
measure_type = "discrete"),
SixMonthAnsweredApplicability = audit_measure(
stem_name = "SixMonthAnsweredApplicability",
description = glue::glue(
"Patient record deemed appropriate to be actively answered
(excludes died in care)"),
exclusions = NULL,
numerators = rlang::expr(.data[["S7DischargeType"]] != "D"),
new_numerators = rlang::expr(.data[["S7DischargeType"]] != "D"),
csv_columns = "S7DischargeType",
measure_type = "discrete"),
SixMonthAnswered = audit_measure(
stem_name = "SixMonthAnswered",
description = glue::glue(
"Section 8 has been actively answered, if record appropriate
for completion"),
exclusions = rlang::expr(.data[["S7DischargeType"]] == "D"),
numerators = rlang::expr(!is.null(.data[["S8FollowUp"]])),
new_numerators = rlang::expr(!is.null(.data[["S8FollowUp"]])),
csv_columns = c("S8FollowUp",
"S7DischargeType"),
measure_type = "discrete"),
SixMonthFollowupApplicability = audit_measure(
stem_name = "SixMonthFollowupApplicability",
description = glue::glue(
"Applicability for follow-up to be undertaken (excludes died
in care, died within 6 months of admission, and 'no but')"),
exclusions = NULL,
numerators = rlang::expr( (.data[["S7DischargeType"]] != "D") &
(.data[["S8FollowUp"]] != "ND") &
(.data[["S8FollowUp"]] != "NB")),
new_numerators = rlang::expr( (.data[["S7DischargeType"]] != "D") &
(.data[["S8FollowUp"]] != "ND") &
(.data[["S8FollowUp"]] != "NB")),
csv_columns = c("S7DischargeType",
"S8FollowUp"),
measure_type = "discrete"),
SixMonthFollowupCompleted = audit_measure(
stem_name = "SixMonthFollowupCompleted",
description = glue::glue(
"Six month followup completed"),
exclusions = rlang::expr( (.data[["S7DischargeType"]] == "D") |
(.data[["S8FollowUp"]] == "ND") |
(.data[["S8FollowUp"]] == "NB")),
numerators = rlang::expr(.data[["S7DischargeType"]] == "Y"),
new_numerators = rlang::expr(.data[["S7DischargeType"]] == "Y"),
csv_columns = c("S7DischargeType",
"S7DischargeType",
"S8FollowUp"),
measure_type = "discrete"),
# ClockStartTo6MonthAssessmentMonths ==============================
ClockStartTo6MonthAssessmentMonths = audit_measure(
stem_name = "ClockStartTo6MonthAssessmentMonths",
description =
"Number of months from Clock Start to six month assessment",
exclusions = rlang::expr(.data[["S8FollowUp"]] != "Y"),
numerators = ssnap_field[["ClockStartTo6MonthAssessmentMonths"]],
new_numerators = ssnap_field[["ClockStartTo6MonthAssessmentMonths"]],
csv_columns = c("S1PatientClockStartDateTime",
"S8FollowUpDate",
"S8FollowUp"),
measure_type = "continuous"),
DischargeTo6MonthAssessmentMonths = audit_measure(
stem_name = "DischargeTo6MonthAssessmentMonths",
description =
"Number of months from discharge to six month assessment",
exclusions = rlang::expr(.data[["S8FollowUp"]] != "Y"),
numerators = ssnap_field[["DischargeTo6MonthAssessmentMonths"]],
new_numerators = ssnap_field[["DischargeTo6MonthAssessmentMonths"]],
csv_columns = c("S7HospitalDischargeDateTime",
"S8FollowUpDate",
"S8FollowUp"),
measure_type = "continuous"),
FollowUpType = audit_measure(
stem_name = "FollowUpType",
description = "Follow-up type",
exclusions = rlang::expr(.data[["S8FollowUp"]] != "Y"),
numerators = rlang::exprs(
"InPerson" = .data[["S8FollowUpType"]] == "IP",
"Online" = .data[["S8FollowUpType"]] == "O",
"Telephone" = .data[["S8FollowUpType"]] == "T",
"Post" = .data[["S8FollowUpType"]] == "P"),
new_numerators = tibble::tribble(
~numerator, ~fun, ~descriptor,
"InPerson",
rlang::expr(.data[["S8FollowUpType"]] == "IP"),
"In person",
"Online",
rlang::expr(.data[["S8FollowUpType"]] == "O"),
"Online",
"Telephone",
rlang::expr(.data[["S8FollowUpType"]] == "T"),
"Telephone",
"Post",
rlang::expr(.data[["S8FollowUpType"]] == "P"),
"Post"),
csv_columns = c("S8FollowUpType",
"S8FollowUp"),
measure_type = "discrete"),
FollowUpProvider = audit_measure(
stem_name = "FollowUpProvider",
description = "Follow-up provider",
exclusions = rlang::expr(.data[["S8FollowUp"]] != "Y"),
numerators = rlang::exprs(
"GP" = .data[["S8FollowUpBy"]] == "GP",
"StrokeCoordinator" = .data[["S8FollowUpBy"]] == "SC",
"Therapist" = .data[["S8FollowUpBy"]] == "T",
"CommunityNurse" = .data[["S8FollowUpBy"]] == "DN",
"Voluntary" = .data[["S8FollowUpBy"]] == "VS",
"SecondaryCare" = .data[["S8FollowUpBy"]] == "SCC",
"Other" = .data[["S8FollowUpBy"]] == "O"),
new_numerators = tibble::tribble(
~numerator, ~fun, ~descriptor,
"GP",
rlang::expr(.data[["S8FollowUpBy"]] == "GP"),
"GP",
"StrokeCoordinator",
rlang::expr(.data[["S8FollowUpBy"]] == "SC"),
"Stroke coordinator",
"Therapist",
rlang::expr(.data[["S8FollowUpBy"]] == "T"),
"Therapist",
"CommunityNurse",
rlang::expr(.data[["S8FollowUpBy"]] == "DN"),
"Community nurse",
"Voluntary",
rlang::expr(.data[["S8FollowUpBy"]] == "VS"),
"Voluntary",
"SecondaryCare",
rlang::expr(.data[["S8FollowUpBy"]] == "SCC"),
"Secondary care",
"Other",
rlang::expr(.data[["S8FollowUpBy"]] == "O"),
"Other"),
csv_columns = c("S8FollowUpBy",
"S8FollowUp"),
measure_type = "discrete"),
FollowUpMood = audit_measure(
stem_name = "FollowUpMood",
description = "Mood, behaviour, cognition screening",
exclusions = rlang::expr(.data[["S8FollowUp"]] != "Y"),
numerators = rlang::exprs(
"Yes" = .data[["S8MoodBehaviourCognitiveScreened"]] == TRUE,
"No" = .data[["S8MoodBehaviourCognitiveScreened"]] == FALSE,
"NoBut" = is.na(.data[["S8MoodBehaviourCognitiveScreened"]])),
new_numerators = tibble::tribble(
~numerator, ~fun, ~descriptor,
"Yes",
rlang::expr(.data[["S8MoodBehaviourCognitiveScreened"]] == TRUE),
"Yes",
"No",
rlang::expr(.data[["S8MoodBehaviourCognitiveScreened"]] == FALSE),
"No",
"NoBut",
rlang::expr(is.na(.data[["S8MoodBehaviourCognitiveScreened"]])),
"No but"),
csv_columns = c("S8MoodBehaviourCognitiveScreened",
"S8FollowUp"),
measure_type = "discrete"),
FollowUpMoodSupportNeeded = audit_measure(
stem_name = "FollowUpMood",
description = "Mood, behaviour, cognition screening",
exclusions = rlang::expr(
.data[["S8MoodBehaviourCognitiveScreened"]] != "Y"),
numerators = rlang::expr(
.data[["S8MoodBehaviourCognitiveSupportNeeded"]] == TRUE),
new_numerators = rlang::expr(
.data[["S8MoodBehaviourCognitiveSupportNeeded"]] == TRUE),
csv_columns = c("S8MoodBehaviourCognitiveSupportNeeded",
"S8MoodBehaviourCognitiveScreened"),
measure_type = "discrete"),
FollowUpPsychologicalSupport = audit_measure(
stem_name = "FollowUpPsychologicalSupport",
description = glue::glue(
"If support needed, psychological support received since
discharge"),
exclusions = rlang::expr(
.data[["S8MoodBehaviourCognitiveSupportNeeded"]] != TRUE),
numerators = rlang::exprs(
"Yes" = .data[[
"S8MoodBehaviourCognitivePsychologicalSupport"]] == TRUE,
"No" = .data[[
"S8MoodBehaviourCognitivePsychologicalSupport"]] == FALSE,
"NoBut" = is.na(.data[[
"S8MoodBehaviourCognitivePsychologicalSupport"]])),
new_numerators = tibble::tribble(
~numerator, ~fun, ~descriptor,
"Yes",
rlang::expr(.data[["S8MoodBehaviourCognitivePsychologicalSupport"]] == TRUE),
"Yes",
"No",
rlang::expr(.data[["S8MoodBehaviourCognitivePsychologicalSupport"]] == FALSE),
"No",
"NoBut",
rlang::expr(is.na(.data[["S8MoodBehaviourCognitivePsychologicalSupport"]])),
"No but"),
csv_columns = c("S8MoodBehaviourCognitivePsychologicalSupport",
"S8MoodBehaviourCognitiveSupportNeeded"),
measure_type = "discrete"),
FollowUpLiving = audit_measure(
stem_name = "FollowUpLiving",
description = "Where the patient is living",
exclusions = rlang::expr(.data[["S8FollowUp"]] != "Y"),
numerators = rlang::exprs(
"Home" = .data[["S8Living"]] == "H",
"CareHome" = .data[["S8Living"]] == "CH",
"Other" = .data[["S8Living"]] == "O"),
new_numerators = tibble::tribble(
~numerator, ~fun, ~descriptor,
"Home",
rlang::expr(.data[["S8Living"]] == "H"),
"Home",
"CareHome",
rlang::expr(.data[["S8Living"]] == "CH"),
"Care home",
"Other",
rlang::expr(.data[["S8Living"]] == "O"),
"Other"),
csv_columns = c("S8Living",
"S8FollowUp"),
measure_type = "discrete"),
FollowUpRankin6Month = audit_measure(
stem_name = "FollowUpRankinNotKnown",
description = "Modified Rankin Scale is not known",
exclusions = rlang::expr(.data[["S8FollowUp"]] != "Y"),
numerators = rlang::exprs(
"0" = .data[["S8Rankin6Month"]] == 0,
"1" = .data[["S8Rankin6Month"]] == 1,
"2" = .data[["S8Rankin6Month"]] == 2,
"3" = .data[["S8Rankin6Month"]] == 3,
"4" = .data[["S8Rankin6Month"]] == 4,
"5" = .data[["S8Rankin6Month"]] == 5,
"6" = (.data[["S7DischargeType"]] == "D") |
(.data[["S8FollowUp"]] == "ND"),
"NotKnown" = is.na(.data[["S8Rankin6Month"]])),
new_numerators = tibble::tribble(
~numerator, ~fun, ~descriptor,
"0",
rlang::expr(.data[["S8Rankin6Month"]] == 0),
"0",
"1",
rlang::expr(.data[["S8Rankin6Month"]] == 1),
"1",
"2",
rlang::expr(.data[["S8Rankin6Month"]] == 2),
"2",
"3",
rlang::expr(.data[["S8Rankin6Month"]] == 3),
"3",
"4",
rlang::expr(.data[["S8Rankin6Month"]] == 4),
"4",
"5",
rlang::expr(.data[["S8Rankin6Month"]] == 5),
"5",
"6",
rlang::expr((.data[["S7DischargeType"]] == "D") |
(.data[["S8FollowUp"]] == "ND")),
"6",
"NotKnown",
rlang::expr(is.na(.data[["S8Rankin6Month"]])),
"Not known"),
csv_columns = c("S8Rankin6Month",
"S7DischargeType",
"S8FollowUp",
"S8FollowUp"),
measure_type = "discrete"),
FollowUpAtrialFibrillation = audit_measure(
stem_name = "FollowUpAtrialFibrillation",
description = glue::glue(
"Persistent, permanent or paroxysmal Atrial Fibrillation (AF)
at the time of six month follow-up assessment"),
exclusions = rlang::expr(.data[["S8FollowUp"]] != "Y"),
numerators = rlang::exprs(
"Yes" = .data[["S8PersistentAtrialFibrillation"]] == TRUE,
"No" = .data[["S8PersistentAtrialFibrillation"]] == FALSE,
"NoBut" = is.na(.data[["S8PersistentAtrialFibrillation"]])),
new_numerators = tibble::tribble(
~numerator, ~fun, ~descriptor,
"Yes",
rlang::expr(.data[["S8PersistentAtrialFibrillation"]] == TRUE),
"Yes",
"No",
rlang::expr(.data[["S8PersistentAtrialFibrillation"]] == FALSE),
"No",
"NoBut",
rlang::expr(is.na(.data[["S8PersistentAtrialFibrillation"]])),
"No but"),
csv_columns = c("S8PersistentAtrialFibrillation",
"S8FollowUp"),
measure_type = "discrete"),
FollowUpAFFromAdmission = audit_measure(
stem_name = "FollowUpAFFromAdmission",
description = glue::glue(
"If patient is in AF at six month follow-up assessment, was
also in AF when first admitted to hospital"),
exclusions = rlang::expr(
.data[["S8PersistentAtrialFibrillation"]] != TRUE),
numerators = rlang::expr(
.data[["S2CoMAtrialFibrillation"]] == TRUE),
new_numerators = rlang::expr(
.data[["S2CoMAtrialFibrillation"]] == TRUE),
csv_columns = c("S2CoMAtrialFibrillation",
"S8PersistentAtrialFibrillation"),
measure_type = "discrete"),
FollowUpAFFromDischarge = audit_measure(
stem_name = "FollowUpAFFromDischarge",
description = glue::glue(
"If patient is in AF at six month follow-assessment, was also
in AF when discharged from inpatient care"),
exclusions = rlang::expr(
.data[["S8PersistentAtrialFibrillation"]] != TRUE),
numerators = rlang::expr(
.data[["S7DischargeAtrialFibrillation"]] == TRUE),
new_numerators = rlang::expr(
.data[["S7DischargeAtrialFibrillation"]] == TRUE),
csv_columns = c("S7DischargeAtrialFibrillation",
"S8PersistentAtrialFibrillation"),
measure_type = "discrete"),
FollowUpAFOnAnticoagulant = audit_measure(
stem_name = "FollowUpAFOnAnticoagulant",
description = glue::glue(
"If patient is in AF at six month follow-up assessment, then
taking anti-coagulant"),
exclusions = rlang::expr(
.data[["S8PersistentAtrialFibrillation"]] != TRUE),
numerators = rlang::expr(
.data[["S8TakingAnticoagulent"]] == TRUE),
new_numerators = rlang::expr(
.data[["S8TakingAnticoagulent"]] == TRUE),
csv_columns = c("S8TakingAnticoagulent",
"S8PersistentAtrialFibrillation"),
measure_type = "discrete"),
FollowUpTakingAntiplatelet = audit_measure(
stem_name = "FollowUpTakingAntiplatelet",
description = "Taking antiplatelet",
exclusions = rlang::expr(.data[["S8FollowUp"]] != "Y"),
numerators = rlang::exprs(
"Yes" = .data[["S8TakingAntiplateletDrug"]] == TRUE,
"No" = .data[["S8TakingAntiplateletDrug"]] == FALSE,
"NoBut" = is.na(.data[["S8TakingAntiplateletDrug"]])),
new_numerators = tibble::tribble(
~numerator, ~fun, ~descriptor,
"Yes",
rlang::expr(.data[["S8TakingAntiplateletDrug"]] == TRUE),
"Yes",
"No",
rlang::expr(.data[["S8TakingAntiplateletDrug"]] == FALSE),
"No",
"NoBut",
rlang::expr(is.na(.data[["S8TakingAntiplateletDrug"]])),
"No but"),
csv_columns = c("S8TakingAntiplateletDrug",
"S8FollowUp"),
measure_type = "discrete"),
FollowUpTakingAnticoagulant = audit_measure(
stem_name = "FollowUpTakingAnticoagulant",
description = "Taking anticoagulant",
exclusions = rlang::expr(.data[["S8FollowUp"]] != "Y"),
numerators = rlang::exprs(
"Yes" = .data[["S8TakingAnticoagulent"]] == TRUE,
"No" = .data[["S8TakingAnticoagulent"]] == FALSE,
"NoBut" = is.na(.data[["S8TakingAnticoagulent"]])),
new_numerators = tibble::tribble(
~numerator, ~fun, ~descriptor,
"Yes",
rlang::expr(.data[["S8TakingAnticoagulent"]] == TRUE),
"Yes",
"No",
rlang::expr(.data[["S8TakingAnticoagulent"]] == FALSE),
"No",
"NoBut",
rlang::expr(is.na(.data[["S8TakingAnticoagulent"]])),
"No but"),
csv_columns = c("S8TakingAnticoagulent",
"S8FollowUp"),
measure_type = "discrete"),
FollowUpAnticoagulantSinceDischarge = audit_measure(
stem_name = "FollowUpAnticoagulantSinceDischarge",
description = glue::glue(
"If patient was discharged on anti-coagulant, still taking at
six month follow-up assessment"),
exclusions = rlang::expr(
.data[["S8TakingAnticoagulent"]] != TRUE),
numerators = rlang::expr(.data[[
"S7DischargeAtrialFibrillationAnticoagulation"]] == TRUE),
new_numerators = rlang::expr(.data[[
"S7DischargeAtrialFibrillationAnticoagulation"]] == TRUE),
csv_columns = c("S7DischargeAtrialFibrillationAnticoagulation",
"S8TakingAnticoagulent"),
measure_type = "discrete"),
FollowUpTakingLipidLowering = audit_measure(
stem_name = "FollowUpTakingLipidLowering",
description = "Taking lipid lowering drug",
exclusions = rlang::expr(.data[["S8FollowUp"]] != "Y"),
numerators = rlang::exprs(
"Yes" = .data[["S8TakingLipidLowering"]] == TRUE,
"No" = .data[["S8TakingLipidLowering"]] == FALSE,
"NoBut" = is.na(.data[["S8TakingLipidLowering"]])),
new_numerators = tibble::tribble(
~numerator, ~fun, ~descriptor,
"Yes",
rlang::expr(.data[["S8TakingLipidLowering"]] == TRUE),
"Yes",
"No",
rlang::expr(.data[["S8TakingLipidLowering"]] == FALSE),
"No",
"NoBut",
rlang::expr(is.na(.data[["S8TakingLipidLowering"]])),
"No but"),
csv_columns = c("S8TakingLipidLowering",
"S8FollowUp"),
measure_type = "discrete"),
FollowUpTakingAntihypertensive = audit_measure(
stem_name = "FollowUpTakingAntihypertensive",
description = "Taking antihypertensive",
exclusions = rlang::expr(.data[["S8FollowUp"]] != "Y"),
numerators = rlang::exprs(
"Yes" = .data[["S8TakingAntihypertensive"]] == TRUE,
"No" = .data[["S8TakingAntihypertensive"]] == FALSE,
"NoBut" = is.na(.data[["S8TakingAntihypertensive"]])),
new_numerators = tibble::tribble(
~numerator, ~fun, ~descriptor,
"Yes",
rlang::expr(.data[["S8TakingAntihypertensive"]] == TRUE),
"Yes",
"No",
rlang::expr(.data[["S8TakingAntihypertensive"]] == FALSE),
"No",
"NoBut",
rlang::expr(is.na(.data[["S8TakingAntihypertensive"]])),
"No but"),
csv_columns = c("S8TakingAntihypertensive",
"S8FollowUp"),
measure_type = "discrete"),
SinceStrokeAnotherStroke = audit_measure(
stem_name = "SinceStrokeAnotherStroke",
description = "Since stroke, another stroke",
exclusions = rlang::expr(.data[["S8FollowUp"]] != "Y"),
numerators = rlang::exprs(
"Yes" = .data[["S8SinceStrokeAnotherStroke"]] == TRUE,
"No" = .data[["S8SinceStrokeAnotherStroke"]] == FALSE,
"NoBut" = is.na(.data[["S8SinceStrokeAnotherStroke"]])),
new_numerators = tibble::tribble(
~numerator, ~fun, ~descriptor,
"Yes",
rlang::expr(.data[["S8SinceStrokeAnotherStroke"]] == TRUE),
"Yes",
"No",
rlang::expr(.data[["S8SinceStrokeAnotherStroke"]] == FALSE),
"No",
"NoBut",
rlang::expr(is.na(.data[["S8SinceStrokeAnotherStroke"]])),
"No but"),
csv_columns = c("S8SinceStrokeAnotherStroke",
"S8FollowUp"),
measure_type = "discrete"),
SinceStrokeMyocardialInfarction = audit_measure(
stem_name = "SinceStrokeMyocardialInfarction",
description = "Since stroke, myocardial infarction",
exclusions = rlang::expr(.data[["S8FollowUp"]] != "Y"),
numerators = rlang::exprs(
"Yes" = .data[["S8SinceStrokeMyocardialInfarction"]] == TRUE,
"No" = .data[["S8SinceStrokeMyocardialInfarction"]] == FALSE,
"NoBut" = is.na(.data[["S8SinceStrokeMyocardialInfarction"]])),
new_numerators = tibble::tribble(
~numerator, ~fun, ~descriptor,
"Yes",
rlang::expr(.data[["S8SinceStrokeMyocardialInfarction"]] == TRUE),
"Yes",
"No",
rlang::expr(.data[["S8SinceStrokeMyocardialInfarction"]] == FALSE),
"No",
"NoBut",
rlang::expr(is.na(.data[["S8SinceStrokeMyocardialInfarction"]])),
"No but"),
csv_columns = c("S8SinceStrokeMyocardialInfarction",
"S8FollowUp"),
measure_type = "discrete"),
SinceStrokeHospitalisation = audit_measure(
stem_name = "SinceStrokeHospitalisation",
description =
"Since stroke, other illness requiring hospitalisation",
exclusions = rlang::expr(.data[["S8FollowUp"]] != "Y"),
numerators = rlang::exprs(
"Yes" =
.data[["S8SinceStrokeOtherHospitalisationIllness"]] == TRUE,
"No" =
.data[["S8SinceStrokeOtherHospitalisationIllness"]] == FALSE,
"NoBut" =
is.na(.data[["S8SinceStrokeOtherHospitalisationIllness"]])),
new_numerators = tibble::tribble(
~numerator, ~fun, ~descriptor,
"Yes",
rlang::expr(.data[["S8SinceStrokeOtherHospitalisationIllness"]] == TRUE),
"Yes",
"No",
rlang::expr(.data[["S8SinceStrokeOtherHospitalisationIllness"]] == FALSE),
"No",
"NoBut",
rlang::expr(is.na(.data[["S8SinceStrokeOtherHospitalisationIllness"]])),
"No but"),
csv_columns = c("S8SinceStrokeOtherHospitalisationIllness",
"S8FollowUp"),
measure_type = "discrete"),
# ClinicianAssessedWithin1hr ===================================
ClinicianAssessedWithin1hr = audit_measure(
stem_name = "ClinicianAssessedWithin1hr",
description = "Assessed by stroke consultant or nurse within 1 hr",
exclusions = NULL,
numerators = rlang::expr(
(!!ssnap_field[["ClockStartToConsultantMins"]] <= 60) |
(!!ssnap_field[["ClockStartToStrokeNurseMins"]] <= 60)),
new_numerators = rlang::expr(
(!!ssnap_field[["ClockStartToConsultantMins"]] <= 60) |
(!!ssnap_field[["ClockStartToStrokeNurseMins"]] <= 60)),
csv_columns = c("S1PatientClockStartDateTime",
"S3StrokeNurseAssessedDateTime",
"S3StrokeConsultantAssessedDateTime"),
measure_type = "discrete"),
# tPACriticalHourStandardWithin1hr =============================
tPACriticalHourStandardWithin1hr = audit_measure(
stem_name = "tPACriticalHourStandardWithin1hr",
description = glue::glue("
If an ischaemic stroke arriving within 4hrs of onset,
was thrombolysis administered within 1 hour"),
exclusions = rlang::expr(
(tidyr::replace_na(!! ssnap_field[["OnsetToArrivalTimeMins"]], 999)
> (4 * 60)) |
(!.data[["S2StrokeTypeIsInfarct"]]) |
((.data[["S2Thrombolysis"]] == "NB") &
bitwAnd(.data[["S2ThrombolysisNoBut"]],
ssnapinterface::tpa_no_but["Refusal"])) |
((.data[["S2Thrombolysis"]] == "NB") &
bitwAnd(.data[["S2ThrombolysisNoBut"]],
ssnapinterface::tpa_no_but["Medication"])) |
.data[["S2IAI"]]
),
numerators = rlang::expr(
!! ssnap_field[["ClockStartToThrombolysisMins"]] <= 60),
new_numerators = rlang::expr(
!! ssnap_field[["ClockStartToThrombolysisMins"]] <= 60),
csv_columns = c("S1PatientClockStartDateTime",
"S1OnsetInHospital",
"S1OnsetDateIsPrecise",
"S1OnsetTimeIsPrecise",
"S1OnsetDateTime",
"S2StrokeTypeIsInfarct",
"S2ThrombolysisDateTime",
"S2Thrombolysis"),
measure_type = "discrete")
)
md0u80c9/SSNAPStats documentation built on Feb. 11, 2020, 11:43 a.m.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
#' Define available auditing measures
#'
#' These functions provide a list of all the available auditing
#' measures. The master list is retrieved using \code{ssnap_measures}
#' which is an amalgamation of all lists; lists of measures intended
#' for a particular cohort group are stored using the other functions
#' for code legibility and/or ease of access if you know you only
#' need a subset of the measures.
#' @importFrom rlang ":="
#' @importFrom rlang "!!"
#' @export
ssnap_measures <- list(
# * Casemix ---------------------------------------------------------
# * -----------------------------------------------------------------
# Gender ==========================================================
# F3.1-5 Proportions of men and women.
Gender = audit_measure(
stem_name = "Gender",
description = "Gender",
exclusions = NULL,
numerators = list(
"Male" = rlang::expr(.data[["S1IsMale"]]),
"Female" = rlang::expr(!.data[["S1IsMale"]])),
numerator_descriptors = list(
"Male" = "Male",
"Female" = "Female"),
new_numerators = tibble::tribble(
~numerator, ~fun, ~descriptor,
"Male",
rlang::expr(.data[["S1IsMale"]]),
"Male",
"Female",
rlang::expr(!.data[["S1IsMale"]]),
"Female"
),
csv_columns = "S1IsMale",
measure_type = "discrete"),
# AgeOnArrival ====================================================
# F4.1-3 Age distribution
# G1.3, H1.3 Median age.
AgeOnArrival = audit_measure(
stem_name = "AgeOnArrival",
description = "Age on arrival",
exclusions = NULL,
numerators = rlang::expr(.data[["S1AgeOnArrival"]]),
new_numerators = rlang::expr(.data[["S1AgeOnArrival"]]),
csv_columns = "S1AgeOnArrival",
measure_type = "continuous"),
# AgeOver80 =======================================================
# F4.4-6 Proportion aged > 80
AgeOver80 = audit_measure(
stem_name = "AgeOver80",
description = "Age over 80",
exclusions = NULL,
numerators = rlang::expr(.data[["S1AgeOnArrival"]] > 80),
new_numerators = rlang::expr(.data[["S1AgeOnArrival"]] > 80),
csv_columns = "S1AgeOnArrival",
measure_type = "discrete"),
#TODO Conditional medians for age distribution of men and women
# F4.7-4.9 Female age distribution
# F4.10-4.12 Male age distribution
# FemaleAgeOver80 =================================================
# F4.13-15 Females aged over 80
FemaleAgeOver80 = audit_measure(
stem_name = "FemaleAgeOver80",
description = "Women aged over 80",
exclusions = rlang::expr(!.data[["S1IsMale"]]),
numerators = rlang::expr(.data[["S1AgeOnArrival"]] > 80),
new_numerators = rlang::expr(.data[["S1AgeOnArrival"]] > 80),
csv_columns = c("S1AgeOnArrival", "S1IsMale"),
measure_type = "continuous"),
# MaleAgeOver80 ===================================================
# F4.16-18 Males aged over 80
MaleAgeOver80 = audit_measure(
stem_name = "MaleAgeOver80",
description = "Men aged over 80",
exclusions = rlang::expr(!.data[["S1IsMale"]]),
numerators = rlang::expr(.data[["S1AgeOnArrival"]] > 80),
new_numerators = rlang::expr(.data[["S1AgeOnArrival"]] > 80),
csv_columns = c("S1AgeOnArrival", "S1IsMale"),
measure_type = "continuous"),
# AgeOnArrivalGrouped =============================================
# F4.19-29 Age breakdown
AgeOnArrivalGrouped = audit_measure(
stem_name = "AgeOnArrivalGrouped",
description = "Age on arrival (grouped)",
exclusions = NULL,
numerators = rlang::exprs(
"LessThan60" = .data[["S1AgeOnArrival"]] < 60,
"60To69" = dplyr::between(.data[["S1AgeOnArrival"]], 60, 69),
"70To79" = dplyr::between(.data[["S1AgeOnArrival"]], 70, 79),
"80To89" = dplyr::between(.data[["S1AgeOnArrival"]], 80, 89),
"90OrMore" = .data[["S1AgeOnArrival"]] >= 90),
numerator_descriptors = list(
"LessThan60" = "Age less than 60",
"60To69" = "Age 60-69",
"70To79" = "Age 70-79",
"80To89" = "Age 80-89",
"90OrMore" = "Age 90+"),
new_numerators = tibble::tribble(
~numerator, ~fun, ~descriptor,
"LessThan60",
rlang::expr(.data[["S1AgeOnArrival"]] < 60),
"Age less than 60",
"60To69",
rlang::expr(dplyr::between(.data[["S1AgeOnArrival"]], 60, 69)),
"Age 60-69",
"70To79",
rlang::expr(dplyr::between(.data[["S1AgeOnArrival"]], 70, 79)),
"Age 70-79",
"80To89",
rlang::expr(dplyr::between(.data[["S1AgeOnArrival"]], 80, 89)),
"Age 80-89",
"90OrMore",
rlang::expr(.data[["S1AgeOnArrival"]] >= 90),
"Age 90+"),
csv_columns = "S1AgeOnArrival",
measure_type = "discrete"),
# EthnicityKnown ==================================================
# C6.1-6.3 Ethnicity known
EthnicityKnown = audit_measure(
stem_name = "EthnicityKnown",
description = "Ethnicity known",
exclusions = NULL,
numerators = rlang::expr(.data[["S1Ethnicity"]] != "Unknown"),
new_numerators = rlang::expr(.data[["S1Ethnicity"]] != "Unknown"),
csv_columns = "S1Ethnicity",
measure_type = "discrete"),
# * -----------------------------------------------------------------
# * Record creation -------------------------------------------------
ClockStartToRecordCreationHours = audit_measure(
stem_name = "ClockStartToRecordCreationHours",
description = "Clock start to record creation (hours)",
exclusions = NULL,
numerators = ssnap_field[["ClockStartToRecordCreationHours"]],
new_numerators = rlang::expr(ssnap_field[["ClockStartToRecordCreationHours"]]),
csv_columns = c("S1PatientClockStartDateTime", "CreatedDateTime"),
measure_type = "continuous"),
# * -----------------------------------------------------------------
# * Comorbidities ---------------------------------------------------
# * -----------------------------------------------------------------
# ComorbidityCount ================================================
# F5.1-5.13 Comorbidities
ComorbidityCount = audit_measure(
stem_name = "ComorbidityCount",
description = "Comorbidity count",
exclusions = NULL,
numerators = rlang::exprs(
"0" = !! ssnap_field[["Comorbidities"]] == 0,
"1" = !! ssnap_field[["Comorbidities"]] == 1,
"2" = !! ssnap_field[["Comorbidities"]] == 2,
"3" = !! ssnap_field[["Comorbidities"]] == 3,
"4" = !! ssnap_field[["Comorbidities"]] == 4,
"5" = !! ssnap_field[["Comorbidities"]] == 5),
numerator_descriptors = list(
"0" = "0 comorbidities",
"1" = "1 comorbidity",
"2" = "2 comorbidities",
"3" = "3 comorbidities",
"4" = "4 comorbidities",
"5" = "5 comorbidities"),
new_numerators = tibble::tribble(
~numerator, ~fun, ~descriptor,
"0",
rlang::expr(!! ssnap_field[["Comorbidities"]] == 0),
"0 comorbidities",
"1",
rlang::expr(!! ssnap_field[["Comorbidities"]] == 1),
"1 comorbidity",
"2",
rlang::expr(!! ssnap_field[["Comorbidities"]] == 2),
"2 comorbidities",
"3",
rlang::expr(!! ssnap_field[["Comorbidities"]] == 3),
"3 comorbidities",
"4",
rlang::expr(!! ssnap_field[["Comorbidities"]] == 4),
"4 comorbidities",
"5",
rlang::expr(!! ssnap_field[["Comorbidities"]] == 5),
"5 comorbidities"),
csv_columns = c("S2CoMCongestiveHeartFailure",
"S2CoMHypertension",
"S2CoMAtrialFibrillation",
"S2CoMDiabetes",
"S2CoMStrokeTIA"),
measure_type = "discrete"),
# CongestiveHeartFailure ==========================================
# F5.14-16 CHF before stroke
CongestiveHeartFailure = audit_measure(
stem_name = "CongestiveHeartFailure",
description = "Congestive heart failure",
exclusions = NULL,
numerators = rlang::expr(.data[["S2CoMCongestiveHeartFailure"]]),
new_numerators = rlang::expr(.data[["S2CoMCongestiveHeartFailure"]]),
csv_columns = "S2CoMCongestiveHeartFailure",
measure_type = "discrete"),
# Hypertension ====================================================
# F5.17-19 Hypertension before stroke
Hypertension = audit_measure(
stem_name = "Hypertension",
description = "Hypertension",
exclusions = NULL,
numerators = rlang::expr(.data[["S2CoMHypertension"]]),
new_numerators = rlang::expr(.data[["S2CoMHypertension"]]),
csv_columns = "S2CoMHypertension",
measure_type = "discrete"),
# Diabetes ========================================================
# F5.20-22 Diabetes before stroke
Diabetes = audit_measure(
stem_name = "Diabetes",
description = "Diabetes",
exclusions = NULL,
numerators = rlang::expr(.data[["S2CoMDiabetes"]]),
new_numerators = rlang::expr(.data[["S2CoMDiabetes"]]),
csv_columns = "S2CoMDiabetes",
measure_type = "discrete"),
# PreviousStrokeTIA ===============================================
# F5.23-25 Stroke or TIA before stroke
PreviousStrokeTIA = audit_measure(
stem_name = "PreviousStrokeTIA",
description = "Previous stroke or TIA",
exclusions = NULL,
numerators = rlang::expr(.data[["S2CoMStrokeTIA"]]),
new_numerators = rlang::expr(.data[["S2CoMStrokeTIA"]]),
csv_columns = "S2CoMStrokeTIA",
measure_type = "discrete"),
# * -----------------------------------------------------------------
# * Atrial fibrillation ---------------------------------------------
# * -----------------------------------------------------------------
# AtrialFibrillation ==============================================
# F6.1-3 Atrial fibrillation (AF) before stroke
AtrialFibrillation = audit_measure(
stem_name = "AtrialFibrillation",
description = "Previously known atrial fibrillation",
exclusions = NULL,
numerators = rlang::expr(.data[["S2CoMAtrialFibrillation"]]),
new_numerators = rlang::expr(.data[["S2CoMAtrialFibrillation"]]),
csv_columns = "S2CoMAtrialFibrillation",
measure_type = "discrete"),
# AFOnAntiplatelet ================================================
# F6.4-10 Atrial fibrillation (AF) before stroke
AFOnAntiplatelet = audit_measure(
stem_name = "AFOnAntiplatelet",
description = "Previous atrial fibrillation on antiplatelets",
exclusions = NULL,
numerators = rlang::exprs(
"Yes" = .data[["S2CoMAFAntiplatelet"]] == "Y",
"No" = .data[["S2CoMAFAntiplatelet"]] == "N",
"NoBut" = .data[["S2CoMAFAntiplatelet"]] == "NB"),
numerator_descriptors = list("Yes", "No", "No but"),
new_numerators = tibble::tribble(
~numerator, ~fun, ~descriptor,
"Yes",
rlang::expr(.data[["S2CoMAFAntiplatelet"]] == "Y"),
"Yes",
"No",
rlang::expr(.data[["S2CoMAFAntiplatelet"]] == "N"),
"No",
"NoBut",
rlang::expr(.data[["S2CoMAFAntiplatelet"]] == "NB"),
"No but"),
csv_columns = "S2CoMAFAntiplatelet",
measure_type = "discrete"),
# AFOnAnticoagulant ===============================================
# F6.11-17 Atrial fibrillation (AF) before stroke
AFOnAnticoagulant = audit_measure(
stem_name = "AFOnAnticoagulant",
description = "Previous atrial fibrillation on anticoagulants",
exclusions = NULL,
numerators = rlang::exprs(
"Yes" = .data[["S2CoMAFAnticoagulent"]] == "Y",
"No" = .data[["S2CoMAFAnticoagulent"]] == "N",
"NoBut" = .data[["S2CoMAFAnticoagulent"]] == "NB"),
numerator_descriptors = list("Yes", "No", "No but"),
new_numerators = tibble::tribble(
~numerator, ~fun, ~descriptor,
"Yes",
rlang::expr(.data[["S2CoMAFAnticoagulent"]] == "Y"),
"Yes",
"No",
rlang::expr(.data[["S2CoMAFAnticoagulent"]] == "N"),
"No",
"NoBut",
rlang::expr(.data[["S2CoMAFAnticoagulent"]] == "NB"),
"No but"),
csv_columns = "S2CoMAFAnticoagulent",
measure_type = "discrete"),
# AFMeds ==========================================================
# F6.18-26 Atrial fibrillation (AF) before stroke
AFMeds = audit_measure(
stem_name = "AFMeds",
description = "Atrial fibrillation medication",
exclusions = NULL,
numerators = rlang::exprs(
"Both" = (.data[["S2CoMAFAnticoagulent"]] == "Y")
& (.data[["S2CoMAFAntiplatelet"]] == "Y"),
"Anticoagulant" = (.data[["S2CoMAFAnticoagulent"]] == "Y")
& (.data[["S2CoMAFAntiplatelet"]] != "Y"),
"Antiplatelet" = (.data[["S2CoMAFAnticoagulent"]] != "Y")
& (.data[["S2CoMAFAntiplatelet"]] == "Y"),
"None" = (.data[["S2CoMAFAnticoagulent"]] != "Y")
& (.data[["S2CoMAFAntiplatelet"]] != "Y")),
numerator_descriptors = list(
"Both" = "Both anticoagulant and antiplatelet medication",
"Anticoagulant" = "Anticoagulant medication only",
"Antiplatelet" = "Antiplatelet medication only",
"None" = "Neither medication"),
new_numerators = tibble::tribble(
~numerator, ~fun, ~descriptor,
"Both",
rlang::expr((.data[["S2CoMAFAnticoagulent"]] == "Y")
& (.data[["S2CoMAFAntiplatelet"]] == "Y")),
"Both anticoagulant and antiplatelet medication",
"Anticoagulant",
rlang::expr((.data[["S2CoMAFAnticoagulent"]] == "Y")
& (.data[["S2CoMAFAntiplatelet"]] != "Y")),
"Anticoagulant medication only",
"Antiplatelet",
rlang::expr((.data[["S2CoMAFAnticoagulent"]] != "Y")
& (.data[["S2CoMAFAntiplatelet"]] == "Y")),
"Antiplatelet medication only",
"None",
rlang::expr((.data[["S2CoMAFAnticoagulent"]] != "Y")
& (.data[["S2CoMAFAntiplatelet"]] != "Y")),
"Neither medication"),
csv_columns = c("S2CoMAFAnticoagulent", "S2CoMAFAntiplatelet"),
measure_type = "discrete"),
# * -----------------------------------------------------------------
# * StrokeType ------------------------------------------------------
# * -----------------------------------------------------------------
# F7.1-7 Stroke type
# G1.9-10 Infarction / PIH
# H1.9-10 Infarction / PIH
StrokeType = audit_measure(
stem_name = "StrokeType",
description = "Stroke type",
exclusions = NULL,
numerators = rlang::exprs(
"Infarct" = .data[["S2StrokeTypeIsInfarct"]],
"PIH" = !.data[["S2StrokeTypeIsInfarct"]]),
numerator_descriptors = list(
"Infarct" = "Infarction",
"PIH" = "Primary intracerebral haemorrhage"),
new_numerators = tibble::tribble(
~numerator, ~fun, ~descriptor,
"Infarct",
rlang::expr(.data[["S2StrokeTypeIsInfarct"]]),
"Infarction",
"PIH",
rlang::expr(!.data[["S2StrokeTypeIsInfarct"]]),
"Primary intracerebral haemorrhage"
),
csv_columns = "S2StrokeTypeIsInfarct",
measure_type = "discrete"),
# * Modified Rankin Score -------------------------------------------
# * -----------------------------------------------------------------
# F8.1-13 mRS before stroke
RankinBeforeStroke = audit_measure(
stem_name = "RankinBeforeStroke",
description = "Pre-stroke Rankin score",
exclusions = NULL,
numerators = rlang::exprs(
"0" = .data[["S2RankinBeforeStroke"]] == 0,
"1" = .data[["S2RankinBeforeStroke"]] == 1,
"2" = .data[["S2RankinBeforeStroke"]] == 2,
"3" = .data[["S2RankinBeforeStroke"]] == 3,
"4" = .data[["S2RankinBeforeStroke"]] == 4,
"5" = .data[["S2RankinBeforeStroke"]] == 5),
numerator_descriptors = list(
"0" = "0", "1" = "1", "2" = "2", "3" = "3",
"4" = "4", "5" = "5"),
new_numerators = tibble::tribble(
~numerator, ~fun, ~descriptor,
"0",
rlang::expr(.data[["S2RankinBeforeStroke"]] == 0),
"0",
"1",
rlang::expr(.data[["S2RankinBeforeStroke"]] == 1),
"1",
"2",
rlang::expr(.data[["S2RankinBeforeStroke"]] == 2),
"2",
"3",
rlang::expr(.data[["S2RankinBeforeStroke"]] == 3),
"3",
"4",
rlang::expr(.data[["S2RankinBeforeStroke"]] == 4),
"4",
"5",
rlang::expr(.data[["S2RankinBeforeStroke"]] == 5),
"5"),
csv_columns = "S2RankinBeforeStroke",
measure_type = "discrete"),
# * Modified Rankin Score Grouped -----------------------------------
# * -----------------------------------------------------------------
# G1.11-13 mRS grouping before stroke
# H1.11-13 mRS grouping before stroke
RankinBeforeStrokeGrouped = audit_measure(
stem_name = "RankinBeforeStrokeGrouped",
description = "Pre-stroke Rankin score",
exclusions = NULL,
numerators = rlang::exprs(
"0" = .data[["S2RankinBeforeStroke"]] == 0,
"1Or2" = (.data[["S2RankinBeforeStroke"]] == 1) |
(.data[["S2RankinBeforeStroke"]] == 2),
"3OrMore" = .data[["S2RankinBeforeStroke"]] > 2),
numerator_descriptors = list(
"0" = "Modified Rankin Scale (mRS) score before stroke: 0",
"1Or2" =
"Modified Rankin Scale (mRS) score before stroke: 1 or 2",
"3OrMore" =
"Modified Rankin Scale (mRS) score before stroke: 3, 4 or 5"),
new_numerators = tibble::tribble(
~numerator, ~fun, ~descriptor,
"0",
rlang::expr(.data[["S2RankinBeforeStroke"]] == 0),
"Modified Rankin Scale (mRS) score before stroke: 0",
"1Or2",
rlang::expr((.data[["S2RankinBeforeStroke"]] == 1) |
(.data[["S2RankinBeforeStroke"]] == 2)),
"Modified Rankin Scale (mRS) score before stroke: 1 or 2",
"3OrMore",
rlang::expr(.data[["S2RankinBeforeStroke"]] > 2),
"Modified Rankin Scale (mRS) score before stroke: 3, 4 or 5"),
csv_columns = "S2RankinBeforeStroke",
measure_type = "discrete"),
# * NIHSS -----------------------------------------------------------
# * -----------------------------------------------------------------
# LOCArrival ======================================================
# F9.1-9 NIHSS Level of consciousness at arrival
# Expressed as discrete values (ie. broken down by value)
LOCArrival = audit_measure(
stem_name = "LOCArrival",
description = "Level of consciousness on arrival",
exclusions = NULL,
numerators = rlang::exprs(
"0" = .data[["S2NihssArrivalLoc"]] == 0,
"1" = .data[["S2NihssArrivalLoc"]] == 1,
"2" = .data[["S2NihssArrivalLoc"]] == 2,
"3" = .data[["S2NihssArrivalLoc"]] == 3),
numerator_descriptors = list(
"0" = "0", "1" = "1", "2" = "2", "3" = "3"),
new_numerators = tibble::tribble(
~numerator, ~fun, ~descriptor,
"0", rlang::expr(.data[["S2NihssArrivalLoc"]] == 0), "0",
"1", rlang::expr(.data[["S2NihssArrivalLoc"]] == 1), "1",
"2", rlang::expr(.data[["S2NihssArrivalLoc"]] == 2), "2",
"3", rlang::expr(.data[["S2NihssArrivalLoc"]] == 3), "3"),
csv_columns = "S2NihssArrivalLoc",
measure_type = "discrete"),
# LOCArrivalGrouped ===============================================
# G1.14-16 LOC at arrival
# H1.14-16 LOC at arrival
LOCArrivalGrouped = audit_measure(
stem_name = "LOCArrivalGrouped",
description = "Level of consciousness on arrival",
exclusions = NULL,
numerators = rlang::exprs(
"0" = .data[["S2NihssArrivalLoc"]] == 0,
"1Or2" = (.data[["S2NihssArrivalLoc"]] == 1) |
(.data[["S2NihssArrivalLoc"]] == 2),
"3" = .data[["S2NihssArrivalLoc"]] == 3),
numerator_descriptors = list(
"0" = "Alert upon arrival",
"1Or2" = "Responds to voice or pain on arrival",
"3" = "Unresponsive on arrival"),
new_numerators = tibble::tribble(
~numerator, ~fun, ~descriptor,
"0",
rlang::expr(.data[["S2NihssArrivalLoc"]] == 0),
"Alert upon arrival",
"1Or2",
rlang::expr((.data[["S2NihssArrivalLoc"]] == 1) |
(.data[["S2NihssArrivalLoc"]] == 2)),
"Responds to voice or pain on arrival",
"3",
rlang::expr(.data[["S2NihssArrivalLoc"]] == 3),
"Unresponsive on arrival"),
csv_columns = "S2NihssArrivalLoc",
measure_type = "discrete"),
# WorstLOCFirst7Days ==============================================
# K4.1-9 Worst LOC in first 7 days
WorstLOCFirst7Days = audit_measure(
stem_name = "WorstLOCFirst7Days",
description = "Worst level of consciousness in the first 7 days from clock start",
exclusions = NULL,
numerators = rlang::exprs(
"0" = .data[["S5LocWorst7Days"]] == 0,
"1" = .data[["S5LocWorst7Days"]] == 1,
"2" = .data[["S5LocWorst7Days"]] == 2,
"3" = .data[["S5LocWorst7Days"]] == 3),
numerator_descriptors = list(
"0" = "Alert upon arrival",
"1" = "Responds to voice",
"2" = "Responds to pain",
"3" = "Unresponsive on arrival"),
new_numerators = tibble::tribble(
~numerator, ~fun, ~descriptor,
"0",
rlang::expr(.data[["S5LocWorst7Days"]] == 0),
"Alert upon arrival",
"1",
rlang::expr(.data[["S5LocWorst7Days"]] == 1),
"Responds to voice",
"2",
rlang::expr(.data[["S5LocWorst7Days"]] == 2),
"Responds to pain",
"3",
rlang::expr(.data[["S5LocWorst7Days"]] == 3),
"Unresponsive on arrival"),
csv_columns = "S5LocWorst7Days",
measure_type = "discrete"),
# NihssCompletion =================================================
# F9.10-16 Completeness of NIHSS score
NihssCompletion = audit_measure(
stem_name = "NihssCompletion",
description = "Completion of NIHSS score",
exclusions = NULL,
numerators = rlang::exprs(
"LOCOnly" = !!ssnap_field[["NihssComponentsComplete"]] == 1,
"Incomplete" = dplyr::between(
!!ssnap_field[["NihssComponentsComplete"]], 2, 14),
"Complete" = !!ssnap_field[["NihssComponentsComplete"]] == 15),
numerator_descriptors = list(
"LOCOnly" = "Level of consciousness (AVPU) only",
"Incomplete" = "Incomplete",
"Complete" = "Complete"),
new_numerators = tibble::tribble(
~numerator, ~fun, ~descriptor,
"LOCOnly",
rlang::expr(!!ssnap_field[["NihssComponentsComplete"]] == 1),
"Level of consciousness (AVPU) only",
"Incomplete",
rlang::expr(dplyr::between(
!!ssnap_field[["NihssComponentsComplete"]], 2, 14)),
"Incomplete",
"Complete",
rlang::expr(!!ssnap_field[["NihssComponentsComplete"]] == 15),
"Complete"),
csv_columns = c("S2NihssArrivalLoc",
"S2NihssArrivalLocQuestions",
"S2NihssArrivalLocCommands",
"S2NihssArrivalBestGaze",
"S2NihssArrivalVisual",
"S2NihssArrivalFacialPalsy",
"S2NihssArrivalMotorArmLeft",
"S2NihssArrivalMotorArmRight",
"S2NihssArrivalMotorLegLeft",
"S2NihssArrivalMotorLegRight",
"S2NihssArrivalLimbAtaxia",
"S2NihssArrivalSensory",
"S2NihssArrivalBestLanguage",
"S2NihssArrivalDysarthria",
"S2NihssArrivalExtinctionInattention"),
measure_type = "discrete"),
# NihssOnArrival ==================================================
# F9.28-30 NIHSS spread
# G1.17 Median NIHSS on arrival
# H1.17 Median NIHSS on arrival
NihssOnArrival = audit_measure(
stem_name = "NihssOnArrival",
description = "NIHSS score on arrival",
exclusions = NULL,
numerators = rlang::expr(.data[["S2NihssArrival"]]),
new_numerators = rlang::expr(.data[["S2NihssArrival"]]),
csv_columns = "S2NihssArrival",
# numerator_descriptors = list(
# "NIHSS at arrival if fully completed"),
measure_type = "continuous"),
# NihssOnArrivalGrouped ===========================================
# F9.17-27 NIHSS at arrival
NihssOnArrivalGrouped = audit_measure(
stem_name = "NihssOnArrivalGrouped",
description = "NIHSS score on arrival",
exclusions = NULL,
numerators = rlang::exprs(
"0" = .data[["S2NihssArrival"]] == 0,
"1To4" = dplyr::between(.data[["S2NihssArrival"]], 1, 4),
"5To15" = dplyr::between(.data[["S2NihssArrival"]], 5, 15),
"16To20" = dplyr::between(.data[["S2NihssArrival"]], 16, 20),
"21OrMore" = .data[["S2NihssArrival"]] >= 21),
numerator_descriptors = list(
"0" = "0",
"1To4" = "1 - 4",
"5To15" = "5 - 15",
"16To20" = "16 - 20",
"21OrMore" = "21 or more"),
new_numerators = tibble::tribble(
~numerator, ~fun, ~descriptor,
"0",
rlang::expr(.data[["S2NihssArrival"]] == 0),
"0",
"1To4",
rlang::expr(dplyr::between(.data[["S2NihssArrival"]], 1, 4)),
"1 - 4",
"5To15",
rlang::expr(dplyr::between(.data[["S2NihssArrival"]], 5, 15)),
"5 - 15",
"16To20",
rlang::expr(dplyr::between(.data[["S2NihssArrival"]], 16, 20)),
"16 - 20",
"21OrMore",
rlang::expr(.data[["S2NihssArrival"]] >= 21),
"21 or more"),
csv_columns = "S2NihssArrival",
measure_type = "discrete"),
# TODO NIHSS LOC if NIHSS incomplete
# * -----------------------------------------------------------------
# * Palliative Care -------------------------------------------------
# * -----------------------------------------------------------------
# EndOfLifeWithin72hrs ============================================
# F10.1-3 Palliative care in 72hrs
# G1.18 Palliative care in 72hrs
# H1.18 Palliative care in 72hrs
EndOfLifeWithin72hrs = audit_measure(
stem_name = "EndOfLifeWithin72hrs",
description = "End of life care within 72hrs",
exclusions = NULL,
numerators = rlang::expr(!is.na(
.data[["S3PalliativeCareDecisionDate"]])),
new_numerators = rlang::expr(!is.na(
.data[["S3PalliativeCareDecisionDate"]])),
csv_columns = "S3PalliativeCareDecisionDate",
measure_type = "discrete"),
# EndOfLifePathway ================================================
# F10.4-6 End of life pathway use
EndOfLifePathway = audit_measure(
stem_name = "EndOfLifePathway",
description = "Is the patient on an end of life pathway",
exclusions = rlang::expr(is.na(
.data[["S3PalliativeCareDecisionDate"]])),
numerators = rlang::expr(!is.na(
.data[["S3EndOfLifePathway"]])),
new_numerators =
rlang::expr(!is.na(.data[["S3EndOfLifePathway"]])),
csv_columns = c("S3EndOfLifePathway",
"S3PalliativeCareDecisionDate"),
measure_type = "discrete"),
# ClockStartToPalliativeCare72Hours ===============================
# F10.7 Clock start to palliative care decision (days) spread
ClockStartToPalliativeCare72Hours = audit_measure(
stem_name = "ClockStartToPalliativeCare72Hours",
description = "Is the patient on an end of life pathway",
exclusions = NULL,
numerators = ssnap_field[["ClockStartToPalliativeCare72Days"]],
new_numerators =
ssnap_field[["ClockStartToPalliativeCare72Days"]],
csv_columns = c("S1PatientClockStartDateTime",
"S3PalliativeCareDecisionDate"),
measure_type = "continuous"),
# * -----------------------------------------------------------------
# * In hospital stroke ----------------------------------------------
# * -----------------------------------------------------------------
# F11.1-3 Was the stroke in hospital?
OnsetInHospital = audit_measure(
stem_name = "OnsetInHospital",
description = "Onset in hospital",
exclusions = NULL,
numerators = rlang::expr(!is.na(.data[["S1OnsetInHospital"]])),
new_numerators =
rlang::expr(!is.na(.data[["S1OnsetInHospital"]])),
csv_columns = "S1OnsetInHospital",
measure_type = "discrete"),
# * Onset of symptoms -----------------------------------------------
# * -----------------------------------------------------------------
# OnsetDateAccuracy ===============================================
# G2.1-2.7 Date of symptom onset
# H2.1-2.7 Date of symptom onset
OnsetDateAccuracy = audit_measure(
stem_name = "OnsetDate",
description = "Accuracy of onset date",
exclusions = NULL,
numerators = rlang::exprs(
"Precise" = .data[["S1OnsetDateIsPrecise"]],
"Estimate" = !.data[["S1OnsetDateIsPrecise"]],
"DuringSleep" = is.na(.data[["S1OnsetDateIsPrecise"]])),
new_numerators = tibble::tribble(
~numerator, ~fun, ~descriptor,
"Precise",
rlang::expr(.data[["S1OnsetDateIsPrecise"]]),
"Precise",
"Estimate",
rlang::expr(!.data[["S1OnsetDateIsPrecise"]]),
"Best estimate",
"DuringSleep",
rlang::expr(is.na(.data[["S1OnsetDateIsPrecise"]])),
"During sleep"),
csv_columns = "S1OnsetDateIsPrecise",
measure_type = "discrete"),
# OnsetTimeAccuracy ===============================================
# G2.8-14 Time of symptom onset
# H2.8-14 Time of symptom onset
OnsetTimeAccuracy = audit_measure(
stem_name = "OnsetTime",
description = "Accuracy of onset time",
exclusions = NULL,
numerators = rlang::exprs(
"Precise" = .data[["S1OnsetTimeIsPrecise"]],
"Estimate" = !.data[["S1OnsetTimeIsPrecise"]],
"DuringSleep" = is.na(.data[["S1OnsetTimeIsPrecise"]])),
new_numerators = tibble::tribble(
~numerator, ~fun, ~descriptor,
"Precise",
rlang::expr(.data[["S1OnsetTimeIsPrecise"]]),
"Precise",
"Estimate",
rlang::expr(!.data[["S1OnsetTimeIsPrecise"]]),
"Best estimate",
"DuringSleep",
rlang::expr(is.na(.data[["S1OnsetTimeIsPrecise"]])),
"During sleep"),
csv_columns = "S1OnsetTimeIsPrecise",
measure_type = "discrete"),
# OnsetTimeKnown ==================================================
# G2.15-17 Time of symptom onset known
# H2.15-17 Time of symptom onset known
OnsetTimeKnown = audit_measure(
stem_name = "OnsetTimeKnown",
description = "Onset time is known",
exclusions = NULL,
numerators = rlang::expr(!is.na(.data[["S1OnsetTimeIsPrecise"]])),
new_numerators =
rlang::expr(!is.na(.data[["S1OnsetTimeIsPrecise"]])),
csv_columns = "S1OnsetTimeIsPrecise",
measure_type = "discrete"),
# OnsetToArrivalGrouped ===========================================
# H2.18-28 Onset to arrival times (grouped)
OnsetToArrivalGrouped = audit_measure(
stem_name = "OnsetToArrival",
description = "Onset to arrival",
exclusions = NULL,
numerators = rlang::exprs(
"Within4hrs" = !!ssnap_field[["OnsetToArrivalTimeMins"]]
<= (4 * 60),
"4To12hrs" = dplyr::between(
!!ssnap_field[["OnsetToArrivalTimeMins"]],
(4 * 60), (12 * 60)),
"12To24hrs" = dplyr::between(
!!ssnap_field[["OnsetToArrivalTimeMins"]],
(12 * 60), (24 * 60)),
"24To72hrs" = dplyr::between(
!!ssnap_field[["OnsetToArrivalTimeMins"]],
(24 * 60), (72 * 60)),
"Over72hrs" = !!ssnap_field[["OnsetToArrivalTimeMins"]]
> (72 * 60)),
new_numerators = tibble::tribble(
~numerator, ~fun, ~descriptor,
"Within4hrs",
rlang::expr(
!!ssnap_field[["OnsetToArrivalTimeMins"]] <= (4 * 60)),
"Within 4 hours",
"4To12hrs",
rlang::expr(dplyr::between(
!!ssnap_field[["OnsetToArrivalTimeMins"]],
(4 * 60), (12 * 60))),
"4 to 12 hours",
"12To24hrs",
rlang::expr(dplyr::between(
!!ssnap_field[["OnsetToArrivalTimeMins"]],
(12 * 60), (24 * 60))),
"12 to 24 hours",
"24To72hrs",
rlang::expr(dplyr::between(
!!ssnap_field[["OnsetToArrivalTimeMins"]],
(24 * 60), (72 * 60))),
"24 to 72 hours",
"Over72hrs",
rlang::expr(
!!ssnap_field[["OnsetToArrivalTimeMins"]] > (72 * 60)),
"Over 72 hours"),
csv_columns = c("S1OnsetInHospital",
"S1OnsetDateIsPrecise",
"S1OnsetTimeIsPrecise",
"S1OnsetDateTime",
"S1PatientClockStartDateTime"),
measure_type = "discrete"),
# OnsetToArrivalTimeMins ==========================================
OnsetToArrivalTimeMins = audit_measure(
stem_name = "OnsetToArrivalMins",
description = "Onset to arrival",
exclusions = NULL,
numerators = ssnap_field[["OnsetToArrivalTimeMins"]],
new_numerators = ssnap_field[["OnsetToArrivalTimeMins"]],
csv_columns = c("S1OnsetInHospital",
"S1OnsetDateIsPrecise",
"S1OnsetTimeIsPrecise",
"S1OnsetDateTime",
"S1PatientClockStartDateTime"),
measure_type = "continuous"),
# OnsetToFirstStrokeUnitMins ======================================
OnsetToFirstStrokeUnitMins = audit_measure(
stem_name = "OnsetToFirstStrokeUnitMins",
description = "Onset to first stroke unit",
exclusions = NULL,
numerators = ssnap_field[["OnsetToFirstStrokeUnitMins"]],
new_numerators = ssnap_field[["OnsetToFirstStrokeUnitMins"]],
csv_columns = c("S1OnsetDateTime",
"S1FirstStrokeUnitArrivalDateTime"),
measure_type = "continuous"),
# OnsetToBrainImagingMins =========================================
OnsetToBrainImagingMins = audit_measure(
stem_name = "OnsetToBrainImagingMins",
description = "Onset to brain imaging",
exclusions = NULL,
numerators = ssnap_field[["OnsetToBrainImagingMins"]],
new_numerators = ssnap_field[["OnsetToBrainImagingMins"]],
csv_columns = c("S1OnsetDateTime",
"S2BrainImagingDateTime"),
measure_type = "continuous"),
# OnsetToThrombolysisMins =========================================
OnsetToThrombolysisMins = audit_measure(
stem_name = "OnsetToThrombolysisMins",
description = "Onset to thrombolysis",
exclusions = NULL,
numerators = ssnap_field[["OnsetToThrombolysisMins"]],
new_numerators = ssnap_field[["OnsetToThrombolysisMins"]],
csv_columns = c("S1OnsetDateTime",
"S2ThrombolysisDateTime"),
measure_type = "continuous"),
# * -----------------------------------------------------------------
# * Ambulance -------------------------------------------------------
# * -----------------------------------------------------------------
ArrivalByAmbulance = audit_measure(
stem_name = "ArrivalByAmbulance",
description = "Arrival by ambulance",
exclusions = rlang::expr(.data[["S1OnsetInHospital"]]),
numerators = rlang::expr(.data[["S1ArriveByAmbulance"]]),
new_numerators = rlang::expr(.data[["S1ArriveByAmbulance"]]),
csv_columns = c("S1ArriveByAmbulance",
"S1OnsetInHospital"),
measure_type = "discrete"),
# * Time and day of arrival -----------------------------------------
# * -----------------------------------------------------------------
#TODO Time and day of arrival needs first arrival breaking down to
# In hours, out of hours, weekends and bank holidays
# TODO DayTypeOfArrival needs to also include bank holidays.
# Output also should be a factor rather than character
#DayTypeOfArrival = dplyr::case_when(
# .data[["S1OnsetInHospital"]] ~ NA_character_,
# lubridate::wday(.data[["S1FirstArrivalDateTime"]]) > 5 ~
# "Weekend",
# TRUE ~ "Weekday"),
#TimeRangeOfArrival = dplyr::case_when(
# .data[["S1OnsetInHospital"]] ~ NA_character_,
# dplyr::between(lubridate::hour(.data[["S1FirstArrivalDateTime"]]),
# 8, 18) ~ "In-hours",
# TRUE ~ "Out of hours"
#),
# * Scanning --------------------------------------------------------
# * -----------------------------------------------------------------
# ClockStartToBrainImagingMins ====================================
# G6.4-6 Clock start to first brain imaging
# H6.4-6 Clock start to first brain imaging
ClockStartToBrainImagingMins = audit_measure(
stem_name = "ClockStartToBrainImagingMins",
description = "Clock start to first brain imaging (mins)",
exclusions = NULL,
numerators = ssnap_field[["ClockStartToBrainImagingMins"]],
new_numerators = ssnap_field[["ClockStartToBrainImagingMins"]],
csv_columns = c("S1PatientClockStartDateTime",
"S2BrainImagingDateTime"),
measure_type = "continuous"),
# BrainImagingGrouped =============================================
# G6.1-3 Scanned
# H6.1-3 Scanned
# G6.7-9 Scanned within 1 hour of clock start
# H6.7-9 Scanned within 1 hour of clock start
# G6.10-12 Scanned within 12 hours of clock start
# H6.10-12 Scanned within 12 hours of clock start
# G6.13-15 Scanned within 24 hours of clock start
# H6.13-15 Scanned within 24 hours of clock start
BrainImagingGrouped = audit_measure(
stem_name = "BrainImaging",
description = "Brain imaging",
exclusions = NULL,
numerators = rlang::exprs(
"Scanned" = !is.na(
!! ssnap_field[["ClockStartToBrainImagingMins"]]),
"Within1hr" = !! ssnap_field[["ClockStartToBrainImagingMins"]]
<= 60,
"Within12hrs" = !! ssnap_field[["ClockStartToBrainImagingMins"]]
<= (60 * 12),
"Within24hrs" = !! ssnap_field[["ClockStartToBrainImagingMins"]]
<= (60 * 24)),
new_numerators = tibble::tribble(
~numerator, ~fun, ~descriptor,
"Scanned", rlang::expr(
!is.na(!! ssnap_field[["ClockStartToBrainImagingMins"]])),
"Scanned",
"Within1hr", rlang::expr(
!! ssnap_field[["ClockStartToBrainImagingMins"]] <= 60),
"Scanned within 1hr",
"Within12hrs", rlang::expr(
!! ssnap_field[["ClockStartToBrainImagingMins"]] <= (60 * 12)),
"Scanned within 12hrs",
"Within24hrs", rlang::expr(
!! ssnap_field[["ClockStartToBrainImagingMins"]] <= (60 * 24)),
"Scanned within 24hrs"),
csv_columns = c("S1PatientClockStartDateTime",
"S2BrainImagingDateTime"),
measure_type = "discrete"),
# * -----------------------------------------------------------------
# * Admission to stroke unit -----------------------------------------
# * -----------------------------------------------------------------
# WentToAStrokeUnit ===============================================
# G7.1-3 Patient went to a stroke unit (SU) at any point at the
# first admitting hospital
# H7.1-3 Patient went to a stroke unit (SU) at any point at the
# first admitting hospital
WentToAStrokeUnit = audit_measure(
stem_name = "WentToAStrokeUnit",
description = "Went to a stroke unit",
exclusions = NULL,
numerators = rlang::expr(!is.na(
!! ssnap_field[["ClockStartToFirstStrokeUnitMins"]])),
new_numerators = rlang::expr(!is.na(
!! ssnap_field[["ClockStartToFirstStrokeUnitMins"]])),
csv_columns = c("S1PatientClockStartDateTime",
"S1FirstStrokeUnitArrivalDateTime"),
measure_type = "discrete"),
# ClockStartToFirstStrokeUnitMins =================================
# G7.4-6 Clock start to first stroke unit admission (mins)
# H7.4-6 Clock start to first stroke unit admission (mins)
ClockStartToFirstStrokeUnitMins = audit_measure(
stem_name = "ClockStartToFirstStrokeUnitMins",
description = "Clock start to first stroke unit (mins)",
exclusions = NULL,
numerators = ssnap_field[["ClockStartToFirstStrokeUnitMins"]],
new_numerators =
ssnap_field[["ClockStartToFirstStrokeUnitMins"]],
csv_columns = c("S1PatientClockStartDateTime",
"S1FirstStrokeUnitArrivalDateTime"),
measure_type = "continuous"),
# FirstWard =======================================================
# G7.7-15 First ward of admission
# H7.7-15 First ward of admission
FirstWard = audit_measure(
stem_name = "FirstWard",
description = "First ward",
exclusions = NULL,
numerators = rlang::exprs(
"MAU_AAU_CDU" = (.data[["S1FirstWard"]] == "MAC"),
"StrokeUnit" = (.data[["S1FirstWard"]] == "SU"),
"ICU_CCU_HDU" = (.data[["S1FirstWard"]] == "ICH"),
"Other" = (.data[["S1FirstWard"]] == "O")),
new_numerators = tibble::tribble(
~numerator, ~fun, ~descriptor,
"MAU_AAU_CDU",
rlang::expr(.data[["S1FirstWard"]] == "MAC"),
"Admitted to an assessment area",
"StrokeUnit",
rlang::expr(.data[["S1FirstWard"]] == "SU"),
"Admitted to a stroke unit",
"ICU_CCU_HDU",
rlang::expr(.data[["S1FirstWard"]] == "ICH"),
"Admitted to a high dependency area (ICU, CCU, HDU)",
"Other",
rlang::expr(.data[["S1FirstWard"]] == "O"),
"Other"),
csv_columns = "S1FirstWard",
measure_type = "discrete"),
# FirstSUWithin4hrs ===============================================
# G 7.16.1-18.1 First stroke unit within 4 hours
# H 7.16.1-18.1 First stroke unit within 4 hours
FirstSUWithin4hrs = audit_measure(
stem_name = "FirstSUWithin4hrs",
description = "First stroke unit within 4 hours",
exclusions = rlang::expr( (.data[["S1FirstWard"]] == "ICH") |
(!is.na(.data[["S2IAI"]]) & .data[["S2IAI"]])),
numerators = rlang::expr(.data[["S1FirstWard"]] == "SU" &
(!! ssnap_field[["ClockStartToFirstStrokeUnitMins"]]
<= (4 * 60))),
new_numerators =
rlang::expr(.data[["S1FirstWard"]] == "SU" &
(!! ssnap_field[["ClockStartToFirstStrokeUnitMins"]]
<= (4 * 60))),
csv_columns = c("S1PatientClockStartDateTime",
"S1FirstStrokeUnitArrivalDateTime",
"S1FirstWard",
"S2IAI"),
measure_type = "discrete"),
# TODO Out of hours and SU within 4 hrs.
# * -----------------------------------------------------------------
# * Stroke nurse assessment -----------------------------------------
# * -----------------------------------------------------------------
# StrokeNurseReview ===============================================
# G 8.1-3 Stroke nurse within 24hrs
# H 8.1-3 Stroke nurse within 24hrs
# G 8.4-6 Stroke nurse within 72hrs
# H 8.4-6 Stroke nurse within 72hrs
# G 8.7-13 Stroke nurse review times grouped by time
# H 8.7-13 Stroke nurse review times grouped by time
StrokeNurseReview = audit_measure(
stem_name = "StrokeNurseReview",
description = "Onset to stroke nurse review",
exclusions = NULL,
numerators = rlang::exprs(
"Within12hrs" = !! ssnap_field[["ClockStartToStrokeNurseMins"]]
<= (12 * 60),
"Within24hrs" = !! ssnap_field[["ClockStartToStrokeNurseMins"]]
<= (24 * 60),
"Within72hrs" = !! ssnap_field[["ClockStartToStrokeNurseMins"]]
<= (72 * 60),
"12To24hrs" = dplyr::between(
!! ssnap_field[["ClockStartToStrokeNurseMins"]],
(12 * 60), (24 * 60)),
"24To72hrs" = dplyr::between(
!! ssnap_field[["ClockStartToStrokeNurseMins"]],
(24 * 60), (72 * 60))),
new_numerators = tibble::tribble(
~numerator, ~fun, ~descriptor,
"Within12hrs", rlang::expr(
!! ssnap_field[["ClockStartToStrokeNurseMins"]] <= (12 * 60)),
"Within 12 hours",
"Within24hrs", rlang::expr(
!! ssnap_field[["ClockStartToStrokeNurseMins"]] <= (24 * 60)),
"Within 24 hours",
"Within72hrs", rlang::expr(
!! ssnap_field[["ClockStartToStrokeNurseMins"]] <= (72 * 60)),
"Within 72 hours",
"12To24hrs",
rlang::expr(dplyr::between(
!! ssnap_field[["ClockStartToStrokeNurseMins"]],
(12 * 60), (24 * 60))),
"In 12 to 24 hours",
"24To72hrs",
rlang::expr(dplyr::between(
!! ssnap_field[["ClockStartToStrokeNurseMins"]],
(24 * 60), (72 * 60))),
"In 24 to 72 hours"),
csv_columns = c("S1PatientClockStartDateTime",
"S3StrokeNurseAssessedDateTime"),
measure_type = "discrete"),
# ClockStartToStrokeNurseMins =====================================
# G 8.14-16 Clock start to stroke nurse (minutes)
# H 8.14-16 Clock start to stroke nurse (minutes)
ClockStartToStrokeNurseMins = audit_measure(
stem_name = "ClockStartToStrokeNurseMins",
description = "Clock start to stroke nurse (mins)",
exclusions = NULL,
numerators = ssnap_field[["ClockStartToStrokeNurseMins"]],
new_numerators = ssnap_field[["ClockStartToStrokeNurseMins"]],
csv_columns = c("S1PatientClockStartDateTime",
"S3StrokeNurseAssessedDateTime"),
measure_type = "continuous"),
# * -----------------------------------------------------------------
# * Stroke consultant assessment ------------------------------------
# * -----------------------------------------------------------------
# StrokeConsultantReviewGrouped ===================================
# G 9.1-3 Stroke consultant within 24hrs
# H 9.1-3 Stroke consultant within 24hrs
# G 9.4-6 Stroke consultant within 72hrs
# H 9.4-6 Stroke consultant within 72hrs
# G 9.7-13 Stroke consultant review times grouped by time
# H 9.7-13 Stroke consultant review times grouped by time
# G 9.17-19 Stroke consultant within 14hrs
# H 9.17-19 Stroke consultant within 14hrs
StrokeConsultantReview = audit_measure(
stem_name = "StrokeConsultantReview",
description = "Onset to consultant review",
exclusions = NULL,
numerators = rlang::exprs(
"Within12hrs" = !! ssnap_field[["ClockStartToConsultantMins"]]
<= (12 * 60),
"Within14hrs" = !! ssnap_field[["ClockStartToConsultantMins"]]
<= (14 * 60),
"Within24hrs" = !! ssnap_field[["ClockStartToConsultantMins"]]
<= (24 * 60),
"Within72hrs" = !! ssnap_field[["ClockStartToConsultantMins"]]
<= (72 * 60),
"12To24hrs" = dplyr::between(
!! ssnap_field[["ClockStartToConsultantMins"]],
(12 * 60), (24 * 60)),
"24To72hrs" = dplyr::between(
!! ssnap_field[["ClockStartToConsultantMins"]],
(24 * 60), (72 * 60))),
new_numerators = tibble::tribble(
~numerator, ~fun, ~descriptor,
"Within12hrs",
rlang::expr(!! ssnap_field[["ClockStartToConsultantMins"]] <= (12 * 60)),
"Within 12 hours",
"Within14hrs",
rlang::expr(!! ssnap_field[["ClockStartToConsultantMins"]] <= (14 * 60)),
"Within 14 hours",
"Within24hrs",
rlang::expr(!! ssnap_field[["ClockStartToConsultantMins"]] <= (24 * 60)),
"Within 24 hours",
"Within72hrs",
rlang::expr(!! ssnap_field[["ClockStartToConsultantMins"]] <= (72 * 60)),
"Within 72 hours",
"12To24hrs", rlang::expr(dplyr::between(
!! ssnap_field[["ClockStartToConsultantMins"]], (12 * 60), (24 * 60))),
"12 to 24 hours",
"24To72hrs", rlang::expr(dplyr::between(
!! ssnap_field[["ClockStartToConsultantMins"]], (24 * 60), (72 * 60))),
"24 to 72 hours"),
csv_columns = c("S1PatientClockStartDateTime",
"S3StrokeConsultantAssessedDateTime"),
measure_type = "discrete"),
# ClockStartToConsultantMins ======================================
# G 9.14-16 Clock start to stroke consultant (minutes)
# H 9.14-16 Clock start to stroke consultant (minutes)
ClockStartToConsultantMins = audit_measure(
stem_name = "ClockStartToConsultantMins",
description = "Clock start to consultant review (mins)",
exclusions = NULL,
numerators = ssnap_field[["ClockStartToConsultantMins"]],
new_numerators = ssnap_field[["ClockStartToConsultantMins"]],
csv_columns = c("S1PatientClockStartDateTime",
"S3StrokeConsultantAssessedDateTime"),
measure_type = "continuous"),
# * -----------------------------------------------------------------
# * Occupational therapy --------------------------------------------
# * -----------------------------------------------------------------
# OccTherReviewGrouped ============================================
# G 10.1-15 Occupational therapy assessment breakdown
# H 10.1-15 Occupational therapy assessment breakdown
OccTherReviewGrouped = audit_measure(
stem_name = "OccTherReview",
description = "Onset to occupational therapy initial assessment",
exclusions = NULL,
numerators = rlang::exprs(
"Within24hrs" = !! ssnap_field[["ClockStartToOTMins"]]
<= (24 * 60),
"24To72hrs" = dplyr::between(
!! ssnap_field[["ClockStartToOTMins"]], (24 * 60), (72 * 60)),
"NotDoneOrg" =
.data[["S3OccTherapist72HrsNotAssessedReason"]] == "OR",
"NotDoneRefused" =
.data[["S3OccTherapist72HrsNotAssessedReason"]] == "PR",
"NotDoneUnwell" =
.data[["S3OccTherapist72HrsNotAssessedReason"]] == "MU",
"NotDoneNoDeficit" =
.data[["S3OccTherapist72HrsNotAssessedReason"]] == "ND",
"NotDoneNotKnown" =
.data[["S3OccTherapist72HrsNotAssessedReason"]] == "NK"),
new_numerators = tibble::tribble(
~numerator, ~fun, ~descriptor,
"Within24hrs",
rlang::expr(!! ssnap_field[["ClockStartToOTMins"]] <= (24 * 60)),
"Within 24 hours",
"24To72hrs", rlang::expr(dplyr::between(
!! ssnap_field[["ClockStartToOTMins"]], (24 * 60), (72 * 60))),
"24 to 72 hours",
"NotDoneOrg", rlang::expr(
.data[["S3OccTherapist72HrsNotAssessedReason"]] == "OR"),
"Not done (organisational reasons)",
"NotDoneRefused", rlang::expr(
.data[["S3OccTherapist72HrsNotAssessedReason"]] == "PR"),
"Not done (patient refused)",
"NotDoneUnwell", rlang::expr(
.data[["S3OccTherapist72HrsNotAssessedReason"]] == "MU"),
"Not done (unwell)",
"NotDoneNoDeficit", rlang::expr(
.data[["S3OccTherapist72HrsNotAssessedReason"]] == "ND"),
"Not done (no deficit)",
"NotDoneNotKnown", rlang::expr(
.data[["S3OccTherapist72HrsNotAssessedReason"]] == "NK"),
"Not done (not known)"),
csv_columns = c("S1PatientClockStartDateTime",
"S3OccTherapist72HrsDateTime",
"S3OccTherapist72HrsNotAssessedReason"),
measure_type = "discrete"),
# ClockStartToOTMins ==============================================
# G 10.16-18 Clock start to occupational therapy assessment (mins)
# H 10.16-18 Clock start to occupational therapy assessment (mins)
ClockStartToOTMins = audit_measure(
stem_name = "ClockStartToOTMins",
description = "Clock start to initial OT assessment (mins)",
exclusions = NULL,
numerators = ssnap_field[["ClockStartToOTMins"]],
new_numerators = ssnap_field[["ClockStartToOTMins"]],
csv_columns = c("S1PatientClockStartDateTime",
"S3OccTherapist72HrsDateTime"),
measure_type = "continuous"),
# OccTherApplicability ============================================
# G 10.19-21 Applicability for occupational therapy
# H 10.19-21 Applicability for occupational therapy
OccTherApplicability = audit_measure(
stem_name = "OccTherApplicability",
description = "Applicability for occupational therapy",
exclusions = NULL,
numerators = rlang::expr(!(
.data[["S3OccTherapist72HrsNotAssessedReason"]]
%in% c("PR", "PU", "ND"))),
new_numerators = rlang::expr(!(
.data[["S3OccTherapist72HrsNotAssessedReason"]]
%in% c("PR", "PU", "ND"))),
csv_columns = "S3OccTherapist72HrsNotAssessedReason",
measure_type = "discrete"),
# OccTherApplicableWithin72hrs ====================================
# G 10.22-24 If applicable, OT assessment within 72 hours
# H 10.22-24 If applicable, OT assessment within 72 hours
OccTherApplicableWithin72hrs = audit_measure(
stem_name = "OccTherApplicableWithin72hrs",
description = "Applicability for occupational therapy",
exclusions = rlang::expr(
.data[["S3OccTherapist72HrsNotAssessedReason"]]
%in% c("PR", "PU", "ND")),
numerators = rlang::expr(!! ssnap_field[["ClockStartToOTMins"]]
<= (72 * 60)),
new_numerators =
rlang::expr(!! ssnap_field[["ClockStartToOTMins"]] <= (72 * 60)),
csv_columns = c("S1PatientClockStartDateTime",
"S3OccTherapist72HrsDateTime",
"S3OccTherapist72HrsNotAssessedReason"),
measure_type = "discrete"),
# OccTherApplicableWithin24hrs ====================================
# G 10.25-27 If applicable, OT assessment within 24 hours
# H 10.25-27 If applicable, OT assessment within 24 hours
OccTherApplicableWithin24hrs = audit_measure(
stem_name = "OccTherApplicableWithin24hrs",
description = "Applicability for occupational therapy",
exclusions = rlang::expr(
.data[["S3OccTherapist72HrsNotAssessedReason"]]
%in% c("PR", "PU", "ND")),
numerators = rlang::expr(!! ssnap_field[["ClockStartToOTMins"]]
<= (24 * 60)),
new_numerators =
rlang::expr(!! ssnap_field[["ClockStartToOTMins"]] <= (24 * 60)),
csv_columns = c("S1PatientClockStartDateTime",
"S3OccTherapist72HrsDateTime",
"S3OccTherapist72HrsNotAssessedReason"),
measure_type = "discrete"),
# OTAssessment72HrsComplete =======================================
# C6.4-6.6 Reason for no OT assessment within 72hrs is known
OTAssessment72HrsComplete = audit_measure(
stem_name = "OTAssessment72HrsComplete",
description = "OT assessment within 72hrs known",
exclusions = NULL,
numerators = rlang::expr(
(.data[["S3OccTherapist72HrsNotAssessedReason"]] != "NK") |
is.na(.data[["S3OccTherapist72HrsNotAssessedReason"]])),
new_numerators = rlang::expr(
(.data[["S3OccTherapist72HrsNotAssessedReason"]] != "NK") |
is.na(.data[["S3OccTherapist72HrsNotAssessedReason"]])),
csv_columns = "S3OccTherapist72HrsNotAssessedReason",
measure_type = "discrete"),
# * -----------------------------------------------------------------
# * Physiotherapy ---------------------------------------------------
# * -----------------------------------------------------------------
# PhysioReviewGrouped =============================================
# G 11.1-15 Physiotherapy assessment breakdown
# H 11.1-15 Physiotherapy assessment breakdown
PhysioReviewGrouped = audit_measure(
stem_name = "PhysioReview",
description = "Onset to physiotherapy initial assessment",
exclusions = NULL,
numerators = rlang::exprs(
"Within24hrs" = !! ssnap_field[["ClockStartToPTMins"]]
<= (24 * 60),
"24To72hrs" = dplyr::between(
!! ssnap_field[["ClockStartToPTMins"]], (24 * 60), (72 * 60)),
"NotDoneOrg" =
.data[["S3Physio72HrsNotAssessedReason"]] == "OR",
"NotDoneRefused" =
.data[["S3Physio72HrsNotAssessedReason"]] == "PR",
"NotDoneUnwell" =
.data[["S3Physio72HrsNotAssessedReason"]] == "MU",
"NotDoneNoDeficit" =
.data[["S3Physio72HrsNotAssessedReason"]] == "ND",
"NotDoneNotKnown" =
.data[["S3Physio72HrsNotAssessedReason"]] == "NK"),
new_numerators = tibble::tribble(
~numerator, ~fun, ~descriptor,
"Within24hrs", rlang::expr(
!! ssnap_field[["ClockStartToPTMins"]] <= (24 * 60)),
"Within 24 hours",
"24To72hrs", rlang::expr(dplyr::between(
!! ssnap_field[["ClockStartToPTMins"]], (24 * 60), (72 * 60))),
"24 to 72 hours",
"NotDoneOrg", rlang::expr(
.data[["S3Physio72HrsNotAssessedReason"]] == "OR"),
"Not done (organisational reasons)",
"NotDoneRefused", rlang::expr(
.data[["S3Physio72HrsNotAssessedReason"]] == "PR"),
"Not done (patient refused)",
"NotDoneUnwell", rlang::expr(
.data[["S3Physio72HrsNotAssessedReason"]] == "MU"),
"Not done (medically unwell)",
"NotDoneNoDeficit", rlang::expr(
.data[["S3Physio72HrsNotAssessedReason"]] == "ND"),
"Not done (no deficits)",
"NotDoneNotKnown", rlang::expr(
.data[["S3Physio72HrsNotAssessedReason"]] == "NK"),
"Not done (not known)"),
csv_columns = c("S1PatientClockStartDateTime",
"S3Physio72HrsDateTime",
"S3Physio72HrsNotAssessedReason"),
measure_type = "discrete"),
# ClockStartToPTMins ==============================================
# G 11.16-18 Clock start to physiotherapy assessment (mins)
# H 11.16-18 Clock start to physiotherapy assessment (mins)
ClockStartToPTMins = audit_measure(
stem_name = "ClockStartToPTMins",
description = "Clock start to initial PT assessment (mins)",
exclusions = NULL,
numerators = ssnap_field[["ClockStartToPTMins"]],
new_numerators = ssnap_field[["ClockStartToPTMins"]],
csv_columns = c("S1PatientClockStartDateTime",
"S3Physio72HrsDateTime"),
measure_type = "continuous"),
# PhysioApplicability =============================================
# G 11.19-21 Applicability for physiotherapy
# H 11.19-21 Applicability for physiotherapy
PhysioApplicability = audit_measure(
stem_name = "PhysioApplicability",
description = "Applicability for physiotherapy",
exclusions = NULL,
numerators = rlang::expr(!(
.data[["S3Physio72HrsNotAssessedReason"]]
%in% c("PR", "PU", "ND"))),
new_numerators = rlang::expr(!(
.data[["S3Physio72HrsNotAssessedReason"]]
%in% c("PR", "PU", "ND"))),
csv_columns = "S3Physio72HrsNotAssessedReason",
measure_type = "discrete"),
# PhysioApplicableWithin72hrs =====================================
# G 11.22-24 If applicable, PT assessment within 72 hours
# H 11.22-24 If applicable, PT assessment within 72 hours
PhysioApplicableWithin72hrs = audit_measure(
stem_name = "PhysioApplicableWithin72hrs",
description = "Applicability for physiotherapy",
exclusions = rlang::expr(.data[["S3Physio72HrsNotAssessedReason"]]
%in% c("PR", "PU", "ND")),
numerators = rlang::expr(!! ssnap_field[["ClockStartToPTMins"]]
<= (72 * 60)),
new_numerators = rlang::expr(!! ssnap_field[["ClockStartToPTMins"]]
<= (72 * 60)),
csv_columns = c("S1PatientClockStartDateTime",
"S3Physio72HrsDateTime",
"S3Physio72HrsNotAssessedReason"),
measure_type = "discrete"),
# PhysioApplicableWithin24hrs =====================================
# G 11.25-27 If applicable, PT assessment within 24 hours
# H 11.25-27 If applicable, PT assessment within 24 hours
PhysioApplicableWithin24hrs = audit_measure(
stem_name = "PhysioApplicableWithin24hrs",
description = "Applicability for physiotherapy",
exclusions = rlang::expr(.data[["S3Physio72HrsNotAssessedReason"]]
%in% c("PR", "PU", "ND")),
numerators = rlang::expr(!! ssnap_field[["ClockStartToPTMins"]]
<= (24 * 60)),
new_numerators = rlang::expr(!! ssnap_field[["ClockStartToPTMins"]]
<= (24 * 60)),
csv_columns = c("S1PatientClockStartDateTime",
"S3Physio72HrsDateTime",
"S3Physio72HrsNotAssessedReason"),
measure_type = "discrete"),
# PTAssessment72HrsComplete =======================================
# C6.13-15 Reason for no PT assessment within 72hrs is known
PTAssessment72HrsComplete = audit_measure(
stem_name = "PTAssessment72HrsComplete",
description = "PT assessment within 72hrs known",
exclusions = NULL,
numerators = rlang::expr(
(.data[["S3Physio72HrsNotAssessedReason"]] != "NK") |
is.na(.data[["S3Physio72HrsNotAssessedReason"]])),
new_numerators = rlang::expr(
(.data[["S3Physio72HrsNotAssessedReason"]] != "NK") |
is.na(.data[["S3Physio72HrsNotAssessedReason"]])),
csv_columns = "S3Physio72HrsNotAssessedReason",
measure_type = "discrete"),
# * -----------------------------------------------------------------
# * Speech and language therapy (communication) ---------------------
# * -----------------------------------------------------------------
# SLTCommReviewGrouped ==============================================
# G 12.1-15 Speech and language communication assessment breakdown
# H 12.1-15 Speech and language communication assessment breakdown
SLTCommReviewGrouped = audit_measure(
stem_name = "SLTCommReview",
description = "Onset to SLT communication initial assessment",
exclusions = NULL,
numerators = rlang::exprs(
"Within24hrs" = !! ssnap_field[["ClockStartToSLTCommMins"]]
<= (24 * 60),
"24To72hrs" = dplyr::between(
!! ssnap_field[["ClockStartToSLTCommMins"]],
(24 * 60), (72 * 60)),
"NotDoneOrg" =
.data[["S3SpLangTherapistComm72HrsNotAssessedReason"]] == "OR",
"NotDoneRefused" =
.data[["S3SpLangTherapistComm72HrsNotAssessedReason"]] == "PR",
"NotDoneUnwell" =
.data[["S3SpLangTherapistComm72HrsNotAssessedReason"]] == "MU",
"NotDoneNoDeficit" =
.data[["S3SpLangTherapistComm72HrsNotAssessedReason"]] == "ND",
"NotDoneNotKnown" =
.data[["S3SpLangTherapistComm72HrsNotAssessedReason"]] == "NK"),
new_numerators = tibble::tribble(
~numerator, ~fun, ~descriptor,
"Within24hrs", rlang::expr(
!! ssnap_field[["ClockStartToSLTCommMins"]] <= (24 * 60)),
"Within 24 hours",
"24To72hrs", rlang::expr(dplyr::between(
!! ssnap_field[["ClockStartToSLTCommMins"]],
(24 * 60), (72 * 60))),
"24 to 72 hours",
"NotDoneOrg", rlang::expr(
.data[["S3SpLangTherapistComm72HrsNotAssessedReason"]] == "OR"),
"Not done (organisational reasons)",
"NotDoneRefused", rlang::expr(
.data[["S3SpLangTherapistComm72HrsNotAssessedReason"]] == "PR"),
"Not done (patient refused)",
"NotDoneUnwell", rlang::expr(
.data[["S3SpLangTherapistComm72HrsNotAssessedReason"]] == "MU"),
"Not done (patient unwell)",
"NotDoneNoDeficit", rlang::expr(
.data[["S3SpLangTherapistComm72HrsNotAssessedReason"]] == "ND"),
"Not done (no deficit)",
"NotDoneNotKnown", rlang::expr(
.data[["S3SpLangTherapistComm72HrsNotAssessedReason"]] == "NK"),
"Not done (not known)"),
csv_columns = c("S1PatientClockStartDateTime",
"S3SpLangTherapistComm72HrsDateTime",
"S3SpLangTherapistComm72HrsNotAssessedReason"),
measure_type = "discrete"),
# ClockStartToSLTCommMins =========================================
# G 12.16-18 Clock start to SLT communication assessment (mins)
# H 12.16-18 Clock start to SLT communication assessment (mins)
ClockStartToSLTCommMins = audit_measure(
stem_name = "ClockStartToSLTCommMins",
description =
"Clock start to initial SLT communication assessment (mins)",
exclusions = NULL,
numerators = ssnap_field[["ClockStartToSLTCommMins"]],
new_numerators = ssnap_field[["ClockStartToSLTCommMins"]],
csv_columns = c("S1PatientClockStartDateTime",
"S3SpLangTherapistComm72HrsDateTime"),
measure_type = "continuous"),
# SLTCommApplicability ============================================
# G 12.19-21 Applicability for SLT communication therapy
# H 12.19-21 Applicability for SLT communication therapy
SLTCommApplicability = audit_measure(
stem_name = "SLTCommApplicability",
description = "Applicability for SLT communication therapy",
exclusions = NULL,
numerators = rlang::expr(!(
.data[["S3SpLangTherapistComm72HrsNotAssessedReason"]]
%in% c("PR", "PU", "ND"))),
new_numerators = rlang::expr(!(
.data[["S3SpLangTherapistComm72HrsNotAssessedReason"]]
%in% c("PR", "PU", "ND"))),
csv_columns = "S3SpLangTherapistComm72HrsNotAssessedReason",
measure_type = "discrete"),
# SLTCommApplicableWithin72hrs ====================================
# G 12.22-24 If applicable, SLT Comm assessment within 72 hours
# H 12.22-24 If applicable, SLT Comm assessment within 72 hours
SLTCommApplicableWithin72hrs = audit_measure(
stem_name = "SLTCommApplicableWithin72hrs",
description = "Applicability for SLT communication therapy",
exclusions = rlang::expr(
.data[["S3SpLangTherapistComm72HrsNotAssessedReason"]]
%in% c("PR", "PU", "ND")),
numerators = rlang::expr(!! ssnap_field[["ClockStartToSLTCommMins"]]
<= (72 * 60)),
new_numerators = rlang::expr(!! ssnap_field[["ClockStartToSLTCommMins"]]
<= (72 * 60)),
csv_columns = c("S1PatientClockStartDateTime",
"S3SpLangTherapistComm72HrsDateTime",
"S3SpLangTherapistComm72HrsNotAssessedReason"),
measure_type = "discrete"),
# SLTCommApplicableWithin24hrs ====================================
# G 12.25-27 If applicable, SLT Comm assessment within 24 hours
# H 12.25-27 If applicable, SLT Comm assessment within 24 hours
SLTCommApplicableWithin24hrs = audit_measure(
stem_name = "SLTCommApplicableWithin24hrs",
description = "Applicability for SLT communication therapy",
exclusions = rlang::expr(
.data[["S3SpLangTherapistComm72HrsNotAssessedReason"]]
%in% c("PR", "PU", "ND")),
numerators = rlang::expr(ssnap_field[["ClockStartToSLTCommMins"]]
<= (24 * 60)),
new_numerators = rlang::expr(ssnap_field[["ClockStartToSLTCommMins"]]
<= (24 * 60)),
csv_columns = "S3SpLangTherapistComm72HrsNotAssessedReason",
measure_type = "discrete"),
# SLTCommAssessment72HrsComplete ==================================
# C6.16-18 Reason for no SLT Comm assessment within 72hrs is known
SLTCommAssessment72HrsComplete = audit_measure(
stem_name = "SLTCommAssessment72HrsComplete",
description = "SLT Comm assessment within 72hrs known",
exclusions = NULL,
numerators = rlang::expr(
(.data[["S3SpLangTherapistComm72HrsNotAssessedReason"]]
!= "NK") | is.na(
.data[["S3SpLangTherapistComm72HrsNotAssessedReason"]])),
new_numerators = rlang::expr(
(.data[["S3SpLangTherapistComm72HrsNotAssessedReason"]]
!= "NK") | is.na(
.data[["S3SpLangTherapistComm72HrsNotAssessedReason"]])),
csv_columns = "S3SpLangTherapistComm72HrsNotAssessedReason",
measure_type = "discrete"),
# * -----------------------------------------------------------------
# * First 72hrs Bundle ----------------------------------------------
# * -----------------------------------------------------------------
# G 13.1-3 Seen by nurse in 24hrs, one therapist in 24hrs and all
# therapists in 72hrs.
# H 13.1-3 Seen by nurse in 24hrs, one therapist in 24hrs and all
# therapists in 72hrs.
# TODO This needs to be implemented
# * Swallow Screening -----------------------------------------------
# * -----------------------------------------------------------------
# SwallowScreen4hrsGrouped ========================================
# G 14.1-11 Swallow screening within 4 hours breakdown
# H 14.1-11 Swallow screening within 4 hours breakdown
SwallowScreen4hrsGrouped = audit_measure(
stem_name = "SwallowScreen4hrs",
description = "Swallow screen within 4hrs",
exclusions = NULL,
numerators = rlang::exprs(
"Within4hrs" =
!! ssnap_field[["ClockStartToSwallowScreen4hrsMins"]]
<= (4 * 60),
"NotDoneOrg" =
.data[["S2SwallowScreening4HrsNotPerformedReason"]] == "OR",
"NotDoneRefused" =
.data[["S2SwallowScreening4HrsNotPerformedReason"]] == "PR",
"NotDoneUnwell" =
.data[["S2SwallowScreening4HrsNotPerformedReason"]] == "MU",
"NotDoneNotKnown" =
.data[["S2SwallowScreening4HrsNotPerformedReason"]] == "NK"),
new_numerators = tibble::tribble(
~numerator, ~fun, ~descriptor,
"Within4hrs",
!! ssnap_field[["ClockStartToSwallowScreen4hrsMins"]] <= (4 * 60),
"Within 4 hours",
"NotDoneOrg",
.data[["S2SwallowScreening4HrsNotPerformedReason"]] == "OR",
"Not done (organisational reasons)",
"NotDoneRefused",
.data[["S2SwallowScreening4HrsNotPerformedReason"]] == "PR",
"Not done (refused)",
"NotDoneUnwell",
.data[["S2SwallowScreening4HrsNotPerformedReason"]] == "MU",
"Not done (unwell)",
"NotDoneNotKnown",
.data[["S2SwallowScreening4HrsNotPerformedReason"]] == "NK",
"Not done (not known)"),
csv_columns = c("S1PatientClockStartDateTime",
"S2SwallowScreening4HrsDateTime",
"S2SwallowScreening4HrsNotPerformedReason"),
measure_type = "discrete"),
# ClockStartToSwallowScreen4hrsMins ===============================
# G 14.12-14 Clock start to swallow screening if done within 4hrs
# H 14.12-14 Clock start to swallow screening if done within 4hrs
ClockStartToSwallowScreen4hrsMins = audit_measure(
stem_name = "ClockStartToSwallowScreen4hrsMins",
description =
"Clock start to swallow screening if done within 4hrs (mins)",
exclusions = NULL,
numerators = ssnap_field[["ClockStartToSwallowScreen4hrsMins"]],
new_numerators = ssnap_field[["ClockStartToSwallowScreen4hrsMins"]],
csv_columns = c("S1PatientClockStartDateTime",
"S2SwallowScreening4HrsDateTime"),
measure_type = "continuous"),
# SwallowScreen4hrsApplicability ==================================
# G 14.15-17 Applicability for swallow screening within 4hrs
# H 14.15-17 Applicability for swallow screening within 4hrs
SwallowScreen4hrsApplicability = audit_measure(
stem_name = "SwallowScreen4hrsApplicability",
description = "Applicability for swallow screening within 4hrs",
exclusions = NULL,
numerators = rlang::expr(!(
.data[["S2SwallowScreening4HrsNotPerformedReason"]] %in%
c("PR", "PU"))),
new_numerators = rlang::expr(!(
.data[["S2SwallowScreening4HrsNotPerformedReason"]] %in%
c("PR", "PU"))),
csv_columns = "S2SwallowScreening4HrsNotPerformedReason",
measure_type = "discrete"),
# SwallowScreenWithin4hrs =========================================
# G 14.18-20 Swallow screen done if applicable within 4hrs
# H 14.18-20 Swallow screen done if applicable within 4hrs
SwallowScreenWithin4hrs = audit_measure(
stem_name = "SwallowScreenWithin4hrs",
description = "Swallow screen within 4 hours",
exclusions = rlang::expr(
.data[["S2SwallowScreening4HrsNotPerformedReason"]] %in%
c("PR", "PU")),
numerators = rlang::expr(
!! ssnap_field[["ClockStartToSwallowScreen4hrsMins"]] <= (4 * 60)),
new_numerators = rlang::expr(
!! ssnap_field[["ClockStartToSwallowScreen4hrsMins"]] <= (4 * 60)),
csv_columns = c("S1PatientClockStartDateTime",
"S2SwallowScreening4HrsDateTime",
"S2SwallowScreening4HrsNotPerformedReason"),
measure_type = "discrete"),
# SwallowScreen4hrsComplete =======================================
# C6.4-6 Reason for no swallow screening within 4hrs is known
SwallowScreen4hrsComplete = audit_measure(
stem_name = "SwallowScreen4hrsComplete",
description = "Swallow screening at 4 hrs known",
exclusions = NULL,
numerators = rlang::expr(
(.data[["S2SwallowScreening4HrsNotPerformedReason"]] != "NK") |
is.na(.data[["S2SwallowScreening4HrsNotPerformedReason"]])),
new_numerators = rlang::expr(
(.data[["S2SwallowScreening4HrsNotPerformedReason"]] != "NK") |
is.na(.data[["S2SwallowScreening4HrsNotPerformedReason"]])),
csv_columns = "S2SwallowScreening4HrsNotPerformedReason",
measure_type = "discrete"),
# ClockStartToSwallowScreen72hrsMins ==============================
# G 14.21-23 Clock start to swallow screening if done within 72hrs
# H 14.21-23 Clock start to swallow screening if done within 72hrs
ClockStartToSwallowScreen72hrsMins = audit_measure(
stem_name = "ClockStartToSwallowScreen72hrsMins",
description =
"Clock start to swallow screening if done within 72hrs (mins)",
exclusions = NULL,
numerators = ssnap_field[["ClockStartToSwallowScreen72hrsMins"]],
new_numerators = ssnap_field[["ClockStartToSwallowScreen72hrsMins"]],
csv_columns = c("S2SwallowScreening4HrsDateTime",
"S1PatientClockStartDateTime",
"S3SwallowScreening72HrsDateTime"),
measure_type = "continuous"),
# SwallowScreen72hrsGrouped ========================================
# G 14.24-40 Swallow screening within 72 hours breakdown
# H 14.24-40 Swallow screening within 72 hours breakdown
SwallowScreen72hrsGrouped = audit_measure(
stem_name = "SwallowScreen72hrs",
description = "Swallow screen within 72hrs",
exclusions = NULL,
numerators = rlang::exprs(
"Within4hrs" =
!! ssnap_field[["ClockStartToSwallowScreen72hrsMins"]]
<= (4 * 60),
"4To12hrs" = dplyr::between(
!! ssnap_field[["ClockStartToSwallowScreen72hrsMins"]],
(4 * 60), (12 * 60)),
"12To24hrs" = dplyr::between(
!! ssnap_field[["ClockStartToSwallowScreen72hrsMins"]],
(12 * 60), (24 * 60)),
"24To72hrs" = dplyr::between(
!! ssnap_field[["ClockStartToSwallowScreen72hrsMins"]],
(24 * 60), (72 * 60)),
"NotDoneOrg" =
.data[["S3SwallowScreening72HrsNotPerformedReason"]] == "OR",
"NotDoneRefused" =
.data[["S3SwallowScreening72HrsNotPerformedReason"]] == "PR",
"NotDoneUnwell" =
.data[["S3SwallowScreening72HrsNotPerformedReason"]] == "MU",
"NotDoneNotKnown" =
.data[["S3SwallowScreening72HrsNotPerformedReason"]] == "NK"),
new_numerators = tibble::tribble(
~numerator, ~fun, ~descriptor,
"Within4hrs", rlang::expr(
!! ssnap_field[["ClockStartToSwallowScreen72hrsMins"]] <= (4 * 60)),
"Within 4 hours",
"4To12hrs", rlang::expr(dplyr::between(
!! ssnap_field[["ClockStartToSwallowScreen72hrsMins"]],
(4 * 60), (12 * 60))),
"4 to 12 hours",
"12To24hrs", rlang::expr(dplyr::between(
!! ssnap_field[["ClockStartToSwallowScreen72hrsMins"]],
(12 * 60), (24 * 60))),
"12 to 24 hours",
"24To72hrs", rlang::expr(dplyr::between(
!! ssnap_field[["ClockStartToSwallowScreen72hrsMins"]],
(24 * 60), (72 * 60))),
"24 to 72 hours",
"NotDoneOrg", rlang::expr(
.data[["S3SwallowScreening72HrsNotPerformedReason"]] == "OR"),
"Not done (organisational reasons)",
"NotDoneRefused", rlang::expr(
.data[["S3SwallowScreening72HrsNotPerformedReason"]] == "PR"),
"Not done (refused)",
"NotDoneUnwell", rlang::expr(
.data[["S3SwallowScreening72HrsNotPerformedReason"]] == "MU"),
"Not done (medically unwell)",
"NotDoneNotKnown", rlang::expr(
.data[["S3SwallowScreening72HrsNotPerformedReason"]] == "NK"),
"Not done (not known)"),
csv_columns = c("S2SwallowScreening4HrsDateTime",
"S1PatientClockStartDateTime",
"S3SwallowScreening72HrsDateTime",
"S3SwallowScreening72HrsNotPerformedReason"),
measure_type = "discrete"),
# SwallowScreen72hrsApplicability =================================
# G 14.41-43 Applicability for swallow screening within 72hrs
# H 14.41-43 Applicability for swallow screening within 72hrs
SwallowScreen72hrsApplicability = audit_measure(
stem_name = "SwallowScreen72hrsApplicability",
description = "Applicability for swallow screening within 72hrs",
exclusions = NULL,
numerators = rlang::expr(!(
.data[["S3SwallowScreening72HrsNotPerformedReason"]] %in%
c("PR", "PU"))),
new_numerators = rlang::expr(!(
.data[["S3SwallowScreening72HrsNotPerformedReason"]] %in%
c("PR", "PU"))),
csv_columns = "S3SwallowScreening72HrsNotPerformedReason",
measure_type = "discrete"),
# SwallowScreenWithin72hrs ========================================
# G 14.44-46 Swallow screen done if applicable within 72hrs
# H 14.44-46 Swallow screen done if applicable within 72hrs
SwallowScreenWithin72hrs = audit_measure(
stem_name = "SwallowScreenWithin72hrs",
description = "Swallow screen within 72 hours",
exclusions = rlang::expr(
.data[["S3SwallowScreening72HrsNotPerformedReason"]] %in%
c("PR", "PU")),
numerators = rlang::expr(
!! ssnap_field[["ClockStartToSwallowScreen72hrsMins"]]
<= (72 * 60)),
new_numerators = rlang::expr(
!! ssnap_field[["ClockStartToSwallowScreen72hrsMins"]]
<= (72 * 60)),
csv_columns = c("S2SwallowScreening4HrsDateTime",
"S1PatientClockStartDateTime",
"S3SwallowScreening72HrsDateTime",
"S3SwallowScreening72HrsNotPerformedReason"),
measure_type = "discrete"),
# SwallowScreen72hrsComplete ======================================
# C6/7-9 Swallow screening at 72hrs is known.
SwallowScreen72hrsComplete = audit_measure(
stem_name = "SwallowScreen72hrsComplete",
description = "Swallow screening at 72hrs known",
exclusions = NULL,
numerators = rlang::expr(
(.data[["S3SwallowScreening72HrsNotPerformedReason"]] != "NK") |
is.na(.data[["S3SwallowScreening72HrsNotPerformedReason"]])),
new_numerators = rlang::expr(
(.data[["S3SwallowScreening72HrsNotPerformedReason"]] != "NK") |
is.na(.data[["S3SwallowScreening72HrsNotPerformedReason"]])),
csv_columns = "S3SwallowScreening72HrsNotPerformedReason",
measure_type = "discrete"),
# * -----------------------------------------------------------------
# * Formal swallow assessment ---------------------------------------
# * -----------------------------------------------------------------
# ClockStartToSpLangTherapistSwallowMins ==========================
# G 15.1-3 Clock start to formal swallow assessment
# H 15.1-3 Clock start to formal swallow assessment
ClockStartToSpLangTherapistSwallowMins = audit_measure(
stem_name = "ClockStartToSpLangTherapistSwallowMins",
description =
"Clock start to formal swallow assessment (mins)",
exclusions = NULL,
numerators =
ssnap_field[["ClockStartToSpLangTherapistSwallowMins"]],
new_numerators =
ssnap_field[["ClockStartToSpLangTherapistSwallowMins"]],
csv_columns = c("S1PatientClockStartDateTime",
"S3SpLangTherapistSwallow72HrsDateTime"),
measure_type = "continuous"),
# SpLangTherapistSwallow72hrsGrouped ==============================
# G 15.4-18 SLT Swallow assessment breakdown
# H 15.4-18 SLT Swallow assessment breakdown
SpLangTherapistSwallow72hrsGrouped = audit_measure(
stem_name = "SpLangTherapistSwallow72hrs",
description = "Speech and language swallow within 72hrs",
exclusions = NULL,
numerators = rlang::exprs(
"Within12hrs" =
!! ssnap_field[["ClockStartToSpLangTherapistSwallowMins"]]
<= (12 * 60),
"12To24hrs" = dplyr::between(
!! ssnap_field[["ClockStartToSpLangTherapistSwallowMins"]],
(12 * 60), (24 * 60)),
"24To72hrs" = dplyr::between(
!! ssnap_field[["ClockStartToSpLangTherapistSwallowMins"]],
(24 * 60), (72 * 60)),
"NotDoneOrg" =
.data[["S3SpLangTherapistSwallow72HrsNotAssessedReason"]]
== "OR",
"NotDoneRefused" =
.data[["S3SpLangTherapistSwallow72HrsNotAssessedReason"]]
== "PR",
"NotDoneUnwell" =
.data[["S3SpLangTherapistSwallow72HrsNotAssessedReason"]]
== "PU",
"NotDonePassedSwallow" =
.data[["S3SpLangTherapistSwallow72HrsNotAssessedReason"]]
== "PS",
"NotDoneNotKnown" =
.data[["S3SpLangTherapistSwallow72HrsNotAssessedReason"]]
== "NK"),
new_numerators = tibble::tribble(
~numerator, ~fun, ~descriptor,
"Within12hrs", rlang::expr(
!! ssnap_field[["ClockStartToSpLangTherapistSwallowMins"]] <= (12 * 60)),
"Within 12 hours",
"12To24hrs", rlang::expr(dplyr::between(
!! ssnap_field[["ClockStartToSpLangTherapistSwallowMins"]],
(12 * 60), (24 * 60))),
"12 to 24 hours",
"24To72hrs", rlang::expr(dplyr::between(
!! ssnap_field[["ClockStartToSpLangTherapistSwallowMins"]],
(24 * 60), (72 * 60))),
"24 to 72 hours",
"NotDoneOrg", rlang::expr(
.data[["S3SpLangTherapistSwallow72HrsNotAssessedReason"]] == "OR"),
"Not done (organisational reasons)",
"NotDoneRefused", rlang::expr(
.data[["S3SpLangTherapistSwallow72HrsNotAssessedReason"]] == "PR"),
"Not done (refused)",
"NotDoneUnwell", rlang::expr(
.data[["S3SpLangTherapistSwallow72HrsNotAssessedReason"]] == "PU"),
"Not done (medically unwell)",
"NotDonePassedSwallow", rlang::expr(
.data[["S3SpLangTherapistSwallow72HrsNotAssessedReason"]] == "PS"),
"Not done (passed swallow)",
"NotDoneNotKnown", rlang::expr(
.data[["S3SpLangTherapistSwallow72HrsNotAssessedReason"]] == "NK"),
"Not done (not known)"),
csv_columns = c("S1PatientClockStartDateTime",
"S3SpLangTherapistSwallow72HrsDateTime",
"S3SpLangTherapistSwallow72HrsNotAssessedReason"),
measure_type = "discrete"),
# SpLangTherapistSwallowApplicability =============================
# G 15.19-22 Applicability for swallow assessment
# H 15.19-22 Applicability for swallow assessment
SpLangTherapistSwallowApplicability = audit_measure(
stem_name = "SpLangTherapistSwallowApplicability",
description = "Applicability for swallow assessment",
exclusions = NULL,
numerators = rlang::expr(!(
.data[["S3SpLangTherapistSwallow72HrsNotAssessedReason"]] %in%
c("PR", "PU", "PS"))),
new_numerators = rlang::expr(!(
.data[["S3SpLangTherapistSwallow72HrsNotAssessedReason"]] %in%
c("PR", "PU", "PS"))),
csv_columns = "S3SpLangTherapistSwallow72HrsNotAssessedReason",
measure_type = "discrete"),
# SpLangTherapistSwallowWithin72hrs ===============================
# G 15.23-25 Swallow assessment done if applicable within 72hrs
# H 14.23-25 Swallow assessment done if applicable within 72hrs
SpLangTherapistSwallowWithin72hrs = audit_measure(
stem_name = "SpLangTherapistSwallowWithin72hrs",
description = "Swallow assessment if applicable within 72 hours",
exclusions = rlang::expr(
.data[["S3SpLangTherapistSwallow72HrsNotAssessedReason"]] %in%
c("PR", "PU", "PS")),
numerators = rlang::expr(
!! ssnap_field[["ClockStartToSpLangTherapistSwallowMins"]]
<= (72 * 60)),
new_numerators = rlang::expr(
!! ssnap_field[["ClockStartToSpLangTherapistSwallowMins"]]
<= (72 * 60)),
csv_columns = c("S1PatientClockStartDateTime",
"S3SpLangTherapistSwallow72HrsDateTime",
"S3SpLangTherapistSwallow72HrsNotAssessedReason"),
measure_type = "discrete"),
# SwallowAssessment72hrsComplete ==================================
# C 6.19.-21 Reason for formal swallow assessment known
SwallowAssessment72hrsComplete = audit_measure(
stem_name = "SwallowAssessment72hrsComplete",
description = "Swallow assessment within 72hrs known",
exclusions = NULL,
numerators = rlang::expr(
(.data[["S3SpLangTherapistSwallow72HrsNotAssessedReason"]] !=
"NK") | is.na(
.data[["S3SpLangTherapistSwallow72HrsNotAssessedReason"]])
),
new_numerators = rlang::expr(
(.data[["S3SpLangTherapistSwallow72HrsNotAssessedReason"]] !=
"NK") | is.na(
.data[["S3SpLangTherapistSwallow72HrsNotAssessedReason"]])),
csv_columns = "S3SpLangTherapistSwallow72HrsNotAssessedReason",
measure_type = "discrete"),
# * -----------------------------------------------------------------
# * Thrombolysis ----------------------------------------------------
# * -----------------------------------------------------------------
# Thrombolysis ====================================================
# G 16.1-41 Was thrombolysis given
# H 16.1-41 Was thrombolysis given
# G 16.66-68 Thrombolysed?
# H 16.66-68 Thrombolysed?
Thrombolysis = audit_measure(
stem_name = "Thrombolysis",
description = "Thrombolysis",
exclusions = NULL,
numerators = rlang::exprs(
"Yes" = .data[["S2Thrombolysis"]] == "Y",
"No" = .data[["S2Thrombolysis"]] == "N",
"NoUnavailable" = (.data[["S2Thrombolysis"]] == "N") &
(.data[["S2ThrombolysisNoReason"]] == "TNA"),
"NoUnableToScanInTime" = (.data[["S2Thrombolysis"]] == "N") &
(.data[["S2ThrombolysisNoReason"]] == "USQE"),
"NoOutsideServiceHours" = (.data[["S2Thrombolysis"]] == "N") &
(.data[["S2ThrombolysisNoReason"]] == "OTSH"),
"NoReasonUnknown" = (.data[["S2Thrombolysis"]] == "N") &
(.data[["S2ThrombolysisNoReason"]] == "N"),
"NoBut" = .data[["S2Thrombolysis"]] == "NB",
"NoButHaemorrhagic" = (.data[["S2Thrombolysis"]] == "NB") &
bitwAnd(.data[["S2ThrombolysisNoBut"]],
ssnapinterface::tpa_no_but["Haemorrhagic"]),
"NoButImproving" = (.data[["S2Thrombolysis"]] == "NB") &
bitwAnd(.data[["S2ThrombolysisNoBut"]],
ssnapinterface::tpa_no_but["Improving"]),
"NoButComorbidity" = (.data[["S2Thrombolysis"]] == "NB") &
bitwAnd(.data[["S2ThrombolysisNoBut"]],
ssnapinterface::tpa_no_but["Comorbidity"]),
"NoButMedication" = (.data[["S2Thrombolysis"]] == "NB") &
bitwAnd(.data[["S2ThrombolysisNoBut"]],
ssnapinterface::tpa_no_but["Medication"]),
"NoButRefusal" = (.data[["S2Thrombolysis"]] == "NB") &
bitwAnd(.data[["S2ThrombolysisNoBut"]],
ssnapinterface::tpa_no_but["Refusal"]),
"NoButOtherMedical" = (.data[["S2Thrombolysis"]] == "NB") &
bitwAnd(.data[["S2ThrombolysisNoBut"]],
ssnapinterface::tpa_no_but["OtherMedical"]),
"NoButAge" = (.data[["S2Thrombolysis"]] == "NB") &
bitwAnd(.data[["S2ThrombolysisNoBut"]],
ssnapinterface::tpa_no_but["Age"]),
"NoButTooMildSevere" = (.data[["S2Thrombolysis"]] == "NB") &
bitwAnd(.data[["S2ThrombolysisNoBut"]],
ssnapinterface::tpa_no_but["TooMildSevere"]),
"NoButTimeUnknownWakeUp" = (.data[["S2Thrombolysis"]] == "NB") &
bitwAnd(.data[["S2ThrombolysisNoBut"]],
ssnapinterface::tpa_no_but["TimeUnknownWakeUp"]),
"NoButTimeWindow" = (.data[["S2Thrombolysis"]] == "NB") &
bitwAnd(.data[["S2ThrombolysisNoBut"]],
ssnapinterface::tpa_no_but["TimeWindow"])),
new_numerators = tibble::tribble(
~numerator, ~fun, ~descriptor,
"Yes",
rlang::expr(.data[["S2Thrombolysis"]] == "Y"),
"Yes",
"No",
rlang::expr(.data[["S2Thrombolysis"]] == "N"),
"No",
"NoUnavailable", rlang::expr((.data[["S2Thrombolysis"]] == "N") &
(.data[["S2ThrombolysisNoReason"]] == "TNA")),
"No (unavailable)",
"NoUnableToScanInTime", rlang::expr((.data[["S2Thrombolysis"]] == "N") &
(.data[["S2ThrombolysisNoReason"]] == "USQE")),
"No (unable to scan in time)",
"NoOutsideServiceHours", rlang::expr((.data[["S2Thrombolysis"]] == "N") &
(.data[["S2ThrombolysisNoReason"]] == "OTSH")),
"No (outside service hours)",
"NoReasonUnknown", rlang::expr((.data[["S2Thrombolysis"]] == "N") &
(.data[["S2ThrombolysisNoReason"]] == "N")),
"No (reason unknown)",
"NoBut",
rlang::expr( .data[["S2Thrombolysis"]] == "NB"),
"No but",
"NoButHaemorrhagic", rlang::expr((.data[["S2Thrombolysis"]] == "NB") &
bitwAnd(.data[["S2ThrombolysisNoBut"]],
ssnapinterface::tpa_no_but["Haemorrhagic"])),
"No but (haemorrhagic stroke)",
"NoButImproving", rlang::expr((.data[["S2Thrombolysis"]] == "NB") &
bitwAnd(.data[["S2ThrombolysisNoBut"]],
ssnapinterface::tpa_no_but["Improving"])),
"No but (improving)",
"NoButComorbidity", rlang::expr((.data[["S2Thrombolysis"]] == "NB") &
bitwAnd(.data[["S2ThrombolysisNoBut"]],
ssnapinterface::tpa_no_but["Comorbidity"])),
"No but (comorbidity)",
"NoButMedication", rlang::expr((.data[["S2Thrombolysis"]] == "NB") &
bitwAnd(.data[["S2ThrombolysisNoBut"]],
ssnapinterface::tpa_no_but["Medication"])),
"No but (medication)",
"NoButRefusal", rlang::expr((.data[["S2Thrombolysis"]] == "NB") &
bitwAnd(.data[["S2ThrombolysisNoBut"]],
ssnapinterface::tpa_no_but["Refusal"])),
"No but (refusal)",
"NoButOtherMedical", rlang::expr((.data[["S2Thrombolysis"]] == "NB") &
bitwAnd(.data[["S2ThrombolysisNoBut"]],
ssnapinterface::tpa_no_but["OtherMedical"])),
"No but (other medical)",
"NoButAge", rlang::expr((.data[["S2Thrombolysis"]] == "NB") &
bitwAnd(.data[["S2ThrombolysisNoBut"]],
ssnapinterface::tpa_no_but["Age"])),
"No but (age)",
"NoButTooMildSevere", rlang::expr((.data[["S2Thrombolysis"]] == "NB") &
bitwAnd(.data[["S2ThrombolysisNoBut"]],
ssnapinterface::tpa_no_but["TooMildSevere"])),
"No but (too mild)",
"NoButTimeUnknownWakeUp", rlang::expr((.data[["S2Thrombolysis"]] == "NB") &
bitwAnd(.data[["S2ThrombolysisNoBut"]],
ssnapinterface::tpa_no_but["TimeUnknownWakeUp"])),
"No but (unknown onset time or wake-up stroke)",
"NoButTimeWindow", rlang::expr((.data[["S2Thrombolysis"]] == "NB") &
bitwAnd(.data[["S2ThrombolysisNoBut"]],
ssnapinterface::tpa_no_but["TimeWindow"])),
"No but (outside time window)"),
csv_columns = c("S2Thrombolysis",
"S2ThrombolysisNoReason",
"S2ThrombolysisNoBut"),
measure_type = "discrete"),
# ClockStartToThrombolysisMins ====================================
# G 16.1-42-4 Clock start to thrombolysis (mins)
# H 16.1-42-4 Clock start to thrombolysis (mins)
ClockStartToThrombolysisMins = audit_measure(
stem_name = "ClockStartToThrombolysisMins",
description = "Clock start to thrombolysis (mins)",
exclusions = NULL,
numerators = ssnap_field[["ClockStartToThrombolysisMins"]],
new_numerators = ssnap_field[["ClockStartToThrombolysisMins"]],
csv_columns = c("S1PatientClockStartDateTime",
"S2ThrombolysisDateTime"),
measure_type = "continuous"),
# ThrombolysedOnsetToClockStartMins ===============================
# G 16.45 If thrombolysed, time from onset to clock start (mins)
# H 16.45 If thrombolysed, time from onset to clock start (mins)
ThrombolysedOnsetToClockStartMins = audit_measure(
stem_name = "ThrombolysedOnsetToClockStartMins",
description = "If thrombolysed, onset to clock start (mins)",
exclusions = rlang::expr(.data[["S2Thrombolysis"]] != "Y"),
numerators = ssnap_field[["OnsetToArrivalTimeMins"]],
new_numerators = ssnap_field[["OnsetToArrivalTimeMins"]],
csv_columns = c("S1OnsetInHospital",
"S1OnsetDateIsPrecise",
"S1OnsetTimeIsPrecise",
"S1OnsetDateTime",
"S1PatientClockStartDateTime",
"S2Thrombolysis"),
measure_type = "continuous"),
# ThrombolysedClockStartToBrainImagingMins ========================
# G 16.46 If thrombolysed, clock start to brain imaging (mins)
# H 16.46 If thrombolysed, clock start to brain imaging (mins)
ThrombolysedClockStartToBrainImagingMins = audit_measure(
stem_name = "ThrombolysedClockStartToBrainImagingMins",
description = "If thrombolysed, clock start to scan (mins)",
exclusions = rlang::expr(.data[["S2Thrombolysis"]] != "Y"),
numerators = ssnap_field[["ClockStartToBrainImagingMins"]],
new_numerators = ssnap_field[["ClockStartToBrainImagingMins"]],
csv_columns = c("S1PatientClockStartDateTime",
"S2BrainImagingDateTime",
"S2Thrombolysis"),
measure_type = "continuous"),
# ThrombolysedBrainImagingToNeedleMins ============================
# G 16.47 If thrombolysed, brain imaging to needle (mins)
# H 16.47 If thrombolysed, brain imaging to needle (mins)
ThrombolysedBrainImagingToNeedleMins = audit_measure(
stem_name = "ThrombolysedBrainImagingToNeedleMins",
description = "If thrombolysed, brain imaging to needle (mins)",
exclusions = rlang::expr(.data[["S2Thrombolysis"]] != "Y"),
numerators = ssnap_field[["BrainImagingToNeedleMins"]],
new_numerators = ssnap_field[["BrainImagingToNeedleMins"]],
csv_columns = "S2Thrombolysis",
measure_type = "continuous"),
# EligibleFortPAByRCPCriteria =====================================
# G 16.48-52 Eligible for tPA by RCP criteria
# H 16.48-52 Eligible for tPA by RCP criteria
EligibleFortPAByRCPCriteria = audit_measure(
stem_name = "EligibleFortPAByRCPCriteria",
description = "Eligible for tPA by RCP criteria",
exclusions = NULL,
numerators = rlang::exprs(
"Eligible" = !! ssnap_field[["EligibleFortPAByRCPCriteria"]],
"NotEligible" =
!(!! ssnap_field[["EligibleFortPAByRCPCriteria"]])),
new_numerators = tibble::tribble(
~numerator, ~fun, ~descriptor,
"Eligible",
rlang::expr(!! ssnap_field[["EligibleFortPAByRCPCriteria"]]),
"Eligible",
"NotEligible",
rlang::expr(!(!! ssnap_field[["EligibleFortPAByRCPCriteria"]])),
"Not eligible"),
csv_columns = c("S1OnsetInHospital",
"S1OnsetTimeIsPrecise",
"S1OnsetDateTime",
"S1PatientClockStartDateTime",
"S1AgeOnArrival"),
measure_type = "discrete"),
# tPAIfMeetsRCPCriteria ===========================================
# G 16.53-57 If eligible for tPA, was thrombolysis received?
# H 16.53-57 If eligible for tPA, was thrombolysis received?
tPAIfMeetsRCPCriteria = audit_measure(
stem_name = "tPAIfMeetsRCPCriteria",
description = "Thrombolysis meeting RCP criteria",
exclusions = rlang::expr(
!! ssnap_field[["ThrombolysisNoButConsistent"]] != 0),
numerators = rlang::exprs(
"Yes" = .data[["S2Thrombolysis"]] == "Y",
"No" = .data[["S2Thrombolysis"]] != "Y"),
new_numerators = tibble::tribble(
~numerator, ~fun, ~descriptor,
"Yes",
rlang::expr(.data[["S2Thrombolysis"]] == "Y"),
"Yes",
"No",
rlang::expr(.data[["S2Thrombolysis"]] != "Y"),
"No"),
csv_columns = c("S2Thrombolysis",
"S2ThrombolysisNoBut",
"S1AgeOnArrival",
"S1OnsetTimeIsPrecise",
"S1OnsetInHospital",
"S1OnsetDateTime",
"S1PatientClockStartDateTime",
"S2NihssArrival",
"S1OnsetDateIsPrecise"),
measure_type = "discrete"),
# tPAIfDoesntMeetRCPCriteria ======================================
# G 16.58-62 If not eligible for tPA, was thrombolysis received?
# H 16.58-62 If not eligible for tPA, was thrombolysis received?
tPAIfDoesntMeetRCPCriteria = audit_measure(
stem_name = "tPAIfDoesntMeetRCPCriteria",
description = "If not eligible for tPA, was tPA given?",
exclusions = rlang::expr(
!! ssnap_field[["ThrombolysisNoButConsistent"]] == 0),
numerators = rlang::exprs(
"Yes" = .data[["S2Thrombolysis"]] == "Y",
"No" = .data[["S2Thrombolysis"]] != "Y"),
new_numerators = tibble::tribble(
~numerator, ~fun, ~descriptor,
"Yes",
rlang::expr(.data[["S2Thrombolysis"]] == "Y"),
"Yes",
"No",
rlang::expr(.data[["S2Thrombolysis"]] != "Y"),
"No"),
csv_columns = c("S2Thrombolysis",
"S2ThrombolysisNoBut",
"S1AgeOnArrival",
"S1OnsetTimeIsPrecise",
"S1OnsetInHospital",
"S1OnsetDateTime",
"S1PatientClockStartDateTime",
"S2NihssArrival",
"S1OnsetDateIsPrecise"),
measure_type = "discrete"),
# EligibleOrThrombolysed ==========================================
# G 16.63-65 Was tPA given (measuring either those eligible by RCP
# criteria or those thrombolysed outside RCP criteria
# H 16.63-65 Was tPA given (measuring either those eligible by RCP
# criteria or those thrombolysed outside RCP criteria
EligibleOrThrombolysed = audit_measure(
stem_name = "EligibleOrThrombolysed",
description = paste0("Was tPA given (measuring either those ",
"eligible by RCP criteria or those thrombolysed outside RCP ",
"criteria"),
exclusions = rlang::expr(
(!(!! ssnap_field[["EligibleFortPAByRCPCriteria"]])) &
(.data[["S2Thrombolysis"]] != "Y")),
numerators = rlang::exprs(
"Yes" = .data[["S2Thrombolysis"]] == "Y",
"No" = .data[["S2Thrombolysis"]] != "Y"),
new_numerators = tibble::tribble(
~numerator, ~fun, ~descriptor,
"Yes",
rlang::expr(.data[["S2Thrombolysis"]] == "Y"),
"Yes",
"No",
rlang::expr(.data[["S2Thrombolysis"]] != "Y"),
"No"),
csv_columns = c("S2Thrombolysis",
"S1OnsetInHospital",
"S1OnsetTimeIsPrecise",
"S1OnsetDateTime",
"S1PatientClockStartDateTime",
"S1AgeOnArrival",
"S2Thrombolysis"),
measure_type = "discrete"),
# EligibleExcludingNoButs =========================================
# G 16.69-71 If eligible, patient thrombolysed (excludes "no but"s)
# H 16.69-71 If eligible, patient thrombolysed (excludes "no but"s)
EligibleExcludingNoButs = audit_measure(
stem_name = "EligibleExcludingNoButs",
description = paste0("If eligible, patient thrombolysed ",
"(excludes 'no but's)"),
exclusions = rlang::expr(
(!(!! ssnap_field[["EligibleFortPAByRCPCriteria"]])) |
(.data[["S2Thrombolysis"]] == "NB")),
numerators = rlang::exprs(
"Yes" = .data[["S2Thrombolysis"]] == "Y",
"No" = .data[["S2Thrombolysis"]] != "Y"),
new_numerators = tibble::tribble(
~numerator, ~fun, ~descriptor,
"Yes",
rlang::expr(.data[["S2Thrombolysis"]] == "Y"),
"Yes",
"No",
rlang::expr(.data[["S2Thrombolysis"]] != "Y"),
"No"),
csv_columns = c("S2Thrombolysis",
"S1OnsetInHospital",
"S1OnsetTimeIsPrecise",
"S1OnsetDateTime",
"S1PatientClockStartDateTime",
"S1AgeOnArrival",
"S2Thrombolysis"),
measure_type = "discrete"),
# tPAWithin1hr ====================================================
# G 16.72-74 Thrombolysis given within 1 hour
# H 16.72-74 Thrombolysis given within 1 hour
tPAWithin1hr = audit_measure(
stem_name = "tPAWithin1hr",
description = "Thrombolysis within 1 hour",
exclusions = rlang::expr(.data[["S2Thrombolysis"]] != "Y"),
numerators = rlang::expr(
!! ssnap_field[["ClockStartToThrombolysisMins"]] <= 60),
new_numerators = rlang::expr(
!! ssnap_field[["ClockStartToThrombolysisMins"]] <= 60),
csv_columns = c("S1PatientClockStartDateTime",
"S2ThrombolysisDateTime",
"S2Thrombolysis"),
measure_type = "discrete"),
# tPAAndSUIn4hrs ==================================================
# G 16.75.1-77.1 Thrombolysis if needed and stroke unit within 4hrs
# H 16.75.1-77.1 Thrombolysis if needed and stroke unit within 4hrs
tPAAndSUIn4hrs = audit_measure(
stem_name = "tPAAndSUIn4hrs",
description = "Thrombolysis and stroke unit in 4 hours",
exclusions = rlang::expr( (.data[["S1FirstWard"]] == "ICH") |
(!is.na(.data[["S2IAI"]]) & .data[["S2IAI"]])),
numerators = rlang::expr( (.data[["S2Thrombolysis"]] != "N") &
!! ssnap_field[["ClockStartToFirstStrokeUnitMins"]]
<= (4 * 60)),
new_numerators = rlang::expr( (.data[["S2Thrombolysis"]] != "N") &
!! ssnap_field[["ClockStartToFirstStrokeUnitMins"]]
<= (4 * 60)),
csv_columns = c("S2Thrombolysis",
"S1PatientClockStartDateTime",
"S1FirstStrokeUnitArrivalDateTime",
"S1FirstWard",
"S2IAI"),
measure_type = "discrete"),
# * -----------------------------------------------------------------
# * Thrombolysis complications --------------------------------------
# * -----------------------------------------------------------------
# ThrombolysisComplications =========================================
# G 17.1-3 Patient had complications following thrombolysis
# H 17.1-3 Patient had complications following thrombolysis
ThrombolysisComplications = audit_measure(
stem_name = "ThrombolysisComplications",
description = "Complications following thrombolysis",
exclusions = rlang::expr(.data[["S2Thrombolysis"]] != "Y"),
numerators = rlang::expr(.data[["S2ThrombolysisComplications"]]
>= 0),
new_numerators = rlang::expr(.data[["S2ThrombolysisComplications"]]
>= 0),
csv_columns = c("S2ThrombolysisComplications",
"S2Thrombolysis"),
measure_type = "discrete"),
# ThrombolysisComplicationsGrouped ==================================
# G 17.4-12 Number of each type of thrombolysis complication
# H 17.4-12 Number of each type of thrombolysis complication
ThrombolysisComplicationsGrouped = audit_measure(
stem_name = "ThrombolysisComplications",
description = "Thrombolysis complications grouped by type",
exclusions = rlang::expr(.data[["S2Thrombolysis"]] != "Y"),
numerators = rlang::exprs(
"SymptomaticICH" =
bitwAnd(.data[["S2ThrombolysisComplications"]],
ssnapinterface::tpa_complications["SymptomaticICH"]) ==
ssnapinterface::tpa_complications["SymptomaticICH"],
"Angiooedema" =
bitwAnd(.data[["S2ThrombolysisComplications"]],
ssnapinterface::tpa_complications["Angiooedema"]) ==
ssnapinterface::tpa_complications["Angiooedema"],
"ExtracranialBleed" =
bitwAnd(.data[["S2ThrombolysisComplications"]],
ssnapinterface::tpa_complications["ExtracranialBleed"]) ==
ssnapinterface::tpa_complications["ExtracranialBleed"],
"Other" = bitwAnd(.data[["S2ThrombolysisComplications"]],
ssnapinterface::tpa_complications["Other"]) ==
ssnapinterface::tpa_complications["Other"]),
new_numerators = tibble::tribble(
~numerator, ~fun, ~descriptor,
"SymptomaticICH",
rlang::expr(bitwAnd(.data[["S2ThrombolysisComplications"]],
ssnapinterface::tpa_complications["SymptomaticICH"]) ==
ssnapinterface::tpa_complications["SymptomaticICH"]),
"Symptomatic intracerebral haemorrhage",
"Angiooedema",
rlang::expr(bitwAnd(.data[["S2ThrombolysisComplications"]],
ssnapinterface::tpa_complications["Angiooedema"]) ==
ssnapinterface::tpa_complications["Angiooedema"]),
"Angiooedema",
"ExtracranialBleed",
rlang::expr(bitwAnd(.data[["S2ThrombolysisComplications"]],
ssnapinterface::tpa_complications["ExtracranialBleed"]) ==
ssnapinterface::tpa_complications["ExtracranialBleed"]),
"Extracranial bleed",
"Other",
rlang::expr(bitwAnd(.data[["S2ThrombolysisComplications"]],
ssnapinterface::tpa_complications["Other"]) ==
ssnapinterface::tpa_complications["Other"]),
"Other"),
csv_columns = c("S2ThrombolysisComplications",
"S2Thrombolysis"),
measure_type = "discrete"),
# * -----------------------------------------------------------------
# * NIHSS following thrombolysis ------------------------------------
# * -----------------------------------------------------------------
# Nihss24HrsKnown =================================================
# G 18.1-3 NIHSS at 24hrs is known
# H 18.1-3 NIHSS at 24hrs is known
# C 3.1-3 NIHSS at 24hrs is known
Nihss24HrsKnown = audit_measure(
stem_name = "Nihss24HrsKnown",
description = "NIHSS at 24 hrs known",
exclusions = rlang::expr(!( (.data[["S2Thrombolysis"]] == "Y") |
.data[["S2IAI"]])),
numerators = rlang::expr(!.data[["S2Nihss24HrsNK"]]),
new_numerators = rlang::expr(!.data[["S2Nihss24HrsNK"]]),
csv_columns = c("S2Nihss24HrsNK",
"S2Thrombolysis",
"S2IAI"),
measure_type = "discrete"),
# Nihss24hrsSeverity ==============================================
# G 18.4-14 Severity groups of NIHSS 24 hours after thrombolysis
# H 18.4-14 Severity groups of NIHSS 24 hours after thrombolysis
Nihss24hrsSeverity = audit_measure(
stem_name = "Nihss24hrsSeverity",
description = "NIHSS Severity at 24hrs",
exclusions = rlang::expr( (.data[["S2Thrombolysis"]] != "Y") |
.data[["S2Nihss24HrsNK"]]),
numerators = rlang::exprs(
"0" = .data[["S2Nihss24Hrs"]] == 0,
"1To4" = dplyr::between(.data[["S2Nihss24Hrs"]], 1, 4),
"5To15" = dplyr::between(.data[["S2Nihss24Hrs"]], 5, 15),
"16To20" = dplyr::between(.data[["S2Nihss24Hrs"]], 16, 20),
"21To42" = dplyr::between(.data[["S2Nihss24Hrs"]], 21, 42)),
new_numerators = tibble::tribble(
~numerator, ~fun, ~descriptor,
"0",
rlang::expr(.data[["S2Nihss24Hrs"]] == 0),
"0",
"1To4",
rlang::expr(dplyr::between(.data[["S2Nihss24Hrs"]], 1, 4)),
"1 to 4",
"5To15",
rlang::expr(dplyr::between(.data[["S2Nihss24Hrs"]], 5, 15)),
"5 to 15",
"16To20",
rlang::expr(dplyr::between(.data[["S2Nihss24Hrs"]], 16, 20)),
"16 to 20",
"21To42",
rlang::expr(dplyr::between(.data[["S2Nihss24Hrs"]], 21, 42)),
"21 to 42"),
csv_columns = c("S2Nihss24Hrs",
"S2Thrombolysis",
"S2Nihss24HrsNK"),
measure_type = "discrete"),
# ChangeInNIHSSAt24hrs ============================================
# G 18.15-21 Change in NIHSS from arrival to 24 hours after
# thrombolysis
# H 18.15-21 Change in NIHSS from arrival to 24 hours after
# thrombolysis
ChangeInNIHSSAt24hrs = audit_measure(
stem_name = "ChangeInNIHSSAt24hrs",
description = "Change in NIHSS at 24hrs",
exclusions = rlang::expr( (.data[["S2Thrombolysis"]] != "Y") |
.data[["S2Nihss24HrsNK"]]),
numerators = rlang::exprs(
"Improved" = .data[["S2Nihss24Hrs"]] <
.data[["S2NihssArrival"]],
"NoChange" = .data[["S2Nihss24Hrs"]] ==
.data[["S2NihssArrival"]],
"Worsened" = .data[["S2Nihss24Hrs"]] >
.data[["S2NihssArrival"]]),
new_numerators = tibble::tribble(
~numerator, ~fun, ~descriptor,
"Improved",
rlang::expr(.data[["S2Nihss24Hrs"]] <
.data[["S2NihssArrival"]]),
"Improved",
"NoChange",
rlang::expr(.data[["S2Nihss24Hrs"]] ==
.data[["S2NihssArrival"]]),
"No change",
"Worsened",
rlang::expr(.data[["S2Nihss24Hrs"]] >
.data[["S2NihssArrival"]]),
"Worsened"),
csv_columns = c("S2Nihss24Hrs",
"S2NihssArrival",
"S2Thrombolysis",
"S2Nihss24HrsNK"),
measure_type = "discrete"),
# Nihss24hrsScoreChange ===========================================
# G 18.22-44 Change in NIHSS from arrival to 24 hours after
# thrombolysis
# H 18.22-44 Change in NIHSS from arrival to 24 hours after
# thrombolysis
Nihss24hrsScoreChange = audit_measure(
stem_name = "Nihss24hrsScoreChange",
description = "Change in NIHSS score at 24 hrs",
exclusions = rlang::expr( (.data[["S2Thrombolysis"]] != "Y") |
.data[["S2Nihss24HrsNK"]]),
numerators = rlang::exprs(
"Minus13OrMore" = (.data[["S2NihssArrival"]] -
.data[["S2Nihss24Hrs"]]) < -12,
"Minus9To12" = dplyr::between( (.data[["S2NihssArrival"]] -
.data[["S2Nihss24Hrs"]]), -12, -9),
"Minus5To8" = dplyr::between( (.data[["S2NihssArrival"]] -
.data[["S2Nihss24Hrs"]]), -8, -5),
"Minus3To4" = dplyr::between( (.data[["S2NihssArrival"]] -
.data[["S2Nihss24Hrs"]]), -4, -3),
"Minus1To2" = dplyr::between( (.data[["S2NihssArrival"]] -
.data[["S2Nihss24Hrs"]]), -2, -1),
"NoChange" = .data[["S2NihssArrival"]] ==
.data[["S2Nihss24Hrs"]],
"1To2" = dplyr::between( (.data[["S2NihssArrival"]] -
.data[["S2Nihss24Hrs"]]), 1, 2),
"3To4" = dplyr::between( (.data[["S2NihssArrival"]] -
.data[["S2Nihss24Hrs"]]), 3, 4),
"5To8" = dplyr::between( (.data[["S2NihssArrival"]] -
.data[["S2Nihss24Hrs"]]), 5, 8),
"9To12" = dplyr::between( (.data[["S2NihssArrival"]] -
.data[["S2Nihss24Hrs"]]), 9, 12),
"13OrMore" = (.data[["S2NihssArrival"]] -
.data[["S2Nihss24Hrs"]]) > 12),
new_numerators = tibble::tribble(
~numerator, ~fun, ~descriptor,
"Minus13OrMore",
rlang::expr((.data[["S2NihssArrival"]] -
.data[["S2Nihss24Hrs"]]) < -12),
"-13 or better",
"Minus9To12",
rlang::expr(dplyr::between( (.data[["S2NihssArrival"]] -
.data[["S2Nihss24Hrs"]]), -12, -9)),
"-9 to -12",
"Minus5To8",
rlang::expr(dplyr::between( (.data[["S2NihssArrival"]] -
.data[["S2Nihss24Hrs"]]), -8, -5)),
"-5 to -8",
"Minus3To4",
rlang::expr(dplyr::between( (.data[["S2NihssArrival"]] -
.data[["S2Nihss24Hrs"]]), -4, -3)),
"-3 to -4",
"Minus1To2",
rlang::expr(dplyr::between( (.data[["S2NihssArrival"]] -
.data[["S2Nihss24Hrs"]]), -2, -1)),
"-2 to -1",
"NoChange",
rlang::expr(.data[["S2NihssArrival"]] == .data[["S2Nihss24Hrs"]]),
"No change",
"1To2",
rlang::expr(dplyr::between( (.data[["S2NihssArrival"]] -
.data[["S2Nihss24Hrs"]]), 1, 2)),
"+1 to +2",
"3To4",
rlang::expr(dplyr::between( (.data[["S2NihssArrival"]] -
.data[["S2Nihss24Hrs"]]), 3, 4)),
"+3 to +4",
"5To8",
rlang::expr(dplyr::between( (.data[["S2NihssArrival"]] -
.data[["S2Nihss24Hrs"]]), 5, 8)),
"+5 to +8",
"9To12",
rlang::expr(dplyr::between( (.data[["S2NihssArrival"]] -
.data[["S2Nihss24Hrs"]]), 9, 12)),
"+9 to +12",
"13OrMore",
rlang::expr((.data[["S2NihssArrival"]] -
.data[["S2Nihss24Hrs"]]) > 12),
"+13 or worse"),
csv_columns = c("S2NihssArrival",
"S2Nihss24Hrs",
"S2Thrombolysis",
"S2Nihss24HrsNK"),
measure_type = "discrete"),
# * -----------------------------------------------------------------
# * Onset to arrival ------------------------------------------------
# * -----------------------------------------------------------------
# G 19.1-11 Days from onset to arrival
# H 19.1-11 Days from onset to arrival
DaysOnsetToArrival = audit_measure(
stem_name = "DaysOnsetToArrival",
description = "Days from onset to arrival",
exclusions = rlang::expr(is.na(.data[["S1OnsetDateIsPrecise"]]) |
.data[["S1OnsetInHospital"]]),
numerators = rlang::exprs(
"SameDay" = !! ssnap_field[["DaysOnsetToArrival"]] == 0,
"PreviousDay" = !! ssnap_field[["DaysOnsetToArrival"]] == 1,
"2Days" = !! ssnap_field[["DaysOnsetToArrival"]] == 2,
"3To7Days" = dplyr::between(
!! ssnap_field[["DaysOnsetToArrival"]], 3, 7),
"Over7Days" = !! ssnap_field[["DaysOnsetToArrival"]] > 7),
new_numerators = tibble::tribble(
~numerator, ~fun, ~descriptor,
"SameDay",
rlang::expr(!! ssnap_field[["DaysOnsetToArrival"]] == 0),
"Same day",
"PreviousDay",
rlang::expr(!! ssnap_field[["DaysOnsetToArrival"]] == 1),
"Previous day",
"2Days",
rlang::expr(!! ssnap_field[["DaysOnsetToArrival"]] == 2),
"2 days",
"3To7Days",
rlang::expr(dplyr::between(
!! ssnap_field[["DaysOnsetToArrival"]], 3, 7)),
"3 to 7 days",
"Over7Days",
rlang::expr(!! ssnap_field[["DaysOnsetToArrival"]] > 7),
"Over 7 days"),
csv_columns = c("S1FirstArrivalDateTime",
"S1OnsetDateTime",
"S1OnsetDateIsPrecise",
"S1OnsetInHospital"),
measure_type = "discrete"),
# * Thrombectomy ----------------------------------------------------
# * -----------------------------------------------------------------
# Thrombectomy ====================================================
# G 20.1-3 Thrombectomy performed
# H 20.1-3 Thrombectomy performed
Thrombectomy = audit_measure(
stem_name = "Thrombectomy",
description = "Thrombectomy performed",
exclusions = NULL,
numerators = rlang::expr(.data[["S2IAI"]]),
new_numerators = rlang::expr(.data[["S2IAI"]]),
csv_columns = "S2IAI",
measure_type = "discrete"),
# OnsetToIAIPunctureMins ==========================================
# G 20.4-6 Onset to groin puncture (mins)
# H 20.4-6 Onset to groin puncture (mins)
OnsetToIAIPunctureMins = audit_measure(
stem_name = "OnsetToIAIPunctureMins",
description = "Onset to groin puncture (mins)",
exclusions = NULL,
numerators = ssnap_field[["OnsetToIAIPunctureMins"]],
new_numerators = ssnap_field[["OnsetToIAIPunctureMins"]],
csv_columns = c("S1OnsetDateTime",
"S2IAIArterialPunctureDateTime"),
measure_type = "continuous"),
# OnsetToIAICompletionMins ========================================
# G 20.7-9 Onset to thrombectomy completion (mins)
# H 20.7-9 Onset to thrombectomy completion (mins)
OnsetToIAICompletionMins = audit_measure(
stem_name = "OnsetToIAICompletionMins",
description = "Onset to thrombectomy completion (mins)",
exclusions = NULL,
numerators = ssnap_field[["OnsetToIAICompletionMins"]],
new_numerators = ssnap_field[["OnsetToIAICompletionMins"]],
csv_columns = c("S1OnsetDateTime",
"S2IAIEndOfProcedureDateTime"),
measure_type = "continuous"),
# ClockStartToIAIPunctureMins =====================================
# G 20.10-12 Clock start to groin puncture (mins)
# G 20.10-12 Clock start to groin puncture (mins)
ClockStartToIAIPunctureMins = audit_measure(
stem_name = "ClockStartToIAIPunctureMins",
description = "Clock start to groin puncture (mins)",
exclusions = NULL,
numerators = ssnap_field[["ClockStartToIAIPunctureMins"]],
new_numerators = ssnap_field[["ClockStartToIAIPunctureMins"]],
csv_columns = c("S1PatientClockStartDateTime",
"S2IAIArterialPunctureDateTime"),
measure_type = "continuous"),
# PunctureToDeploymentMins ========================================
# G 20.13-15 Groin puncture to stent retriever deployment (mins)
# H 20.13-15 Groin puncture to stent retriever deployment (mins)
PunctureToDeploymentMins = audit_measure(
stem_name = "PunctureToDeploymentMins",
description = "Groin puncture to stent deployment (mins)",
exclusions = NULL,
numerators = ssnap_field[["PunctureToDeploymentMins"]],
new_numerators = ssnap_field[["PunctureToDeploymentMins"]],
csv_columns = c("S2IAIArterialPunctureDateTime",
"S2IAIThrombectomyAspirationDeviceDateTime"),
measure_type = "continuous"),
# PunctureToIAICompletionMins =====================================
# G 20.16-18 Groin puncture to procedure completion (mins)
# H 20.16-18 Groin puncture to procedure completion (mins)
PunctureToIAICompletionMins = audit_measure(
stem_name = "PunctureToIAICompletionMins",
description = "Groin puncture to procedure completion (mins)",
exclusions = NULL,
numerators = ssnap_field[["PunctureToIAICompletionMins"]],
new_numerators = ssnap_field[["PunctureToIAICompletionMins"]],
csv_columns = c("S2IAIArterialPunctureDateTime",
"S2IAIEndOfProcedureDateTime"),
measure_type = "continuous"),
# * -----------------------------------------------------------------
# * NIHSS after Thrombectomy ----------------------------------------
# * -----------------------------------------------------------------
# G 21.1-3 NIHSS 24hrs after thrombectomy is known
# H 21.1-3 NIHSS 24hrs after thrombectomy is known
Nihss24hrsAfterIAIKnown = audit_measure(
stem_name = "Thrombectomy",
description = "Thrombectomy performed",
exclusions = rlang::expr(!.data[["S2IAI"]]),
numerators = rlang::expr(.data[["S2Nihss24HrsNK"]]),
new_numerators = rlang::expr(.data[["S2Nihss24HrsNK"]]),
csv_columns = c("S2Nihss24HrsNK",
"S2IAI"),
measure_type = "discrete"),
# * -----------------------------------------------------------------
# * Occupational therapy --------------------------------------------
# * -----------------------------------------------------------------
# OccTherApplicable ===============================================
# J 3.1-3 Applicability for patients to receive occupational
# therapy at least once during their inpatient stay
OccTherApplicable = audit_measure(
stem_name = "OccTherApplicable",
description = "Occupational Therapy applicability",
exclusions = NULL,
numerators = rlang::expr(.data[["S4OccTher"]]),
new_numerators = rlang::expr(.data[["S4OccTher"]]),
csv_columns = "S4OccTher",
measure_type = "discrete"),
# PCOccTherDays ===================================================
# J 3.4 Percentage of days of occupational therapy delivered of
# those where it is needed
PCOccTherDays = audit_measure(
stem_name = "PCOccTherDays",
description = "Percent of days occupational therapy received",
exclusions = NULL,
numerators = ssnap_field[["PCOccTherDays"]],
new_numerators = ssnap_field[["PCOccTherDays"]],
csv_columns = c("S4OccTher",
"S4OccTherDays",
"S1TeamClockStartDateTime",
"S4OccTherEndDate"),
measure_type = "continuous"),
# OccTherMinutes ==================================================
# J 3.5-7 Minutes of occupational therapy received
OccTherMinutes = audit_measure(
stem_name = "OccTherMinutes",
description = "Minutes of occupational therapy received",
exclusions = NULL,
numerators = ssnap_field[["OccTherMinutesPerDay"]],
new_numerators = ssnap_field[["PCOccTherDays"]],
csv_columns = c("S4OccTherDays",
"S4OccTherMinutes"),
measure_type = "continuous"),
# OccTherComplianceMinutes ========================================
# J 3.8 Average number of minutes of OT per day across all patients
# (Proportion of patients applicable for OT*Median percentage of
# days in hospital that OT is received*Median number of minutes per
# day on which OT is received)
OccTherComplianceMinutes = audit_measure(
stem_name = "OccTherComplianceMinutes",
description = "Minutes of occupational therapy received",
exclusions = NULL,
numerators = rlang::expr( (.data[["S4OccTher"]] / 100) *
!! ssnap_field[["OccTherMinutesPerDay"]] *
(!! ssnap_field[["PCOccTherDays"]] / 100)),
new_numerators = rlang::expr( (.data[["S4OccTher"]] / 100) *
!! ssnap_field[["OccTherMinutesPerDay"]] *
(!! ssnap_field[["PCOccTherDays"]] / 100)),
csv_columns = c("S4OccTher",
"S4OccTherDays",
"S4OccTherMinutes",
"S1TeamClockStartDateTime",
"S4OccTherEndDate"),
measure_type = "continuous"),
# OccTherComplianceTarget =========================================
# J 3.9 Occupational therapy compliance target
OccTherComplianceTarget = audit_measure(
stem_name = "OccTherComplianceTarget",
description = "Occupational therapy compliance target",
exclusions = NULL,
numerators = rlang::expr(0.8 * 45 * 5 / 7),
new_numerators = rlang::expr(0.8 * 45 * 5 / 7),
measure_type = "continuous"),
# OccTherCompliance ===============================================
# J 3.10 Occupational therapy compliance
OccTherCompliance = audit_measure(
stem_name = "OccTherCompliance",
description = "Occupational therapy compliance",
exclusions = NULL,
numerators = rlang::expr(
( (.data[["S4OccTher"]] / 100) *
!! ssnap_field[["OccTherMinutesPerDay"]] *
(!! ssnap_field[["PCOccTherDays"]] / 100)) /
(0.8 * 45 * 5 / 7) * 100),
new_numerators = rlang::expr(
( (.data[["S4OccTher"]] / 100) *
!! ssnap_field[["OccTherMinutesPerDay"]] *
(!! ssnap_field[["PCOccTherDays"]] / 100)) /
(0.8 * 45 * 5 / 7) * 100),
csv_columns = c("S4OccTher",
"S4OccTherDays",
"S4OccTherMinutes",
"S1TeamClockStartDateTime",
"S4OccTherEndDate"),
measure_type = "continuous"),
# OccTherEquivalentMinutes ========================================
# J 3.11 Average number of minutes of OT per day as equivalent to
# 45 minutes on 5 days per week for 80% of patients
OccTherEquivalentMinutes = audit_measure(
stem_name = "OccTherEquivalentMinutes",
description = "Occupational therapy equivalent minutes",
exclusions = NULL,
numerators = rlang::expr( ( (.data[["S4OccTher"]] / 100) *
!! ssnap_field[["OccTherMinutesPerDay"]] *
(!! ssnap_field[["PCOccTherDays"]] / 100)) /
(0.8 * 5 / 7)),
new_numerators = rlang::expr( ( (.data[["S4OccTher"]] / 100) *
!! ssnap_field[["OccTherMinutesPerDay"]] *
(!! ssnap_field[["PCOccTherDays"]] / 100)) /
(0.8 * 5 / 7)),
csv_columns = c("S4OccTher",
"S4OccTherDays",
"S4OccTherMinutes",
"S1TeamClockStartDateTime",
"S4OccTherEndDate"),
measure_type = "continuous"),
# TODO J 3.12-18 for All Teams
# * -----------------------------------------------------------------
# * Physiotherapy ---------------------------------------------------
# * -----------------------------------------------------------------
# PhysioApplicable ===============================================
# J 4.1-3 Applicability for patients to receive physiotherapy at
# least once during their inpatient stay
PhysioApplicable = audit_measure(
stem_name = "PhysioApplicable",
description = "Physiotherapy applicability",
exclusions = NULL,
numerators = rlang::expr(.data[["S4Physio"]]),
new_numerators = rlang::expr(.data[["S4Physio"]]),
csv_columns = "S4Physio",
measure_type = "discrete"),
# PCPhysioDays ====================================================
# J 4.4 Percentage of days of physiotherapy delivered of those
# where it is needed
PCPhysioDays = audit_measure(
stem_name = "PCPhysioDays",
description = "Percent of days physio received",
exclusions = NULL,
numerators = ssnap_field[["PCPhysioDays"]],
new_numerators = ssnap_field[["PCPhysioDays"]],
csv_columns = c("S4Physio",
"S4PhysioDays",
"S1TeamClockStartDateTime",
"S4PhysioEndDate"),
measure_type = "continuous"),
# PhysioMinutes ==================================================
# J 4.5-7 Minutes of physiotherapy received
PhysioMinutes = audit_measure(
stem_name = "PhysioMinutes",
description = "Minutes of physio received",
exclusions = NULL,
numerators = ssnap_field[["PhysioMinutesPerDay"]],
new_numerators = ssnap_field[["PhysioMinutesPerDay"]],
csv_columns = c("S4PhysioDays",
"S4PhysioMinutes"),
measure_type = "continuous"),
# PhysioComplianceMinutes =========================================
# J 4.8 Average number of minutes of OT per day across all patients
# (Proportion of patients applicable for PT*Median percentage of
# days in hospital that PT is received*Median number of minutes per
# day on which PT is received)
PhysioComplianceMinutes = audit_measure(
stem_name = "PhysioComplianceMinutes",
description = "Minutes of physiotherapy received",
exclusions = NULL,
numerators = rlang::expr( (.data[["S4Physio"]] / 100) *
!! ssnap_field[["PhysioMinutesPerDay"]] *
(!! ssnap_field[["PCPhysioDays"]] / 100)),
new_numerators = rlang::expr( (.data[["S4Physio"]] / 100) *
!! ssnap_field[["PhysioMinutesPerDay"]] *
(!! ssnap_field[["PCPhysioDays"]] / 100)),
csv_columns = c("S4Physio",
"S4PhysioDays",
"S4PhysioMinutes",
"S1TeamClockStartDateTime",
"S4PhysioEndDate"),
measure_type = "continuous"),
# PhysioComplianceTarget ==========================================
# J 4.9 Physiotherapy compliance target
PhysioComplianceTarget = audit_measure(
stem_name = "PhysioComplianceTarget",
description = "Physiotherapy compliance target",
exclusions = NULL,
numerators = rlang::expr(0.85 * 45 * 5 / 7),
new_numerators = rlang::expr(0.85 * 45 * 5 / 7),
measure_type = "continuous"),
# PhysioCompliance ================================================
# J 4.10 Physiotherapy compliance
PhysioCompliance = audit_measure(
stem_name = "PhysioCompliance",
description = "Physiotherapy compliance",
exclusions = NULL,
numerators = rlang::expr(
( (.data[["S4Physio"]] / 100) *
!! ssnap_field[["PhysioMinutesPerDay"]] *
(!! ssnap_field[["PCPhysioDays"]] / 100)) /
(0.85 * 45 * 5 / 7) * 100),
new_numerators = rlang::expr(
( (.data[["S4Physio"]] / 100) *
!! ssnap_field[["PhysioMinutesPerDay"]] *
(!! ssnap_field[["PCPhysioDays"]] / 100)) /
(0.85 * 45 * 5 / 7) * 100),
csv_columns = c("S4Physio",
"S4PhysioDays",
"S4PhysioMinutes",
"S1TeamClockStartDateTime",
"S4PhysioEndDate"),
measure_type = "continuous"),
# PhysioEquivalentMinutes ========================================
# J 4.11 Average number of minutes of PT per day as equivalent to
# 45 minutes on 5 days per week for 85% of patients
PhysioEquivalentMinutes = audit_measure(
stem_name = "PhysioEquivalentMinutes",
description = "Physiotherapy equivalent minutes",
exclusions = NULL,
numerators = rlang::expr( ( (.data[["S4Physio"]] / 100) *
!! ssnap_field[["PhysioMinutesPerDay"]] *
(!! ssnap_field[["PCPhysioDays"]] / 100)) /
(0.85 * 5 / 7)),
new_numerators = rlang::expr( ( (.data[["S4Physio"]] / 100) *
!! ssnap_field[["PhysioMinutesPerDay"]] *
(!! ssnap_field[["PCPhysioDays"]] / 100)) /
(0.85 * 5 / 7)),
csv_columns = c("S4Physio",
"S4PhysioDays",
"S4PhysioMinutes",
"S1TeamClockStartDateTime",
"S4PhysioEndDate"),
measure_type = "continuous"),
# TODO J 4.12-18 for All Teams
# * -----------------------------------------------------------------
# * Speech and language therapy -------------------------------------
# * -----------------------------------------------------------------
# SpeechLangApplicable ============================================
# J 5.1-3 Applicability for patients to receive speech and language
# therapy at least once during their inpatient stay
SpeechLangApplicable = audit_measure(
stem_name = "SpeechLangApplicable",
description = "Speech and language Therapy applicability",
exclusions = NULL,
numerators = rlang::expr(.data[["S4SpeechLang"]]),
new_numerators = rlang::expr(.data[["S4SpeechLang"]]),
csv_columns = "S4SpeechLang",
measure_type = "discrete"),
# PCSpeechLangDays ================================================
# J 5.4 Percentage of days of physiotherapy delivered of those
# where it is needed
PCSpeechLangDays = audit_measure(
stem_name = "PCSpeechLangDays",
description = "Percent of days speech and language received",
exclusions = NULL,
numerators = ssnap_field[["PCSpeechLangDays"]],
new_numerators = ssnap_field[["PCSpeechLangDays"]],
csv_columns = c("S4SpeechLang",
"S4SpeechLangDays",
"S1TeamClockStartDateTime",
"S4SpeechLangEndDate"),
measure_type = "continuous"),
# SpeechLangMinutes ===============================================
# J 5.5-7 Minutes of physiotherapy received
SpeechLangMinutes = audit_measure(
stem_name = "SpeechLangMinutes",
description = "Minutes of speech and language therapy received",
exclusions = NULL,
numerators = ssnap_field[["SpeechLangMinutesPerDay"]],
new_numerators = ssnap_field[["SpeechLangMinutesPerDay"]],
csv_columns = c("S4SpeechLangDays",
"S4SpeechLangMinutes"),
measure_type = "continuous"),
# SpeechLangComplianceMinutes =====================================
# J 4.8 Average number of minutes of SLT per day across all patients
# (Proportion of patients applicable for SLT*Median percentage of
# days in hospital that SLT is received*Median number of minutes per
# day on which PT is received)
SpeechLangComplianceMinutes = audit_measure(
stem_name = "SpeechLangComplianceMinutes",
description = "Minutes of speech and language therapy received",
exclusions = NULL,
numerators = rlang::expr( (.data[["S4SpeechLang"]] / 100) *
!! ssnap_field[["SpeechLangMinutesPerDay"]] *
(!! ssnap_field[["PCSpeechLangDays"]] / 100)),
new_numerators = rlang::expr( (.data[["S4SpeechLang"]] / 100) *
!! ssnap_field[["SpeechLangMinutesPerDay"]] *
(!! ssnap_field[["PCSpeechLangDays"]] / 100)),
csv_columns = c("S4SpeechLang",
"S4SpeechLangDays",
"S4SpeechLangMinutes",
"S1TeamClockStartDateTime",
"S4SpeechLangEndDate"),
measure_type = "continuous"),
# SpeechLangComplianceTarget ======================================
# J 5.9 Speech and language therapy compliance target
SpeechLangComplianceTarget = audit_measure(
stem_name = "SpeechLangComplianceTarget",
description = "Speech and language therapy compliance target",
exclusions = NULL,
numerators = rlang::expr(0.5 * 45 * 5 / 7),
new_numerators = rlang::expr(0.5 * 45 * 5 / 7),
measure_type = "continuous"),
# SpeechLangCompliance ============================================
# J 5.10 Speech and language therapy compliance
SpeechLangCompliance = audit_measure(
stem_name = "SpeechLangCompliance",
description = "Speech and language therapy compliance",
exclusions = NULL,
numerators = rlang::expr(
( (.data[["S4SpeechLang"]] / 100) *
!! ssnap_field[["SpeechLangMinutesPerDay"]] *
(!! ssnap_field[["PCSpeechLangDays"]] / 100)) /
(0.5 * 45 * 5 / 7) * 100),
new_numerators = rlang::expr(
( (.data[["S4SpeechLang"]] / 100) *
!! ssnap_field[["SpeechLangMinutesPerDay"]] *
(!! ssnap_field[["PCSpeechLangDays"]] / 100)) /
(0.5 * 45 * 5 / 7) * 100),
csv_columns = c("S4SpeechLang",
"S4SpeechLangDays",
"S4SpeechLangMinutes",
"S1TeamClockStartDateTime",
"S4SpeechLangEndDate"),
measure_type = "continuous"),
# SpeechLangEquivalentMinutes =====================================
# J 5.11 Average number of minutes of SLT per day as equivalent to
# 45 minutes on 5 days per week for 50% of patients
SpeechLangEquivalentMinutes = audit_measure(
stem_name = "SpeechLangEquivalentMinutes",
description = "Speech and language therapy equivalent minutes",
exclusions = NULL,
numerators = rlang::expr( ( (.data[["S4SpeechLang"]] / 100) *
!! ssnap_field[["SpeechLangMinutesPerDay"]] *
(!! ssnap_field[["PCSpeechLangDays"]] / 100)) /
(0.5 * 5 / 7)),
new_numerators = rlang::expr( ( (.data[["S4SpeechLang"]] / 100) *
!! ssnap_field[["SpeechLangMinutesPerDay"]] *
(!! ssnap_field[["PCSpeechLangDays"]] / 100)) /
(0.5 * 5 / 7)),
csv_columns = c("S4SpeechLang",
"S4SpeechLangDays",
"S4SpeechLangMinutes",
"S1TeamClockStartDateTime",
"S4SpeechLangEndDate"),
measure_type = "continuous"),
# TODO J 5.12-18 for All Teams
# * -----------------------------------------------------------------
# * All therapies ---------------------------------------------------
# * -----------------------------------------------------------------
# AnyTherapyApplicable ============================================
# J 6.1-3 Applicability for patients to receive any therapy
# discipline at least once during their inpatient stay
AnyTherapyApplicable = audit_measure(
stem_name = "AnyTherapyApplicable",
description = "Any therapy applicability",
exclusions = NULL,
numerators = rlang::expr(.data[["S4OccTher"]] |
.data[["S4Physio"]] |
.data[["S4SpeechLang"]]),
new_numerators = rlang::expr(.data[["S4OccTher"]] |
.data[["S4Physio"]] |
.data[["S4SpeechLang"]]),
csv_columns = c("S4OccTher",
"S4Physio",
"S4SpeechLang"),
measure_type = "discrete"),
# AllTherapyMinutesMet ==============================================
# J 6.4-6 For all therapy disciplines applicable, did the patient
# receive 45 mins therapy/day for at least 5 days/week?
AllTherapyMinutesMet = audit_measure(
stem_name = "AllTherapyMinutesMet",
description = "Any therapy applicability",
exclusions = rlang::expr( (!(.data[["S4OccTher"]])) &
(!(.data[["S4Physio"]])) &
(!(.data[["S4SpeechLang"]]))),
numerators = rlang::expr(
( !(.data[["S4OccTher"]]) |
( (!! ssnap_field[["OccTherMinutesPerDay"]] *
!! ssnap_field[["PCOccTherDays"]] / 100) >=
(45 * 5 / 7))) &
( !(.data[["S4Physio"]]) |
( (!! ssnap_field[["PhysioMinutesPerDay"]] *
!! ssnap_field[["PCPhysioDays"]] / 100) >=
(45 * 5 / 7))) &
( !(.data[["S4SpeechLang"]]) |
( (!! ssnap_field[["SpeechLangMinutesPerDay"]] *
!! ssnap_field[["PCSpeechLangDays"]] / 100) >=
(45 * 5 / 7)))
),
new_numerators = rlang::expr(
( !(.data[["S4OccTher"]]) |
( (!! ssnap_field[["OccTherMinutesPerDay"]] *
!! ssnap_field[["PCOccTherDays"]] / 100) >=
(45 * 5 / 7))) &
( !(.data[["S4Physio"]]) |
( (!! ssnap_field[["PhysioMinutesPerDay"]] *
!! ssnap_field[["PCPhysioDays"]] / 100) >=
(45 * 5 / 7))) &
( !(.data[["S4SpeechLang"]]) |
( (!! ssnap_field[["SpeechLangMinutesPerDay"]] *
!! ssnap_field[["PCSpeechLangDays"]] / 100) >=
(45 * 5 / 7)))
),
csv_columns = c("S4OccTher",
"S4OccTherDays",
"S4OccTherMinutes",
"S1TeamClockStartDateTime",
"S4OccTherEndDate",
"S4Physio",
"S4PhysioDays",
"S4PhysioMinutes",
"S4PhysioEndDate",
"S4SpeechLang",
"S4SpeechLangDays",
"S4SpeechLangMinutes",
"S4SpeechLangEndDate",
"S4OccTher",
"S4Physio",
"S4SpeechLang"),
measure_type = "discrete"),
# * -----------------------------------------------------------------
# * Psychology ------------------------------------------------------
# * -----------------------------------------------------------------
# PsychologyApplicable ==============================================
# J 7.1-3 Applicability for patients to receive psychology at
# least once during their inpatient stay
PsychologyApplicable = audit_measure(
stem_name = "PsychologyApplicable",
description = "Psychology applicability",
exclusions = NULL,
numerators = rlang::expr(.data[["S4Psychology"]]),
new_numerators = rlang::expr(.data[["S4Psychology"]]),
csv_columns = "S4Psychology",
measure_type = "discrete"),
# PCPsychologyDays ================================================
# J 7.4 Percentage of days of psychology delivered of those
# where it is needed
PCPsychologyDays = audit_measure(
stem_name = "PCPsychologyDays",
description = "Percent of days psychology received",
exclusions = NULL,
numerators = ssnap_field[["PCPsychologyDays"]],
new_numerators = ssnap_field[["PCPsychologyDays"]],
csv_columns = c("S4Psychology",
"S4PsychologyDays",
"S1TeamClockStartDateTime",
"S4PsychologyEndDate"),
measure_type = "continuous"),
# PsychologyMinutes ===============================================
# J 4.5-7 Minutes of psychology received
PsychologyMinutes = audit_measure(
stem_name = "PsychologyMinutes",
description = "Minutes of psychology received",
exclusions = NULL,
numerators = ssnap_field[["PsychologyMinutesPerDay"]],
new_numerators = ssnap_field[["PsychologyMinutesPerDay"]],
csv_columns = c("S4PsychologyDays",
"S4PsychologyMinutes"),
measure_type = "continuous"),
# TODO Length of stay
# * -----------------------------------------------------------------
# * Discharge destination -------------------------------------------
# * -----------------------------------------------------------------
# DischargeDestinationGrouped =====================================
# J 9.1-11.4 Discharge destination (grouped)
DischargeDestinationGrouped = audit_measure(
stem_name = "Discharge",
description = "Discharge destination",
exclusions = NULL,
numerators = rlang::exprs(
"Died" = .data[["S7DischargeType"]] == "D",
"CareHome" = .data[["S7DischargeType"]] == "CH",
"Home" = .data[["S7DischargeType"]] == "H",
"SomewhereElse" = .data[["S7DischargeType"]] == "SE",
"InpatientTransfer" = .data[["S7DischargeType"]] == "T",
"CommunityTransfer" = .data[["S7DischargeType"]] == "TC",
"InpatientTransferNonSSNAP" =
.data[["S7DischargeType"]] == "TN",
"CommunityTransferNonSSNAP" =
.data[["S7DischargeType"]] == "TCN"),
new_numerators = tibble::tribble(
~numerator, ~fun, ~descriptor,
"Died",
rlang::expr(.data[["S7DischargeType"]] == "D"),
"Died",
"CareHome",
rlang::expr(.data[["S7DischargeType"]] == "CH"),
"Care home",
"Home",
rlang::expr(.data[["S7DischargeType"]] == "H"),
"Home",
"SomewhereElse",
rlang::expr(.data[["S7DischargeType"]] == "SE"),
"Somewhere else",
"InpatientTransfer",
rlang::expr(.data[["S7DischargeType"]] == "T"),
"Inpatient transfer",
"CommunityTransfer",
rlang::expr(.data[["S7DischargeType"]] == "TC"),
"Community transfer",
"InpatientTransferNonSSNAP",
rlang::expr(.data[["S7DischargeType"]] == "TN"),
"Inpatient transfer (to a team not on SSNAP)",
"CommunityTransferNonSSNAP",
rlang::expr(.data[["S7DischargeType"]] == "TCN"),
"Community transfer (to a team not on SSNAP)"),
csv_columns = "S7DischargeType",
measure_type = "discrete"),
# DeathByDischarge ================================================
# J 9.12-18 Death by discharge
DeathByDischarge = audit_measure(
stem_name = "DeathByDischarge",
description = "Death by discharge",
exclusions = NULL,
numerators = rlang::exprs(
"No" = is.na(.data[["S7StrokeUnitDeath"]]),
"StrokeUnit" = (.data[["S7StrokeUnitDeath"]] == TRUE),
"NotStrokeUnit" = (.data[["S7StrokeUnitDeath"]] == FALSE)),
new_numerators = tibble::tribble(
~numerator, ~fun, ~descriptor,
"No",
rlang::expr(is.na(.data[["S7StrokeUnitDeath"]])),
"No",
"StrokeUnit",
rlang::expr(.data[["S7StrokeUnitDeath"]] == TRUE),
"On a stroke unit",
"NotStrokeUnit",
rlang::expr(.data[["S7StrokeUnitDeath"]] == FALSE),
"Not on a stroke unit"),
csv_columns = "S7StrokeUnitDeath",
measure_type = "discrete"),
# DischargedHome ====================================================
# J 9.19-25 Discharged home
DischargedHome = audit_measure(
stem_name = "DischargedHome",
description = "Discharged home",
exclusions = rlang::expr(is.na(.data[["S7HomeDischargeType"]])),
numerators = rlang::exprs(
"Alone" = .data[["S7HomeDischargeType"]] == "LA",
"NotAlone" = .data[["S7HomeDischargeType"]] == "NLA",
"NotKnown" = .data[["S7HomeDischargeType"]] == "NK"),
new_numerators = tibble::tribble(
~numerator, ~fun, ~descriptor,
"Alone",
rlang::expr(.data[["S7HomeDischargeType"]] == "LA"),
"Alone",
"NotAlone",
rlang::expr(.data[["S7HomeDischargeType"]] == "NLA"),
"Not alone",
"NotKnown",
rlang::expr(.data[["S7HomeDischargeType"]] == "NK"),
"Not known"),
csv_columns = c("S7HomeDischargeType",
"S7HomeDischargeType"),
measure_type = "discrete"),
# DischargedCareHome ==============================================
# J 9.26-30 Discharged to a care home
DischargedCareHome = audit_measure(
stem_name = "DischargedCareHome",
description = "Discharged to a care home",
exclusions = rlang::expr(is.na(
.data[["S7CareHomeDischargePermanentResidence"]])),
numerators = rlang::exprs(
"New" =
(.data[["S7CareHomeDischargePermanentResidence"]] == TRUE),
"NotNew" =
(.data[["S7CareHomeDischargePermanentResidence"]] == FALSE)),
new_numerators = tibble::tribble(
~numerator, ~fun, ~descriptor,
"New",
rlang::expr(.data[["S7CareHomeDischargePermanentResidence"]] == TRUE),
"New",
"NotNew",
rlang::expr(.data[["S7CareHomeDischargePermanentResidence"]] == FALSE),
"Not new"),
csv_columns = c("S7CareHomeDischargePermanentResidence",
"S7CareHomeDischargePermanentResidence"),
measure_type = "discrete"),
# NewlyInstitutionalised ==========================================
# J 9.31-33 Newly institutionalised
NewlyInstitutionalised = audit_measure(
stem_name = "NewlyInstitutionalised",
description = "Newly institutionalised following stroke",
exclusions = rlang::expr(.data[["S7DischargeType"]] == "D"),
numerators = rlang::expr(
.data[["S7CareHomeDischargeToNewResidence"]] == TRUE),
new_numerators = rlang::expr(
.data[["S7CareHomeDischargeToNewResidence"]] == TRUE),
csv_columns = c("S7CareHomeDischargeToNewResidence",
"S7DischargeType"),
measure_type = "discrete"),
# NewTemporaryInstitution =========================================
# J 9.34-38 If newly institutionalised, temporary or permanent?
NewTemporaryInstitution = audit_measure(
stem_name = "NewTemporaryInstitution",
description = "Is new institutionalisation temporary?",
exclusions = rlang::expr(
.data[["S7CareHomeDischargeToNewResidence"]] != TRUE),
numerators = rlang::exprs(
"Temporary" =
(.data[["S7CareHomeDischargePermanentResidence"]] == FALSE),
"Permanent" =
(.data[["S7CareHomeDischargePermanentResidence"]] == TRUE)),
new_numerators = tibble::tribble(
~numerator, ~fun, ~descriptor,
"Temporary",
rlang::expr(.data[["S7CareHomeDischargePermanentResidence"]] == FALSE),
"Temporary",
"Permanent",
rlang::expr(.data[["S7CareHomeDischargePermanentResidence"]] == TRUE),
"Permanent"),
csv_columns = c("S7CareHomeDischargePermanentResidence",
"S7CareHomeDischargeToNewResidence"),
measure_type = "discrete"),
# * -----------------------------------------------------------------
# * ESD -------------------------------------------------------------
# * -----------------------------------------------------------------
# DischargedESD ===================================================
# J 10.1-7 If discharged alive, discharged with early supported
# discharge (ESD) team:
DischargedESD = audit_measure(
stem_name = "DischargedESD",
description = "Discharged with ESD?",
exclusions = rlang::expr(.data[["S7DischargeType"]] == "D"),
numerators = rlang::exprs(
"Specialist" =
(.data[["S7DischargedSpecialistEsdmt"]] == TRUE),
"NotSpecialist" =
(.data[["S7DischargedSpecialistEsdmt"]] == FALSE),
"No" = is.na(.data[["S7DischargedSpecialistEsdmt"]])),
new_numerators = tibble::tribble(
~numerator, ~fun, ~descriptor,
"Specialist",
rlang::expr(.data[["S7DischargedSpecialistEsdmt"]] == TRUE),
"Specialist",
"NotSpecialist",
rlang::expr(.data[["S7DischargedSpecialistEsdmt"]] == FALSE),
"Not specialist",
"No",
rlang::expr(is.na(.data[["S7DischargedSpecialistEsdmt"]])),
"No"),
csv_columns = c("S7DischargedSpecialistEsdmt",
"S7DischargeType"),
measure_type = "discrete"),
# * -----------------------------------------------------------------
# * CRT -------------------------------------------------------------
# * -----------------------------------------------------------------
# DischargedCRT ===================================================
# J 11.1-7 If discharged alive, discharged with community rehab
# team (CRT):
DischargedCRT = audit_measure(
stem_name = "DischargedCRT",
description = "Discharged with CRT?",
exclusions = rlang::expr(.data[["S7DischargeType"]] == "D"),
numerators = rlang::exprs(
"Specialist" =
(.data[["S7DischargedSpecialistMcrt"]] == TRUE),
"NotSpecialist" =
(.data[["S7DischargedSpecialistMcrt"]] == FALSE),
"No" = is.na(.data[["S7DischargedSpecialistMcrt"]])),
new_numerators = tibble::tribble(
~numerator, ~fun, ~descriptor,
"Specialist",
rlang::expr(.data[["S7DischargedSpecialistMcrt"]] == TRUE),
"Specialist",
"NotSpecialist",
rlang::expr(.data[["S7DischargedSpecialistMcrt"]] == FALSE),
"Not specialist",
"No",
rlang::expr(is.na(.data[["S7DischargedSpecialistMcrt"]])),
"No"),
csv_columns = c("S7DischargedSpecialistMcrt",
"S7DischargeType"),
measure_type = "discrete"),
# * -----------------------------------------------------------------
# * ESD or CRT ------------------------------------------------------
# * -----------------------------------------------------------------
# DischargedSpecialistESDOrCRT ====================================
# J 12.1-3 If discharged alive, discharged with a stroke/neurology
# specific service (ESD and/or CRT)
DischargedSpecialistESDOrCRT = audit_measure(
stem_name = "DischargedSpecialistESDOrCRT",
description = "Discharged with speclist ESD or CRT?",
exclusions = rlang::expr(.data[["S7DischargeType"]] == "D"),
numerators = rlang::expr(
(.data[["S7DischargedSpecialistEsdmt"]] == TRUE) |
(.data[["S7DischargedSpecialistMcrt"]] == TRUE)),
new_numerators = rlang::expr(
(.data[["S7DischargedSpecialistEsdmt"]] == TRUE) |
(.data[["S7DischargedSpecialistMcrt"]] == TRUE)),
csv_columns = c("S7DischargedSpecialistEsdmt",
"S7DischargedSpecialistMcrt",
"S7DischargeType"),
measure_type = "discrete"),
# * -----------------------------------------------------------------
# * Rehab goals -----------------------------------------------------
# * -----------------------------------------------------------------
# RehabGoals ======================================================
# J 13.1-9 Rehabilitation goals by discharge from inpatient care
RehabGoals = audit_measure(
stem_name = "RehabGoals",
description = "Rehabilitation goals by inpatient discharge?",
exclusions = rlang::expr(.data[["S7DischargeType"]] == "D"),
numerators = rlang::exprs(
"Within5Days" =
(!!ssnap_field[["ClockStartToRehabGoalsDays"]] <= 5),
"Over5Days" =
(!!ssnap_field[["ClockStartToRehabGoalsDays"]] > 5),
"ApplicableNotSet" = is.na(.data[["S4RehabGoalsDate"]]) &
( (.data[["S4RehabGoalsNoneReason"]] == "OR") |
(.data[["S4RehabGoalsNoneReason"]] == "NK")),
"NotApplicable" = is.na(.data[["S4RehabGoalsDate"]]) &
(.data[["S4RehabGoalsNoneReason"]] != "OR") &
(.data[["S4RehabGoalsNoneReason"]] != "NK")),
new_numerators = tibble::tribble(
~numerator, ~fun, ~descriptor,
"Within5Days",
rlang::expr(!!ssnap_field[["ClockStartToRehabGoalsDays"]] <= 5),
"Within 5 days",
"Over5Days",
rlang::expr(!!ssnap_field[["ClockStartToRehabGoalsDays"]] > 5),
"Over 5 days",
"ApplicableNotSet",
rlang::expr(is.na(.data[["S4RehabGoalsDate"]]) &
( (.data[["S4RehabGoalsNoneReason"]] == "OR") |
(.data[["S4RehabGoalsNoneReason"]] == "NK"))),
"Applicable but not set",
"NotApplicable",
rlang::expr(is.na(.data[["S4RehabGoalsDate"]]) &
(.data[["S4RehabGoalsNoneReason"]] != "OR") &
(.data[["S4RehabGoalsNoneReason"]] != "NK")),
"Not applicable"),
csv_columns = c("S1PatientClockStartDateTime",
"S4RehabGoalsDate",
"S4RehabGoalsNoneReason",
"S7DischargeType"),
measure_type = "discrete"),
# RehabGoalsApplicable ============================================
# J 13.10-12 Applicability for rehabilitation goals within 5 days of
# clock start
RehabGoalsApplicable = audit_measure(
stem_name = "RehabGoalsApplicable",
description = "Applicability for rehab goals within 5 days",
exclusions = rlang::expr(.data[["S7DischargeType"]] == "D"),
numerators = rlang::expr(
(.data[["S4RehabGoalsNoneReason"]] != "OR") &
(.data[["S4RehabGoalsNoneReason"]] != "NK")),
new_numerators = rlang::expr(
(.data[["S4RehabGoalsNoneReason"]] != "OR") &
(.data[["S4RehabGoalsNoneReason"]] != "NK")),
csv_columns = c("S4RehabGoalsNoneReason",
"S7DischargeType"),
measure_type = "discrete"),
# RehabGoalsSetIfApplicable ============================================
# J 13.13-15 Rehab goals set if applicable
RehabGoalsSetIfApplicable = audit_measure(
stem_name = "RehabGoalsSetIfApplicable",
description = "Rehab goals set within 5 days if applicable",
exclusions = rlang::expr( (.data[["S7DischargeType"]] == "D") |
(.data[["S4RehabGoalsNoneReason"]] != "OR") |
(.data[["S4RehabGoalsNoneReason"]] != "NK")),
numerators = rlang::expr(
!!ssnap_field[["ClockStartToRehabGoalsDays"]] <= 5),
new_numerators = rlang::expr(
!!ssnap_field[["ClockStartToRehabGoalsDays"]] <= 5),
csv_columns = c("S1PatientClockStartDateTime",
"S4RehabGoalsDate",
"S7DischargeType",
"S4RehabGoalsNoneReason"),
measure_type = "discrete"),
# TODO J14 - composite measure.
# * -----------------------------------------------------------------
# * Post-stroke infection -------------------------------------------
# * -----------------------------------------------------------------
# UrinaryTractInfection =============================================
# K5.1-7 Urinary tract infection in first 7 days
UrinaryTractInfection = audit_measure(
stem_name = "UrinaryTractInfection",
description =
"Urinary tract infection in the first 7 days from clock start",
exclusions = NULL,
numerators = rlang::exprs(
"Yes" = (.data[["S5UrinaryTractInfection7Days"]] == TRUE),
"No" = (.data[["S5UrinaryTractInfection7Days"]] == FALSE),
"Not known" = is.na(.data[["S5UrinaryTractInfection7Days"]])),
new_numerators = tibble::tribble(
~numerator, ~fun, ~descriptor,
"Yes",
rlang::expr(.data[["S5UrinaryTractInfection7Days"]] == TRUE),
"Yes",
"No",
rlang::expr(.data[["S5UrinaryTractInfection7Days"]] == FALSE),
"No",
"Not known",
rlang::expr(is.na(.data[["S5UrinaryTractInfection7Days"]])),
"Not known"
),
csv_columns = "S5UrinaryTractInfection7Days",
measure_type = "discrete"),
# PneumoniaAntibiotics =============================================
# K6.1-7 Antibiotics for newly acquired pneumonia in first 7 days
PneumoniaAntibiotics = audit_measure(
stem_name = "PneumoniaAntibiotics",
description =
"Antibiotics for newly acquired pneumonia in the first 7 days from clock start",
exclusions = NULL,
numerators = rlang::exprs(
"Yes" = (.data[["S5PneumoniaAntibiotics7Days"]] == TRUE),
"No" = (.data[["S5PneumoniaAntibiotics7Days"]] == FALSE),
"Not known" = is.na(.data[["S5PneumoniaAntibiotics7Days"]]),
),
new_numerators = tibble::tribble(
~numerator, ~fun, ~descriptor,
"Yes",
rlang::expr(.data[["S5PneumoniaAntibiotics7Days"]] == TRUE),
"Yes",
"No",
rlang::expr(.data[["S5PneumoniaAntibiotics7Days"]] == FALSE),
"No",
"Not known",
rlang::expr(is.na(.data[["S5PneumoniaAntibiotics7Days"]])),
"Not known"),
csv_columns = "S5PneumoniaAntibiotics7Days",
measure_type = "discrete"),
# * -----------------------------------------------------------------
# * Continence plan -------------------------------------------------
# * -----------------------------------------------------------------
# ContinencePlanGrouped ===========================================
# J 15.1-11 Urinary continence plan by discharge from inpatient care
# K 2.1-11 Urinary continence plan by discharge from inpatient care
ContinencePlanGrouped = audit_measure(
stem_name = "ContinencePlanGrouped",
description = "Continence plan if applicable",
exclusions = NULL,
numerators = rlang::exprs(
"PlanDrawnUp" = !is.na(.data[["S6UrinaryContinencePlanDate"]]),
"NoPlanOrg" =
.data[["S6UrinaryContinencePlanNoPlanReason"]] == "OR",
"NoPlanRefused" =
.data[["S6UrinaryContinencePlanNoPlanReason"]] == "PR",
"NoPlanContinent" =
.data[["S6UrinaryContinencePlanNoPlanReason"]] == "PC",
"NoPlanNotKnown" =
.data[["S6UrinaryContinencePlanNoPlanReason"]] == "NK"),
new_numerators = tibble::tribble(
~numerator, ~fun, ~descriptor,
"PlanDrawnUp",
rlang::expr(!is.na(.data[["S6UrinaryContinencePlanDate"]])),
"Plan drawn up",
"NoPlanOrg",
rlang::expr(.data[["S6UrinaryContinencePlanNoPlanReason"]] == "OR"),
"No plan (organisational reasons)",
"NoPlanRefused",
rlang::expr(.data[["S6UrinaryContinencePlanNoPlanReason"]] == "PR"),
"No plan (patient refused)",
"NoPlanContinent",
rlang::expr(.data[["S6UrinaryContinencePlanNoPlanReason"]] == "PC"),
"No plan (patient continent)",
"NoPlanNotKnown",
rlang::expr(.data[["S6UrinaryContinencePlanNoPlanReason"]] == "NK"),
"No plan (reason not known)"),
csv_columns = c("S6UrinaryContinencePlanDate",
"S6UrinaryContinencePlanNoPlanReason"),
measure_type = "discrete"),
# ClockStartToContinencePlanHours =================================
# J 15.12-14 Time from clock start to continence plan drawn up (hrs)
# K 2.12-14 Time from clock start to continence plan drawn up (hrs)
ClockStartToContinencePlanHours = audit_measure(
stem_name = "ClockStartToContinencePlanHours",
description = "Clock start to continence plan (hours)",
exclusions = NULL,
numerators = ssnap_field[["ClockStartToContinencePlanHours"]],
new_numerators = ssnap_field[["ClockStartToContinencePlanHours"]],
csv_columns = c("S1PatientClockStartDateTime",
"S6UrinaryContinencePlanDate"),
measure_type = "continuous"),
# ContinencePlanApplicability =====================================
# J 15.15-17 Patient applicability for continence plan
# K 2.15-17 Patient applicability for continence plan
ContinencePlanApplicability = audit_measure(
stem_name = "ContinencePlanApplicability",
description = "Continence plan applicability",
exclusions = NULL,
numerators = rlang::expr(!(
.data[["S6UrinaryContinencePlanNoPlanReason"]] %in%
c("PC", "PR"))),
new_numerators = rlang::expr(!(
.data[["S6UrinaryContinencePlanNoPlanReason"]] %in%
c("PC", "PR"))),
csv_columns = "S6UrinaryContinencePlanNoPlanReason",
measure_type = "discrete"),
# ContinencePlanIfApplicable ======================================
# J 15.18-20 Patient applicability for continence plan
# K 2.18-20 Patient applicability for continence plan
ContinencePlanIfApplicable = audit_measure(
stem_name = "ContinencePlanIfApplicable",
description = "Continence plan if applicable",
exclusions = rlang::expr(
.data[["S6UrinaryContinencePlanNoPlanReason"]] %in%
c("PC", "PR")),
numerators = rlang::expr(
!is.null(.data[["S6UrinaryContinencePlanDate"]])),
new_numerators = rlang::expr(
!is.null(.data[["S6UrinaryContinencePlanDate"]])),
csv_columns = c("S6UrinaryContinencePlanDate",
"S6UrinaryContinencePlanNoPlanReason"),
measure_type = "discrete"),
# ContinencePlanIfApplicableIn21Days ==============================
# J 15.21-23 Continence plan completed within 21 days if applicable
ContinencePlanIfApplicableIn21Days = audit_measure(
stem_name = "ContinencePlanIfApplicableIn21Days",
description = "Continence plan if applicable",
exclusions = rlang::expr(
.data[["S6UrinaryContinencePlanNoPlanReason"]] %in%
c("PC", "PR")),
numerators = rlang::expr(
!! ssnap_field[["ClockStartToContinencePlanHours"]] <=
(21 * 24)),
new_numerators = rlang::expr(
!! ssnap_field[["ClockStartToContinencePlanHours"]] <=
(21 * 24)),
csv_columns = c("S1PatientClockStartDateTime",
"S6UrinaryContinencePlanDate",
"S6UrinaryContinencePlanNoPlanReason"),
measure_type = "discrete"),
# * -----------------------------------------------------------------
# * Nutrition -------------------------------------------------------
# * -----------------------------------------------------------------
# NutritionalScreeningByDischarge =================================
# J 16.1-3 Nutritional screening by discharge from inpatient care
# K 3.1-3 Nutritional screening by discharge from inpatient care
NutritionalScreeningByDischarge = audit_measure(
stem_name = "NutritionScreened",
description = "Nutritional screening by discharge",
exclusions = NULL,
numerators = rlang::expr(
!is.na(.data[["S6MalnutritionScreening"]])),
new_numerators = rlang::expr(
!is.na(.data[["S6MalnutritionScreening"]])),
csv_columns = "S6MalnutritionScreening",
measure_type = "discrete"),
# NutritionalScreeningHighRisk ====================================
# J 16.4-6 If received nutritional screening, were they high risk?
# K 3.4-6 If received nutritional screening, were they high risk?
NutritionalScreeningHighRisk = audit_measure(
stem_name = "NutritionScreeningHighRisk",
description = "High risk on nutritional screening",
exclusions = rlang::expr(
is.na(.data[["S6MalnutritionScreening"]])),
numerators = rlang::expr(.data[["S6MalnutritionScreening"]]),
new_numerators = rlang::expr(.data[["S6MalnutritionScreening"]]),
csv_columns = c("S6MalnutritionScreening",
"S6MalnutritionScreening"),
measure_type = "discrete"),
# NutritionSeenDietitian ==========================================
# J 16.7-9 If high risk on nutritional screening, seen dietitian?
# K 3.7-9 If high risk on nutritional screening, seen dietitian?
NutritionSeenDietitian = audit_measure(
stem_name = "NutritionScreened",
description = "High risk on nutritional screening",
exclusions = rlang::expr(
.data[["S6MalnutritionScreening"]] != TRUE),
numerators = rlang::expr(
!is.na(.data[["S6MalnutritionScreeningDietitianDate"]])),
new_numerators = rlang::expr(
!is.na(.data[["S6MalnutritionScreeningDietitianDate"]])),
csv_columns = c("S6MalnutritionScreeningDietitianDate",
"S6MalnutritionScreening"),
measure_type = "discrete"),
# NutritionalApplicability ========================================
# J 16.10.1-12.1 Applicability for nutritional screening?
# K 3.10.1-12.1 Applicability for nutritional screening?
NutritionalApplicability = audit_measure(
stem_name = "NutritionalApplicability",
description = "High risk on nutritional screening",
exclusions = rlang::expr(
!is.na(.data[["S3PalliativeCareDecisionDate"]]) |
!is.na(.data[["S6PalliativeCareByDischargeDate"]])),
numerators = rlang::expr(
.data[["S6MalnutritionScreening"]] |
is.na(.data[["S6MalnutritionScreening"]])),
new_numerators = rlang::expr(
.data[["S6MalnutritionScreening"]] |
is.na(.data[["S6MalnutritionScreening"]])),
csv_columns = c("S6MalnutritionScreening",
"S3PalliativeCareDecisionDate",
"S6PalliativeCareByDischargeDate"),
measure_type = "discrete"),
# SeenDietitianIfApplicable =======================================
# J 16.13.1-15.1 Seen dietitian if applicable?
# K 3.13.1-15.1 Seen dietitian if applicable?
SeenDietitianIfApplicable = audit_measure(
stem_name = "SeenDietitianIfApplicable",
description = "Seen dietitian if applicable?",
exclusions = rlang::expr(
!is.na(.data[["S3PalliativeCareDecisionDate"]]) |
!is.na(.data[["S6PalliativeCareByDischargeDate"]])),
numerators = rlang::expr(
(.data[["S6MalnutritionScreening"]] |
is.na(.data[["S6MalnutritionScreening"]])) &
!is.na(.data[["S6MalnutritionScreeningDietitianDate"]])),
new_numerators = rlang::expr(
(.data[["S6MalnutritionScreening"]] |
is.na(.data[["S6MalnutritionScreening"]])) &
!is.na(.data[["S6MalnutritionScreeningDietitianDate"]])),
csv_columns = c("S6MalnutritionScreening",
"S6MalnutritionScreeningDietitianDate",
"S3PalliativeCareDecisionDate",
"S6PalliativeCareByDischargeDate"),
measure_type = "discrete"),
# * -----------------------------------------------------------------
# * Mood screen -----------------------------------------------------
# * -----------------------------------------------------------------
# MoodScreenGrouped =================================================
# J 17.1-11 Mood screening by discharge from inpatient care
# K 12.1-11 Mood screening by discharge from inpatient care
MoodScreenGrouped = audit_measure(
stem_name = "MoodScreenGrouped",
description = "Mood screened if applicable",
exclusions = NULL,
numerators = rlang::exprs(
"Screened" = !is.na(.data[["S6MoodScreeningDate"]]),
"NoOrg" =
.data[["S6MoodScreeningNoScreeningReason"]] == "OR",
"NoRefused" =
.data[["S6MoodScreeningNoScreeningReason"]] == "PR",
"NoMedicallyUnwell" =
.data[["S6MoodScreeningNoScreeningReason"]] == "MU",
"NoNotKnown" =
.data[["S6MoodScreeningNoScreeningReason"]] == "NK"),
new_numerators = tibble::tribble(
~numerator, ~fun, ~descriptor,
"Screened",
rlang::expr(!is.na(.data[["S6MoodScreeningDate"]])),
"Screened",
"NoOrg",
rlang::expr(.data[["S6MoodScreeningNoScreeningReason"]] == "OR"),
"No (organisational reasons)",
"NoRefused",
rlang::expr(.data[["S6MoodScreeningNoScreeningReason"]] == "PR"),
"No (patient refused)",
"NoMedicallyUnwell",
rlang::expr(.data[["S6MoodScreeningNoScreeningReason"]] == "MU"),
"No (patient medically unwell)",
"NoNotKnown",
rlang::expr(.data[["S6MoodScreeningNoScreeningReason"]] == "NK"),
"No (reason not known)"),
csv_columns = c("S6MoodScreeningDate",
"S6MoodScreeningNoScreeningReason"),
measure_type = "discrete"),
# MoodScreenApplicability =========================================
# K12.12 Patient applicability for mood screening by discharge
# (excludes patients whose total length of stay was less than 7
# days)
# MoodScreenApplicability = audit_measure(
# stem_name = "MoodScreenApplicability",
# description = glue::glue(
# "Patient applicability for mood screening by discharge
# (excludes patients whose total length of stay was less than 7
# days)"),
# exclusions = NULL,
# numerators = rlang::expr(
# !! ssnap_field[["LengthOfFirstInptStayHrs"]] >
# (7 * 24)),
# csv_columns = c("S1PatientClockStartDateTime",
# "S7FirstInptEpisodeClockStopDateTime"),
# measure_type = "discrete"),
# CognitiveScreenApplicability ====================================
# K12.12 Patient applicability for mood screening by discharge
# (excludes patients whose total length of stay was less than 7
# days)
# CognitiveScreenApplicability = audit_measure(
# stem_name = "CognitiveScreenApplicability",
# description = glue::glue(
# "Patient applicability for cognition screening by discharge
# (excludes patients whose total length of stay was less than 7
# days)"),
# exclusions = NULL,
# numerators = rlang::expr(
# !! ssnap_field[["LengthOfFirstInptStayHrs"]] >
# (7 * 24)),
# csv_columns = c("S1PatientClockStartDateTime",
# "S7FirstInptEpisodeClockStopDateTime"),
# measure_type = "discrete"),
CognitionAndMoodAssessed = audit_measure(
stem_name = "CognitionAndMoodAssessed",
description = "Cognition and mood assessed",
exclusions = rlang::expr(
# Exclude anyone who refuses or is unwell (mood)
(.data[["S6MoodScreeningNoScreeningReason"]]
%in% c("MU", "PR")) |
# Exclude anyone who refuses or is unwell (cognition)
(.data[["S6CognitionScreeningNoScreeningReason"]]
%in% c("MU", "PR")) |
# Exclude anyone whose total length of stay is < 7 days AND
# had one or both screens omitted
( (.data[["S7TeamClockStopDateTime"]] <
(as.Date(.data[["S1PatientClockStartDateTime"]]) + 7)) &
is.na(.data[["S6MoodScreeningDate"]]) &
is.na(.data[["S6CognitionScreeningDate"]]))),
numerators = rlang::expr( (.data[["S6MoodScreeningDate"]] <
(as.Date(.data[["S1PatientClockStartDateTime"]]) + 42)) &
(.data[["S6CognitionScreeningDate"]] <
(as.Date(.data[["S1PatientClockStartDateTime"]]) + 42))),
new_numerators = rlang::expr( (.data[["S6MoodScreeningDate"]] <
(as.Date(.data[["S1PatientClockStartDateTime"]]) + 42)) &
(.data[["S6CognitionScreeningDate"]] <
(as.Date(.data[["S1PatientClockStartDateTime"]]) + 42))),
csv_columns = c("S6MoodScreeningDate",
"S1PatientClockStartDateTime",
"S6CognitionScreeningDate",
"S6MoodScreeningNoScreeningReason",
"S6CognitionScreeningNoScreeningReason",
"S7TeamClockStopDateTime",
"S1PatientClockStartDateTime",
"S6MoodScreeningDate",
"S6CognitionScreeningDate"),
measure_type = "discrete"),
StayOver90PCInStrokeUnit = audit_measure(
stem_name = "StayOver90PCInStrokeUnit",
description = "Stay over 90% on stroke unit",
exclusions = rlang::expr( (.data[["S1FirstWard"]] == "ICH") |
(!is.na(.data[["S7DeathDate"]]) &
(lubridate::day(.data[["S7DeathDate"]]) ==
lubridate::day(!! ssnap_field[["TeamClockStart"]])) &
(lubridate::month(.data[["S7DeathDate"]]) ==
lubridate::month(!! ssnap_field[["TeamClockStart"]])) &
(lubridate::year(.data[["S7DeathDate"]]) ==
lubridate::year(!! ssnap_field[["TeamClockStart"]])))
),
numerators = rlang::expr(!! ssnap_field[["StayPercent"]] >= 90),
new_numerators = rlang::expr(!! ssnap_field[["StayPercent"]] >= 90),
csv_columns = c("S1TeamClockStartDateTime",
"S7TeamClockStopDateTime",
"S4StrokeUnitArrivalDateTime",
"S7StrokeUnitDischargeDateTime",
"S1FirstWard",
"S7DeathDate"),
measure_type = "discrete"),
JointCarePlanning = audit_measure(
stem_name = "JointCarePlanning",
description = "Joint care planning",
exclusions = rlang::expr(
# Exclude patients who die or whose last known records
# indicates transfer to another inpatient team.
.data[["S7DischargeType"]] %in% c("D", "T")),
numerators = rlang::expr(.data[["S7DischargeJointCarePlanning"]]),
new_numerators = rlang::expr(.data[["S7DischargeJointCarePlanning"]]),
csv_columns = c("S7DischargeJointCarePlanning",
"S7DischargeType"),
measure_type = "discrete"),
DischargedWithESD = audit_measure(
stem_name = "DischargedWithESD",
description = "Discharged with ESD",
exclusions = rlang::expr(
# Exclude patients who die or whose last known records
# indicates transfer to another inpatient team.
.data[["S7DischargeType"]] %in% c("D", "T")),
numerators = rlang::expr(dplyr::case_when(
(is.na(.data[["S7DischargedSpecialistEsdmt"]]) &
is.na(.data[["S7DischargedSpecialistMcrt"]])) ~ FALSE,
TRUE ~ (.data[["S7DischargedSpecialistEsdmt"]] |
.data[["S7DischargedSpecialistMcrt"]]))),
new_numerators = rlang::expr(dplyr::case_when(
(is.na(.data[["S7DischargedSpecialistEsdmt"]]) &
is.na(.data[["S7DischargedSpecialistMcrt"]])) ~ FALSE,
TRUE ~ (.data[["S7DischargedSpecialistEsdmt"]] |
.data[["S7DischargedSpecialistMcrt"]]))),
csv_columns = c("S7DischargedSpecialistEsdmt",
"S7DischargedSpecialistMcrt",
"S7DischargeType"),
measure_type = "discrete"),
AFWithAnticoagulation = audit_measure(
stem_name = "AFWithAnticoagulation",
description = "AF discharged with anticoagulation plan",
exclusions = rlang::expr(
# Exclude patients who die or whose last known records indicates
# transfer to another inpatient team.
# Exclude patients who are not in atrial fibrillation
# Patients with "no but" for anticoagulation are excluded
(.data[["S7DischargeType"]] %in% c("D", "T")) |
(!.data[["S7DischargeAtrialFibrillation"]]) |
(is.na(
.data[["S7DischargeAtrialFibrillationAnticoagulation"]]))),
numerators = rlang::expr(
.data[["S7DischargeAtrialFibrillationAnticoagulation"]]),
new_numerators = rlang::expr(
.data[["S7DischargeAtrialFibrillationAnticoagulation"]]),
csv_columns = c("S7DischargeAtrialFibrillationAnticoagulation",
"S7DischargeType",
"S7DischargeAtrialFibrillation",
"S7DischargeAtrialFibrillationAnticoagulation"),
measure_type = "discrete"),
DischargeNamedContact = audit_measure(
stem_name = "DischargeNamedContact",
description = "Discharged with named contact",
exclusions = rlang::expr(
# Exclude patients who die or whose last known records
# indicates transfer to another inpatient team.
.data[["S7DischargeType"]] %in% c("D", "T")),
numerators = rlang::expr(.data[["S7DischargeNamedContact"]]),
new_numerators = rlang::expr(.data[["S7DischargeNamedContact"]]),
csv_columns = c("S7DischargeNamedContact",
"S7DischargeType"),
measure_type = "discrete"),
SixMonthFollowUp = audit_measure(
stem_name = "SixMonthFollowUp",
description = "Breakdown of six month follow-up provision",
exclusions = NULL,
numerators = rlang::exprs(
"Yes" = .data[["S8FollowUp"]] == "Y",
"DiedOnAcutePathway" = is.null(.data[["S8FollowUp"]]) &
(.data[["S7DischargeType"]] == "D"),
"DiedWithin6Months" = .data[["S8FollowUp"]] == "ND",
"NoBut" = .data[["S8FollowUp"]] == "NB",
"No" = .data[["S8FollowUp"]] == "N",
"Blank" = is.null(.data[["S8FollowUp"]]) &
(.data[["S7DischargeType"]] != "D")),
new_numerators = tibble::tribble(
~numerator, ~fun, ~descriptor,
"Yes",
rlang::expr(.data[["S8FollowUp"]] == "Y"),
"Yes",
"DiedOnAcutePathway",
rlang::expr(is.null(.data[["S8FollowUp"]]) &
(.data[["S7DischargeType"]] == "D")),
"Died on acute pathway",
"DiedWithin6Months",
rlang::expr(.data[["S8FollowUp"]] == "ND"),
"Died within 6 months",
"NoBut",
rlang::expr(.data[["S8FollowUp"]] == "NB"),
"No (but reason given)",
"No",
rlang::expr(.data[["S8FollowUp"]] == "N"),
"No (no reason given)",
"Blank",
rlang::expr(is.null(.data[["S8FollowUp"]]) &
(.data[["S7DischargeType"]] != "D")),
"Blank"),
csv_columns = c("S8FollowUp",
"S7DischargeType"),
measure_type = "discrete"),
SixMonthAnsweredApplicability = audit_measure(
stem_name = "SixMonthAnsweredApplicability",
description = glue::glue(
"Patient record deemed appropriate to be actively answered
(excludes died in care)"),
exclusions = NULL,
numerators = rlang::expr(.data[["S7DischargeType"]] != "D"),
new_numerators = rlang::expr(.data[["S7DischargeType"]] != "D"),
csv_columns = "S7DischargeType",
measure_type = "discrete"),
SixMonthAnswered = audit_measure(
stem_name = "SixMonthAnswered",
description = glue::glue(
"Section 8 has been actively answered, if record appropriate
for completion"),
exclusions = rlang::expr(.data[["S7DischargeType"]] == "D"),
numerators = rlang::expr(!is.null(.data[["S8FollowUp"]])),
new_numerators = rlang::expr(!is.null(.data[["S8FollowUp"]])),
csv_columns = c("S8FollowUp",
"S7DischargeType"),
measure_type = "discrete"),
SixMonthFollowupApplicability = audit_measure(
stem_name = "SixMonthFollowupApplicability",
description = glue::glue(
"Applicability for follow-up to be undertaken (excludes died
in care, died within 6 months of admission, and 'no but')"),
exclusions = NULL,
numerators = rlang::expr( (.data[["S7DischargeType"]] != "D") &
(.data[["S8FollowUp"]] != "ND") &
(.data[["S8FollowUp"]] != "NB")),
new_numerators = rlang::expr( (.data[["S7DischargeType"]] != "D") &
(.data[["S8FollowUp"]] != "ND") &
(.data[["S8FollowUp"]] != "NB")),
csv_columns = c("S7DischargeType",
"S8FollowUp"),
measure_type = "discrete"),
SixMonthFollowupCompleted = audit_measure(
stem_name = "SixMonthFollowupCompleted",
description = glue::glue(
"Six month followup completed"),
exclusions = rlang::expr( (.data[["S7DischargeType"]] == "D") |
(.data[["S8FollowUp"]] == "ND") |
(.data[["S8FollowUp"]] == "NB")),
numerators = rlang::expr(.data[["S7DischargeType"]] == "Y"),
new_numerators = rlang::expr(.data[["S7DischargeType"]] == "Y"),
csv_columns = c("S7DischargeType",
"S7DischargeType",
"S8FollowUp"),
measure_type = "discrete"),
# ClockStartTo6MonthAssessmentMonths ==============================
ClockStartTo6MonthAssessmentMonths = audit_measure(
stem_name = "ClockStartTo6MonthAssessmentMonths",
description =
"Number of months from Clock Start to six month assessment",
exclusions = rlang::expr(.data[["S8FollowUp"]] != "Y"),
numerators = ssnap_field[["ClockStartTo6MonthAssessmentMonths"]],
new_numerators = ssnap_field[["ClockStartTo6MonthAssessmentMonths"]],
csv_columns = c("S1PatientClockStartDateTime",
"S8FollowUpDate",
"S8FollowUp"),
measure_type = "continuous"),
DischargeTo6MonthAssessmentMonths = audit_measure(
stem_name = "DischargeTo6MonthAssessmentMonths",
description =
"Number of months from discharge to six month assessment",
exclusions = rlang::expr(.data[["S8FollowUp"]] != "Y"),
numerators = ssnap_field[["DischargeTo6MonthAssessmentMonths"]],
new_numerators = ssnap_field[["DischargeTo6MonthAssessmentMonths"]],
csv_columns = c("S7HospitalDischargeDateTime",
"S8FollowUpDate",
"S8FollowUp"),
measure_type = "continuous"),
FollowUpType = audit_measure(
stem_name = "FollowUpType",
description = "Follow-up type",
exclusions = rlang::expr(.data[["S8FollowUp"]] != "Y"),
numerators = rlang::exprs(
"InPerson" = .data[["S8FollowUpType"]] == "IP",
"Online" = .data[["S8FollowUpType"]] == "O",
"Telephone" = .data[["S8FollowUpType"]] == "T",
"Post" = .data[["S8FollowUpType"]] == "P"),
new_numerators = tibble::tribble(
~numerator, ~fun, ~descriptor,
"InPerson",
rlang::expr(.data[["S8FollowUpType"]] == "IP"),
"In person",
"Online",
rlang::expr(.data[["S8FollowUpType"]] == "O"),
"Online",
"Telephone",
rlang::expr(.data[["S8FollowUpType"]] == "T"),
"Telephone",
"Post",
rlang::expr(.data[["S8FollowUpType"]] == "P"),
"Post"),
csv_columns = c("S8FollowUpType",
"S8FollowUp"),
measure_type = "discrete"),
FollowUpProvider = audit_measure(
stem_name = "FollowUpProvider",
description = "Follow-up provider",
exclusions = rlang::expr(.data[["S8FollowUp"]] != "Y"),
numerators = rlang::exprs(
"GP" = .data[["S8FollowUpBy"]] == "GP",
"StrokeCoordinator" = .data[["S8FollowUpBy"]] == "SC",
"Therapist" = .data[["S8FollowUpBy"]] == "T",
"CommunityNurse" = .data[["S8FollowUpBy"]] == "DN",
"Voluntary" = .data[["S8FollowUpBy"]] == "VS",
"SecondaryCare" = .data[["S8FollowUpBy"]] == "SCC",
"Other" = .data[["S8FollowUpBy"]] == "O"),
new_numerators = tibble::tribble(
~numerator, ~fun, ~descriptor,
"GP",
rlang::expr(.data[["S8FollowUpBy"]] == "GP"),
"GP",
"StrokeCoordinator",
rlang::expr(.data[["S8FollowUpBy"]] == "SC"),
"Stroke coordinator",
"Therapist",
rlang::expr(.data[["S8FollowUpBy"]] == "T"),
"Therapist",
"CommunityNurse",
rlang::expr(.data[["S8FollowUpBy"]] == "DN"),
"Community nurse",
"Voluntary",
rlang::expr(.data[["S8FollowUpBy"]] == "VS"),
"Voluntary",
"SecondaryCare",
rlang::expr(.data[["S8FollowUpBy"]] == "SCC"),
"Secondary care",
"Other",
rlang::expr(.data[["S8FollowUpBy"]] == "O"),
"Other"),
csv_columns = c("S8FollowUpBy",
"S8FollowUp"),
measure_type = "discrete"),
FollowUpMood = audit_measure(
stem_name = "FollowUpMood",
description = "Mood, behaviour, cognition screening",
exclusions = rlang::expr(.data[["S8FollowUp"]] != "Y"),
numerators = rlang::exprs(
"Yes" = .data[["S8MoodBehaviourCognitiveScreened"]] == TRUE,
"No" = .data[["S8MoodBehaviourCognitiveScreened"]] == FALSE,
"NoBut" = is.na(.data[["S8MoodBehaviourCognitiveScreened"]])),
new_numerators = tibble::tribble(
~numerator, ~fun, ~descriptor,
"Yes",
rlang::expr(.data[["S8MoodBehaviourCognitiveScreened"]] == TRUE),
"Yes",
"No",
rlang::expr(.data[["S8MoodBehaviourCognitiveScreened"]] == FALSE),
"No",
"NoBut",
rlang::expr(is.na(.data[["S8MoodBehaviourCognitiveScreened"]])),
"No but"),
csv_columns = c("S8MoodBehaviourCognitiveScreened",
"S8FollowUp"),
measure_type = "discrete"),
FollowUpMoodSupportNeeded = audit_measure(
stem_name = "FollowUpMood",
description = "Mood, behaviour, cognition screening",
exclusions = rlang::expr(
.data[["S8MoodBehaviourCognitiveScreened"]] != "Y"),
numerators = rlang::expr(
.data[["S8MoodBehaviourCognitiveSupportNeeded"]] == TRUE),
new_numerators = rlang::expr(
.data[["S8MoodBehaviourCognitiveSupportNeeded"]] == TRUE),
csv_columns = c("S8MoodBehaviourCognitiveSupportNeeded",
"S8MoodBehaviourCognitiveScreened"),
measure_type = "discrete"),
FollowUpPsychologicalSupport = audit_measure(
stem_name = "FollowUpPsychologicalSupport",
description = glue::glue(
"If support needed, psychological support received since
discharge"),
exclusions = rlang::expr(
.data[["S8MoodBehaviourCognitiveSupportNeeded"]] != TRUE),
numerators = rlang::exprs(
"Yes" = .data[[
"S8MoodBehaviourCognitivePsychologicalSupport"]] == TRUE,
"No" = .data[[
"S8MoodBehaviourCognitivePsychologicalSupport"]] == FALSE,
"NoBut" = is.na(.data[[
"S8MoodBehaviourCognitivePsychologicalSupport"]])),
new_numerators = tibble::tribble(
~numerator, ~fun, ~descriptor,
"Yes",
rlang::expr(.data[["S8MoodBehaviourCognitivePsychologicalSupport"]] == TRUE),
"Yes",
"No",
rlang::expr(.data[["S8MoodBehaviourCognitivePsychologicalSupport"]] == FALSE),
"No",
"NoBut",
rlang::expr(is.na(.data[["S8MoodBehaviourCognitivePsychologicalSupport"]])),
"No but"),
csv_columns = c("S8MoodBehaviourCognitivePsychologicalSupport",
"S8MoodBehaviourCognitiveSupportNeeded"),
measure_type = "discrete"),
FollowUpLiving = audit_measure(
stem_name = "FollowUpLiving",
description = "Where the patient is living",
exclusions = rlang::expr(.data[["S8FollowUp"]] != "Y"),
numerators = rlang::exprs(
"Home" = .data[["S8Living"]] == "H",
"CareHome" = .data[["S8Living"]] == "CH",
"Other" = .data[["S8Living"]] == "O"),
new_numerators = tibble::tribble(
~numerator, ~fun, ~descriptor,
"Home",
rlang::expr(.data[["S8Living"]] == "H"),
"Home",
"CareHome",
rlang::expr(.data[["S8Living"]] == "CH"),
"Care home",
"Other",
rlang::expr(.data[["S8Living"]] == "O"),
"Other"),
csv_columns = c("S8Living",
"S8FollowUp"),
measure_type = "discrete"),
FollowUpRankin6Month = audit_measure(
stem_name = "FollowUpRankinNotKnown",
description = "Modified Rankin Scale is not known",
exclusions = rlang::expr(.data[["S8FollowUp"]] != "Y"),
numerators = rlang::exprs(
"0" = .data[["S8Rankin6Month"]] == 0,
"1" = .data[["S8Rankin6Month"]] == 1,
"2" = .data[["S8Rankin6Month"]] == 2,
"3" = .data[["S8Rankin6Month"]] == 3,
"4" = .data[["S8Rankin6Month"]] == 4,
"5" = .data[["S8Rankin6Month"]] == 5,
"6" = (.data[["S7DischargeType"]] == "D") |
(.data[["S8FollowUp"]] == "ND"),
"NotKnown" = is.na(.data[["S8Rankin6Month"]])),
new_numerators = tibble::tribble(
~numerator, ~fun, ~descriptor,
"0",
rlang::expr(.data[["S8Rankin6Month"]] == 0),
"0",
"1",
rlang::expr(.data[["S8Rankin6Month"]] == 1),
"1",
"2",
rlang::expr(.data[["S8Rankin6Month"]] == 2),
"2",
"3",
rlang::expr(.data[["S8Rankin6Month"]] == 3),
"3",
"4",
rlang::expr(.data[["S8Rankin6Month"]] == 4),
"4",
"5",
rlang::expr(.data[["S8Rankin6Month"]] == 5),
"5",
"6",
rlang::expr((.data[["S7DischargeType"]] == "D") |
(.data[["S8FollowUp"]] == "ND")),
"6",
"NotKnown",
rlang::expr(is.na(.data[["S8Rankin6Month"]])),
"Not known"),
csv_columns = c("S8Rankin6Month",
"S7DischargeType",
"S8FollowUp",
"S8FollowUp"),
measure_type = "discrete"),
FollowUpAtrialFibrillation = audit_measure(
stem_name = "FollowUpAtrialFibrillation",
description = glue::glue(
"Persistent, permanent or paroxysmal Atrial Fibrillation (AF)
at the time of six month follow-up assessment"),
exclusions = rlang::expr(.data[["S8FollowUp"]] != "Y"),
numerators = rlang::exprs(
"Yes" = .data[["S8PersistentAtrialFibrillation"]] == TRUE,
"No" = .data[["S8PersistentAtrialFibrillation"]] == FALSE,
"NoBut" = is.na(.data[["S8PersistentAtrialFibrillation"]])),
new_numerators = tibble::tribble(
~numerator, ~fun, ~descriptor,
"Yes",
rlang::expr(.data[["S8PersistentAtrialFibrillation"]] == TRUE),
"Yes",
"No",
rlang::expr(.data[["S8PersistentAtrialFibrillation"]] == FALSE),
"No",
"NoBut",
rlang::expr(is.na(.data[["S8PersistentAtrialFibrillation"]])),
"No but"),
csv_columns = c("S8PersistentAtrialFibrillation",
"S8FollowUp"),
measure_type = "discrete"),
FollowUpAFFromAdmission = audit_measure(
stem_name = "FollowUpAFFromAdmission",
description = glue::glue(
"If patient is in AF at six month follow-up assessment, was
also in AF when first admitted to hospital"),
exclusions = rlang::expr(
.data[["S8PersistentAtrialFibrillation"]] != TRUE),
numerators = rlang::expr(
.data[["S2CoMAtrialFibrillation"]] == TRUE),
new_numerators = rlang::expr(
.data[["S2CoMAtrialFibrillation"]] == TRUE),
csv_columns = c("S2CoMAtrialFibrillation",
"S8PersistentAtrialFibrillation"),
measure_type = "discrete"),
FollowUpAFFromDischarge = audit_measure(
stem_name = "FollowUpAFFromDischarge",
description = glue::glue(
"If patient is in AF at six month follow-assessment, was also
in AF when discharged from inpatient care"),
exclusions = rlang::expr(
.data[["S8PersistentAtrialFibrillation"]] != TRUE),
numerators = rlang::expr(
.data[["S7DischargeAtrialFibrillation"]] == TRUE),
new_numerators = rlang::expr(
.data[["S7DischargeAtrialFibrillation"]] == TRUE),
csv_columns = c("S7DischargeAtrialFibrillation",
"S8PersistentAtrialFibrillation"),
measure_type = "discrete"),
FollowUpAFOnAnticoagulant = audit_measure(
stem_name = "FollowUpAFOnAnticoagulant",
description = glue::glue(
"If patient is in AF at six month follow-up assessment, then
taking anti-coagulant"),
exclusions = rlang::expr(
.data[["S8PersistentAtrialFibrillation"]] != TRUE),
numerators = rlang::expr(
.data[["S8TakingAnticoagulent"]] == TRUE),
new_numerators = rlang::expr(
.data[["S8TakingAnticoagulent"]] == TRUE),
csv_columns = c("S8TakingAnticoagulent",
"S8PersistentAtrialFibrillation"),
measure_type = "discrete"),
FollowUpTakingAntiplatelet = audit_measure(
stem_name = "FollowUpTakingAntiplatelet",
description = "Taking antiplatelet",
exclusions = rlang::expr(.data[["S8FollowUp"]] != "Y"),
numerators = rlang::exprs(
"Yes" = .data[["S8TakingAntiplateletDrug"]] == TRUE,
"No" = .data[["S8TakingAntiplateletDrug"]] == FALSE,
"NoBut" = is.na(.data[["S8TakingAntiplateletDrug"]])),
new_numerators = tibble::tribble(
~numerator, ~fun, ~descriptor,
"Yes",
rlang::expr(.data[["S8TakingAntiplateletDrug"]] == TRUE),
"Yes",
"No",
rlang::expr(.data[["S8TakingAntiplateletDrug"]] == FALSE),
"No",
"NoBut",
rlang::expr(is.na(.data[["S8TakingAntiplateletDrug"]])),
"No but"),
csv_columns = c("S8TakingAntiplateletDrug",
"S8FollowUp"),
measure_type = "discrete"),
FollowUpTakingAnticoagulant = audit_measure(
stem_name = "FollowUpTakingAnticoagulant",
description = "Taking anticoagulant",
exclusions = rlang::expr(.data[["S8FollowUp"]] != "Y"),
numerators = rlang::exprs(
"Yes" = .data[["S8TakingAnticoagulent"]] == TRUE,
"No" = .data[["S8TakingAnticoagulent"]] == FALSE,
"NoBut" = is.na(.data[["S8TakingAnticoagulent"]])),
new_numerators = tibble::tribble(
~numerator, ~fun, ~descriptor,
"Yes",
rlang::expr(.data[["S8TakingAnticoagulent"]] == TRUE),
"Yes",
"No",
rlang::expr(.data[["S8TakingAnticoagulent"]] == FALSE),
"No",
"NoBut",
rlang::expr(is.na(.data[["S8TakingAnticoagulent"]])),
"No but"),
csv_columns = c("S8TakingAnticoagulent",
"S8FollowUp"),
measure_type = "discrete"),
FollowUpAnticoagulantSinceDischarge = audit_measure(
stem_name = "FollowUpAnticoagulantSinceDischarge",
description = glue::glue(
"If patient was discharged on anti-coagulant, still taking at
six month follow-up assessment"),
exclusions = rlang::expr(
.data[["S8TakingAnticoagulent"]] != TRUE),
numerators = rlang::expr(.data[[
"S7DischargeAtrialFibrillationAnticoagulation"]] == TRUE),
new_numerators = rlang::expr(.data[[
"S7DischargeAtrialFibrillationAnticoagulation"]] == TRUE),
csv_columns = c("S7DischargeAtrialFibrillationAnticoagulation",
"S8TakingAnticoagulent"),
measure_type = "discrete"),
FollowUpTakingLipidLowering = audit_measure(
stem_name = "FollowUpTakingLipidLowering",
description = "Taking lipid lowering drug",
exclusions = rlang::expr(.data[["S8FollowUp"]] != "Y"),
numerators = rlang::exprs(
"Yes" = .data[["S8TakingLipidLowering"]] == TRUE,
"No" = .data[["S8TakingLipidLowering"]] == FALSE,
"NoBut" = is.na(.data[["S8TakingLipidLowering"]])),
new_numerators = tibble::tribble(
~numerator, ~fun, ~descriptor,
"Yes",
rlang::expr(.data[["S8TakingLipidLowering"]] == TRUE),
"Yes",
"No",
rlang::expr(.data[["S8TakingLipidLowering"]] == FALSE),
"No",
"NoBut",
rlang::expr(is.na(.data[["S8TakingLipidLowering"]])),
"No but"),
csv_columns = c("S8TakingLipidLowering",
"S8FollowUp"),
measure_type = "discrete"),
FollowUpTakingAntihypertensive = audit_measure(
stem_name = "FollowUpTakingAntihypertensive",
description = "Taking antihypertensive",
exclusions = rlang::expr(.data[["S8FollowUp"]] != "Y"),
numerators = rlang::exprs(
"Yes" = .data[["S8TakingAntihypertensive"]] == TRUE,
"No" = .data[["S8TakingAntihypertensive"]] == FALSE,
"NoBut" = is.na(.data[["S8TakingAntihypertensive"]])),
new_numerators = tibble::tribble(
~numerator, ~fun, ~descriptor,
"Yes",
rlang::expr(.data[["S8TakingAntihypertensive"]] == TRUE),
"Yes",
"No",
rlang::expr(.data[["S8TakingAntihypertensive"]] == FALSE),
"No",
"NoBut",
rlang::expr(is.na(.data[["S8TakingAntihypertensive"]])),
"No but"),
csv_columns = c("S8TakingAntihypertensive",
"S8FollowUp"),
measure_type = "discrete"),
SinceStrokeAnotherStroke = audit_measure(
stem_name = "SinceStrokeAnotherStroke",
description = "Since stroke, another stroke",
exclusions = rlang::expr(.data[["S8FollowUp"]] != "Y"),
numerators = rlang::exprs(
"Yes" = .data[["S8SinceStrokeAnotherStroke"]] == TRUE,
"No" = .data[["S8SinceStrokeAnotherStroke"]] == FALSE,
"NoBut" = is.na(.data[["S8SinceStrokeAnotherStroke"]])),
new_numerators = tibble::tribble(
~numerator, ~fun, ~descriptor,
"Yes",
rlang::expr(.data[["S8SinceStrokeAnotherStroke"]] == TRUE),
"Yes",
"No",
rlang::expr(.data[["S8SinceStrokeAnotherStroke"]] == FALSE),
"No",
"NoBut",
rlang::expr(is.na(.data[["S8SinceStrokeAnotherStroke"]])),
"No but"),
csv_columns = c("S8SinceStrokeAnotherStroke",
"S8FollowUp"),
measure_type = "discrete"),
SinceStrokeMyocardialInfarction = audit_measure(
stem_name = "SinceStrokeMyocardialInfarction",
description = "Since stroke, myocardial infarction",
exclusions = rlang::expr(.data[["S8FollowUp"]] != "Y"),
numerators = rlang::exprs(
"Yes" = .data[["S8SinceStrokeMyocardialInfarction"]] == TRUE,
"No" = .data[["S8SinceStrokeMyocardialInfarction"]] == FALSE,
"NoBut" = is.na(.data[["S8SinceStrokeMyocardialInfarction"]])),
new_numerators = tibble::tribble(
~numerator, ~fun, ~descriptor,
"Yes",
rlang::expr(.data[["S8SinceStrokeMyocardialInfarction"]] == TRUE),
"Yes",
"No",
rlang::expr(.data[["S8SinceStrokeMyocardialInfarction"]] == FALSE),
"No",
"NoBut",
rlang::expr(is.na(.data[["S8SinceStrokeMyocardialInfarction"]])),
"No but"),
csv_columns = c("S8SinceStrokeMyocardialInfarction",
"S8FollowUp"),
measure_type = "discrete"),
SinceStrokeHospitalisation = audit_measure(
stem_name = "SinceStrokeHospitalisation",
description =
"Since stroke, other illness requiring hospitalisation",
exclusions = rlang::expr(.data[["S8FollowUp"]] != "Y"),
numerators = rlang::exprs(
"Yes" =
.data[["S8SinceStrokeOtherHospitalisationIllness"]] == TRUE,
"No" =
.data[["S8SinceStrokeOtherHospitalisationIllness"]] == FALSE,
"NoBut" =
is.na(.data[["S8SinceStrokeOtherHospitalisationIllness"]])),
new_numerators = tibble::tribble(
~numerator, ~fun, ~descriptor,
"Yes",
rlang::expr(.data[["S8SinceStrokeOtherHospitalisationIllness"]] == TRUE),
"Yes",
"No",
rlang::expr(.data[["S8SinceStrokeOtherHospitalisationIllness"]] == FALSE),
"No",
"NoBut",
rlang::expr(is.na(.data[["S8SinceStrokeOtherHospitalisationIllness"]])),
"No but"),
csv_columns = c("S8SinceStrokeOtherHospitalisationIllness",
"S8FollowUp"),
measure_type = "discrete"),
# ClinicianAssessedWithin1hr ===================================
ClinicianAssessedWithin1hr = audit_measure(
stem_name = "ClinicianAssessedWithin1hr",
description = "Assessed by stroke consultant or nurse within 1 hr",
exclusions = NULL,
numerators = rlang::expr(
(!!ssnap_field[["ClockStartToConsultantMins"]] <= 60) |
(!!ssnap_field[["ClockStartToStrokeNurseMins"]] <= 60)),
new_numerators = rlang::expr(
(!!ssnap_field[["ClockStartToConsultantMins"]] <= 60) |
(!!ssnap_field[["ClockStartToStrokeNurseMins"]] <= 60)),
csv_columns = c("S1PatientClockStartDateTime",
"S3StrokeNurseAssessedDateTime",
"S3StrokeConsultantAssessedDateTime"),
measure_type = "discrete"),
# tPACriticalHourStandardWithin1hr =============================
tPACriticalHourStandardWithin1hr = audit_measure(
stem_name = "tPACriticalHourStandardWithin1hr",
description = glue::glue("
If an ischaemic stroke arriving within 4hrs of onset,
was thrombolysis administered within 1 hour"),
exclusions = rlang::expr(
(tidyr::replace_na(!! ssnap_field[["OnsetToArrivalTimeMins"]], 999)
> (4 * 60)) |
(!.data[["S2StrokeTypeIsInfarct"]]) |
((.data[["S2Thrombolysis"]] == "NB") &
bitwAnd(.data[["S2ThrombolysisNoBut"]],
ssnapinterface::tpa_no_but["Refusal"])) |
((.data[["S2Thrombolysis"]] == "NB") &
bitwAnd(.data[["S2ThrombolysisNoBut"]],
ssnapinterface::tpa_no_but["Medication"])) |
.data[["S2IAI"]]
),
numerators = rlang::expr(
!! ssnap_field[["ClockStartToThrombolysisMins"]] <= 60),
new_numerators = rlang::expr(
!! ssnap_field[["ClockStartToThrombolysisMins"]] <= 60),
csv_columns = c("S1PatientClockStartDateTime",
"S1OnsetInHospital",
"S1OnsetDateIsPrecise",
"S1OnsetTimeIsPrecise",
"S1OnsetDateTime",
"S2StrokeTypeIsInfarct",
"S2ThrombolysisDateTime",
"S2Thrombolysis"),
measure_type = "discrete")
)
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
Embedding an R snippet on your website
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.