Nothing
R/trauma_08.R
In nemsqar: National Emergency Medical Service Quality Alliance Measure Calculations
Defines functions
trauma_08
Documented in
trauma_08
#' @title Trauma-08 Calculation
#'
#' @description
#'
#' This function calculates the Trauma-08 measure, which evaluates the
#completeness ' of pain scale documentation for patients experiencing traumatic
#injury. It determines ' the total population, adult population, and pediatric
#population meeting the criteria ' for the Trauma-08 measure.
#
#' @param df A data frame or tibble containing EMS data with all relevant
#' columns. Default is `NULL`.
#' @param patient_scene_table A data frame or tibble containing only epatient
#' and escene fields as a fact table. Default is `NULL`.
#' @param response_table A data frame or tibble containing only the eresponse
#' fields needed for this measure's calculations. Default is `NULL`.
#' @param situation_table A data frame or tibble containing only the esituation
#' fields needed for this measure's calculations. Default is `NULL`.
#' @param disposition_table A data frame or tibble containing only the
#' edisposition fields needed for this measure's calculations. Default is
#' `NULL`.
#' @param vitals_table A data frame or tibble containing only the evitals fields
#' needed for this measure's calculations. Default is `NULL`.
#' @param erecord_01_col A column specifying unique patient records.
#' @param incident_date_col Column that contains the incident date. This
#' defaults to `NULL` as it is optional in case not available due to PII
#' restrictions.
#' @param patient_DOB_col Column that contains the patient's date of birth. This
#' defaults to `NULL` as it is optional in case not available due to PII
#' restrictions.
#' @param epatient_15_col A column indicating the patient’s age in numeric form.
#' @param epatient_16_col A column specifying the unit of patient age (e.g.,
#' "Years", "Days").
#' @param esituation_02_col A column containing information about the nature of
#' the patient’s condition (e.g., injury type).
#' @param eresponse_05_col A column specifying the type of response (e.g., 911
#' codes).
#' @param transport_disposition_col A column specifying transport disposition
#' for the patient.
#' @param evitals_06_col A column containing systolic blood pressure (SBP) data
#' from initial vital signs.
#' @param evitals_14_col A column containing respiratory rate data from initial
#' vital signs.
#' @param evitals_23_col A column containing total Glasgow Coma Scale (GCS)
#' scores from initial vital signs.
#' @param confidence_interval `r lifecycle::badge("experimental")` Logical. If
#' `TRUE`, the function calculates a confidence interval for the proportion
#' estimate.
#' @param method `r lifecycle::badge("experimental")`Character. Specifies the
#' method used to calculate confidence intervals. Options are `"wilson"`
#' (Wilson score interval) and `"clopper-pearson"` (exact binomial interval).
#' Partial matching is supported, so `"w"` and `"c"` can be used as shorthand.
#' @param conf.level `r lifecycle::badge("experimental")`Numeric. The confidence
#' level for the interval, expressed as a proportion (e.g., 0.95 for a 95%
#' confidence interval). Defaults to 0.95.
#' @param correct `r lifecycle::badge("experimental")`Logical. If `TRUE`,
#' applies a continuity correction to the Wilson score interval when `method =
#' "wilson"`. Defaults to `TRUE`.
#' @param ... optional additional arguments to pass onto `dplyr::summarize`.
#'
#' @return A data.frame summarizing results for two population groups (All,
#' Adults and Peds) with the following columns:
#' - `pop`: Population type (All, Adults, and Peds).
#' - `numerator`: Count of incidents meeting the measure.
#' - `denominator`: Total count of included incidents.
#' - `prop`: Proportion of incidents meeting the measure.
#' - `prop_label`: Proportion formatted as a percentage with a specified number
#' of decimal places.
#' - `lower_ci`: Lower bound of the confidence interval for `prop`
#' (if `confidence_interval = TRUE`).
#' - `upper_ci`: Upper bound of the confidence interval for `prop`
#' (if `confidence_interval = TRUE`).
#'
#' @examples
#'
#' # Synthetic test data
#' test_data <- tibble::tibble(
#' erecord_01 = c("R1", "R2", "R3", "R4", "R5"),
#' epatient_15 = c(34, 5, 45, 2, 60), # Ages
#' epatient_16 = c("Years", "Years", "Years", "Months", "Years"),
#' eresponse_05 = rep(2205001, 5),
#' esituation_02 = rep("Yes", 5),
#' evitals_06 = c(100, 90, 80, 70, 85),
#' evitals_14 = c(30, 9, 8, 7, 31),
#' evitals_23 = c(6, 7, 8, 8, 7),
#' edisposition_30 = c(4230001, 4230003, 4230001, 4230007, 4230007)
#' )
#'
#' # Run function with the first and last pain score columns
#' # Return 95% confidence intervals using the Wilson method
#' trauma_08(
#' df = test_data,
#' erecord_01_col = erecord_01,
#' incident_date_col = NULL,
#' patient_DOB_col = NULL,
#' epatient_15_col = epatient_15,
#' epatient_16_col = epatient_16,
#' eresponse_05_col = eresponse_05,
#' esituation_02_col = esituation_02,
#' evitals_06_col = evitals_06,
#' evitals_14_col = evitals_14,
#' evitals_23_col = evitals_23,
#' transport_disposition_col = edisposition_30,
#' confidence_interval = TRUE
#' )
#'
#' @author Nicolas Foss, Ed.D., MS
#'
#' @export
#'
trauma_08 <- function(df = NULL,
patient_scene_table = NULL,
response_table = NULL,
situation_table = NULL,
disposition_table = NULL,
vitals_table = NULL,
erecord_01_col,
incident_date_col = NULL,
patient_DOB_col = NULL,
epatient_15_col,
epatient_16_col,
esituation_02_col,
eresponse_05_col,
transport_disposition_col,
evitals_06_col,
evitals_14_col,
evitals_23_col,
confidence_interval = FALSE,
method = c("wilson", "clopper-pearson"),
conf.level = 0.95,
correct = TRUE,
...) {
# Set default method and adjustment method
method <- match.arg(method, choices = c("wilson", "clopper-pearson"))
if (
any(
!is.null(patient_scene_table),
!is.null(vitals_table),
!is.null(situation_table),
!is.null(disposition_table),
!is.null(response_table)
) &&
is.null(df)
) {
# Start timing the function execution
start_time <- Sys.time()
# Header
cli::cli_h1("Trauma-08")
# Header
cli::cli_h2("Gathering Records for Trauma-08")
# Gather the population of interest
trauma_08_populations <- trauma_08_population(
patient_scene_table = patient_scene_table,
response_table = response_table,
situation_table = situation_table,
vitals_table = vitals_table,
disposition_table = disposition_table,
erecord_01_col = {{ erecord_01_col }},
incident_date_col = {{ incident_date_col }},
patient_DOB_col = {{ patient_DOB_col }},
epatient_15_col = {{ epatient_15_col }},
epatient_16_col = {{ epatient_16_col }},
esituation_02_col = {{ esituation_02_col }},
eresponse_05_col = {{ eresponse_05_col }},
evitals_06_col = {{ evitals_06_col }},
evitals_14_col = {{ evitals_14_col }},
evitals_23_col = {{ evitals_23_col }},
transport_disposition_col = {{ transport_disposition_col }}
)
# Create a separator
cli::cli_text("\n")
# Header for calculations
cli::cli_h2("Calculating Trauma-08")
# summarize
trauma.08 <- results_summarize(
total_population = NULL,
adult_population = trauma_08_populations$adults,
peds_population = trauma_08_populations$peds,
population_names = c("adults", "peds"),
measure_name = "Trauma-08",
numerator_col = VITALS,
confidence_interval = confidence_interval,
method = method,
conf.level = conf.level,
correct = correct,
...
)
# create a separator
cli::cli_text("\n")
# Calculate and display the runtime
end_time <- Sys.time()
run_time_secs <- difftime(end_time, start_time, units = "secs")
run_time_secs <- as.numeric(run_time_secs)
if (run_time_secs >= 60) {
run_time <- round(run_time_secs / 60, 2) # Convert to minutes and round
cli::cli_alert_success("Function completed in {cli::col_green(paste0(run_time, 'm'))}.")
} else {
run_time <- round(run_time_secs, 2) # Keep in seconds and round
cli::cli_alert_success("Function completed in {cli::col_green(paste0(run_time, 's'))}.")
}
# create a separator
cli::cli_text("\n")
# when confidence interval is "wilson", check for n < 10
# to warn about incorrect Chi-squared approximation
if (any(trauma.08$denominator < 10) && method == "wilson" && confidence_interval) {
cli::cli_warn("In {.fn prop.test}: Chi-squared approximation may be incorrect for any n < 10.")
}
return(trauma.08)
} else if (
any(
is.null(patient_scene_table),
is.null(vitals_table),
is.null(situation_table),
is.null(disposition_table),
is.null(response_table)
) &&
!is.null(df)
) {
# Start timing the function execution
start_time <- Sys.time()
# Header
cli::cli_h1("Trauma-08")
# Header
cli::cli_h2("Gathering Records for Trauma-08")
# Gather the population of interest
trauma_08_populations <- trauma_08_population(
df = df,
erecord_01_col = {{ erecord_01_col }},
incident_date_col = {{ incident_date_col }},
patient_DOB_col = {{ patient_DOB_col }},
epatient_15_col = {{ epatient_15_col }},
epatient_16_col = {{ epatient_16_col }},
esituation_02_col = {{ esituation_02_col }},
eresponse_05_col = {{ eresponse_05_col }},
evitals_06_col = {{ evitals_06_col }},
evitals_14_col = {{ evitals_14_col }},
evitals_23_col = {{ evitals_23_col }},
transport_disposition_col = {{ transport_disposition_col }}
)
# Create a separator
cli::cli_text("\n")
# Header for calculations
cli::cli_h2("Calculating Trauma-08")
# summarize
trauma.08 <- results_summarize(
total_population = NULL,
adult_population = trauma_08_populations$adults,
peds_population = trauma_08_populations$peds,
population_names = c("adults", "peds"),
measure_name = "Trauma-08",
numerator_col = VITALS,
confidence_interval = confidence_interval,
method = method,
conf.level = conf.level,
correct = correct,
...
)
# create a separator
cli::cli_text("\n")
# Calculate and display the runtime
end_time <- Sys.time()
run_time_secs <- difftime(end_time, start_time, units = "secs")
run_time_secs <- as.numeric(run_time_secs)
if (run_time_secs >= 60) {
run_time <- round(run_time_secs / 60, 2) # Convert to minutes and round
cli::cli_alert_success("Function completed in {cli::col_green(paste0(run_time, 'm'))}.")
} else {
run_time <- round(run_time_secs, 2) # Keep in seconds and round
cli::cli_alert_success("Function completed in {cli::col_green(paste0(run_time, 's'))}.")
}
# create a separator
cli::cli_text("\n")
# when confidence interval is "wilson", check for n < 10
# to warn about incorrect Chi-squared approximation
if (any(trauma.08$denominator < 10) && method == "wilson" && confidence_interval) {
cli::cli_warn("In {.fn prop.test}: Chi-squared approximation may be incorrect for any n < 10.")
}
return(trauma.08)
}
}
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Defines functions trauma_08
Documented in trauma_08
#' @title Trauma-08 Calculation
#'
#' @description
#'
#' This function calculates the Trauma-08 measure, which evaluates the
#completeness ' of pain scale documentation for patients experiencing traumatic
#injury. It determines ' the total population, adult population, and pediatric
#population meeting the criteria ' for the Trauma-08 measure.
#
#' @param df A data frame or tibble containing EMS data with all relevant
#' columns. Default is `NULL`.
#' @param patient_scene_table A data frame or tibble containing only epatient
#' and escene fields as a fact table. Default is `NULL`.
#' @param response_table A data frame or tibble containing only the eresponse
#' fields needed for this measure's calculations. Default is `NULL`.
#' @param situation_table A data frame or tibble containing only the esituation
#' fields needed for this measure's calculations. Default is `NULL`.
#' @param disposition_table A data frame or tibble containing only the
#' edisposition fields needed for this measure's calculations. Default is
#' `NULL`.
#' @param vitals_table A data frame or tibble containing only the evitals fields
#' needed for this measure's calculations. Default is `NULL`.
#' @param erecord_01_col A column specifying unique patient records.
#' @param incident_date_col Column that contains the incident date. This
#' defaults to `NULL` as it is optional in case not available due to PII
#' restrictions.
#' @param patient_DOB_col Column that contains the patient's date of birth. This
#' defaults to `NULL` as it is optional in case not available due to PII
#' restrictions.
#' @param epatient_15_col A column indicating the patient’s age in numeric form.
#' @param epatient_16_col A column specifying the unit of patient age (e.g.,
#' "Years", "Days").
#' @param esituation_02_col A column containing information about the nature of
#' the patient’s condition (e.g., injury type).
#' @param eresponse_05_col A column specifying the type of response (e.g., 911
#' codes).
#' @param transport_disposition_col A column specifying transport disposition
#' for the patient.
#' @param evitals_06_col A column containing systolic blood pressure (SBP) data
#' from initial vital signs.
#' @param evitals_14_col A column containing respiratory rate data from initial
#' vital signs.
#' @param evitals_23_col A column containing total Glasgow Coma Scale (GCS)
#' scores from initial vital signs.
#' @param confidence_interval `r lifecycle::badge("experimental")` Logical. If
#' `TRUE`, the function calculates a confidence interval for the proportion
#' estimate.
#' @param method `r lifecycle::badge("experimental")`Character. Specifies the
#' method used to calculate confidence intervals. Options are `"wilson"`
#' (Wilson score interval) and `"clopper-pearson"` (exact binomial interval).
#' Partial matching is supported, so `"w"` and `"c"` can be used as shorthand.
#' @param conf.level `r lifecycle::badge("experimental")`Numeric. The confidence
#' level for the interval, expressed as a proportion (e.g., 0.95 for a 95%
#' confidence interval). Defaults to 0.95.
#' @param correct `r lifecycle::badge("experimental")`Logical. If `TRUE`,
#' applies a continuity correction to the Wilson score interval when `method =
#' "wilson"`. Defaults to `TRUE`.
#' @param ... optional additional arguments to pass onto `dplyr::summarize`.
#'
#' @return A data.frame summarizing results for two population groups (All,
#' Adults and Peds) with the following columns:
#' - `pop`: Population type (All, Adults, and Peds).
#' - `numerator`: Count of incidents meeting the measure.
#' - `denominator`: Total count of included incidents.
#' - `prop`: Proportion of incidents meeting the measure.
#' - `prop_label`: Proportion formatted as a percentage with a specified number
#' of decimal places.
#' - `lower_ci`: Lower bound of the confidence interval for `prop`
#' (if `confidence_interval = TRUE`).
#' - `upper_ci`: Upper bound of the confidence interval for `prop`
#' (if `confidence_interval = TRUE`).
#'
#' @examples
#'
#' # Synthetic test data
#' test_data <- tibble::tibble(
#' erecord_01 = c("R1", "R2", "R3", "R4", "R5"),
#' epatient_15 = c(34, 5, 45, 2, 60), # Ages
#' epatient_16 = c("Years", "Years", "Years", "Months", "Years"),
#' eresponse_05 = rep(2205001, 5),
#' esituation_02 = rep("Yes", 5),
#' evitals_06 = c(100, 90, 80, 70, 85),
#' evitals_14 = c(30, 9, 8, 7, 31),
#' evitals_23 = c(6, 7, 8, 8, 7),
#' edisposition_30 = c(4230001, 4230003, 4230001, 4230007, 4230007)
#' )
#'
#' # Run function with the first and last pain score columns
#' # Return 95% confidence intervals using the Wilson method
#' trauma_08(
#' df = test_data,
#' erecord_01_col = erecord_01,
#' incident_date_col = NULL,
#' patient_DOB_col = NULL,
#' epatient_15_col = epatient_15,
#' epatient_16_col = epatient_16,
#' eresponse_05_col = eresponse_05,
#' esituation_02_col = esituation_02,
#' evitals_06_col = evitals_06,
#' evitals_14_col = evitals_14,
#' evitals_23_col = evitals_23,
#' transport_disposition_col = edisposition_30,
#' confidence_interval = TRUE
#' )
#'
#' @author Nicolas Foss, Ed.D., MS
#'
#' @export
#'
trauma_08 <- function(df = NULL,
patient_scene_table = NULL,
response_table = NULL,
situation_table = NULL,
disposition_table = NULL,
vitals_table = NULL,
erecord_01_col,
incident_date_col = NULL,
patient_DOB_col = NULL,
epatient_15_col,
epatient_16_col,
esituation_02_col,
eresponse_05_col,
transport_disposition_col,
evitals_06_col,
evitals_14_col,
evitals_23_col,
confidence_interval = FALSE,
method = c("wilson", "clopper-pearson"),
conf.level = 0.95,
correct = TRUE,
...) {
# Set default method and adjustment method
method <- match.arg(method, choices = c("wilson", "clopper-pearson"))
if (
any(
!is.null(patient_scene_table),
!is.null(vitals_table),
!is.null(situation_table),
!is.null(disposition_table),
!is.null(response_table)
) &&
is.null(df)
) {
# Start timing the function execution
start_time <- Sys.time()
# Header
cli::cli_h1("Trauma-08")
# Header
cli::cli_h2("Gathering Records for Trauma-08")
# Gather the population of interest
trauma_08_populations <- trauma_08_population(
patient_scene_table = patient_scene_table,
response_table = response_table,
situation_table = situation_table,
vitals_table = vitals_table,
disposition_table = disposition_table,
erecord_01_col = {{ erecord_01_col }},
incident_date_col = {{ incident_date_col }},
patient_DOB_col = {{ patient_DOB_col }},
epatient_15_col = {{ epatient_15_col }},
epatient_16_col = {{ epatient_16_col }},
esituation_02_col = {{ esituation_02_col }},
eresponse_05_col = {{ eresponse_05_col }},
evitals_06_col = {{ evitals_06_col }},
evitals_14_col = {{ evitals_14_col }},
evitals_23_col = {{ evitals_23_col }},
transport_disposition_col = {{ transport_disposition_col }}
)
# Create a separator
cli::cli_text("\n")
# Header for calculations
cli::cli_h2("Calculating Trauma-08")
# summarize
trauma.08 <- results_summarize(
total_population = NULL,
adult_population = trauma_08_populations$adults,
peds_population = trauma_08_populations$peds,
population_names = c("adults", "peds"),
measure_name = "Trauma-08",
numerator_col = VITALS,
confidence_interval = confidence_interval,
method = method,
conf.level = conf.level,
correct = correct,
...
)
# create a separator
cli::cli_text("\n")
# Calculate and display the runtime
end_time <- Sys.time()
run_time_secs <- difftime(end_time, start_time, units = "secs")
run_time_secs <- as.numeric(run_time_secs)
if (run_time_secs >= 60) {
run_time <- round(run_time_secs / 60, 2) # Convert to minutes and round
cli::cli_alert_success("Function completed in {cli::col_green(paste0(run_time, 'm'))}.")
} else {
run_time <- round(run_time_secs, 2) # Keep in seconds and round
cli::cli_alert_success("Function completed in {cli::col_green(paste0(run_time, 's'))}.")
}
# create a separator
cli::cli_text("\n")
# when confidence interval is "wilson", check for n < 10
# to warn about incorrect Chi-squared approximation
if (any(trauma.08$denominator < 10) && method == "wilson" && confidence_interval) {
cli::cli_warn("In {.fn prop.test}: Chi-squared approximation may be incorrect for any n < 10.")
}
return(trauma.08)
} else if (
any(
is.null(patient_scene_table),
is.null(vitals_table),
is.null(situation_table),
is.null(disposition_table),
is.null(response_table)
) &&
!is.null(df)
) {
# Start timing the function execution
start_time <- Sys.time()
# Header
cli::cli_h1("Trauma-08")
# Header
cli::cli_h2("Gathering Records for Trauma-08")
# Gather the population of interest
trauma_08_populations <- trauma_08_population(
df = df,
erecord_01_col = {{ erecord_01_col }},
incident_date_col = {{ incident_date_col }},
patient_DOB_col = {{ patient_DOB_col }},
epatient_15_col = {{ epatient_15_col }},
epatient_16_col = {{ epatient_16_col }},
esituation_02_col = {{ esituation_02_col }},
eresponse_05_col = {{ eresponse_05_col }},
evitals_06_col = {{ evitals_06_col }},
evitals_14_col = {{ evitals_14_col }},
evitals_23_col = {{ evitals_23_col }},
transport_disposition_col = {{ transport_disposition_col }}
)
# Create a separator
cli::cli_text("\n")
# Header for calculations
cli::cli_h2("Calculating Trauma-08")
# summarize
trauma.08 <- results_summarize(
total_population = NULL,
adult_population = trauma_08_populations$adults,
peds_population = trauma_08_populations$peds,
population_names = c("adults", "peds"),
measure_name = "Trauma-08",
numerator_col = VITALS,
confidence_interval = confidence_interval,
method = method,
conf.level = conf.level,
correct = correct,
...
)
# create a separator
cli::cli_text("\n")
# Calculate and display the runtime
end_time <- Sys.time()
run_time_secs <- difftime(end_time, start_time, units = "secs")
run_time_secs <- as.numeric(run_time_secs)
if (run_time_secs >= 60) {
run_time <- round(run_time_secs / 60, 2) # Convert to minutes and round
cli::cli_alert_success("Function completed in {cli::col_green(paste0(run_time, 'm'))}.")
} else {
run_time <- round(run_time_secs, 2) # Keep in seconds and round
cli::cli_alert_success("Function completed in {cli::col_green(paste0(run_time, 's'))}.")
}
# create a separator
cli::cli_text("\n")
# when confidence interval is "wilson", check for n < 10
# to warn about incorrect Chi-squared approximation
if (any(trauma.08$denominator < 10) && method == "wilson" && confidence_interval) {
cli::cli_warn("In {.fn prop.test}: Chi-squared approximation may be incorrect for any n < 10.")
}
return(trauma.08)
}
}
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