ttr_01 {nemsqar} | R Documentation |
TTR-01 Calculation
Description
This function calculates the TTR-01 measure, which evaluates the completeness of vitals documentation for patients not experiencing cardiac arrest who were also not transported during a 911 response. It determines the total population, adult population, and pediatric population meeting the criteria for the TTR_01 measure.
Usage
ttr_01(
df = NULL,
patient_scene_table = NULL,
response_table = NULL,
disposition_table = NULL,
vitals_table = NULL,
arrest_table = NULL,
erecord_01_col,
incident_date_col = NULL,
patient_DOB_col = NULL,
epatient_15_col,
epatient_16_col,
eresponse_05_col,
transport_disposition_col,
earrest_01_col,
evitals_06_col,
evitals_07_col,
evitals_10_col,
evitals_12_col,
evitals_14_col,
evitals_23_col,
evitals_26_col,
confidence_interval = FALSE,
method = c("wilson", "clopper-pearson"),
conf.level = 0.95,
correct = TRUE,
...
)
Arguments
Value
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 forprop
(ifconfidence_interval = TRUE
). -
upper_ci
: Upper bound of the confidence interval forprop
(ifconfidence_interval = TRUE
).
Author(s)
Nicolas Foss, Ed.D., MS
Examples
# Synthetic test data
test_data <- tibble::tibble(
erecord_01 = c("R1", "R2", "R3", "R4", "R5"),
incident_date = as.Date(c("2025-01-01", "2025-01-05", "2025-02-01",
"2025-01-01", "2025-06-01")),
patient_dob = as.Date(c("2000-01-01", "2020-01-01", "2023-02-01",
"2023-01-01", "1970-06-01")),
epatient_15 = c(34, 5, 45, 2, 60), # Ages
epatient_16 = c("Years", "Years", "Years", "Months", "Years"),
eresponse_05 = rep(2205001, 5),
earrest_01 = rep("No", 5),
evitals_06 = c(100, 90, 80, 70, 85),
evitals_07 = c(80, 90, 50, 60, 87),
evitals_10 = c(110, 89, 88, 71, 85),
evitals_12 = c(50, 60, 70, 80, 75),
evitals_14 = c(30, 9, 8, 7, 31),
evitals_23 = c(6, 7, 8, 9, 10),
evitals_26 = c(3326007, 3326005, 3326003, 3326001, 3326007),
edisposition_30 = c(4230013, 4230009, 4230013, 4230009, 4230013)
)
# Run function with the first and last pain score columns
# Return 95% confidence intervals using the Wilson method
ttr_01(
df = test_data,
erecord_01_col = erecord_01,
incident_date_col = incident_date,
patient_DOB_col = patient_dob,
epatient_15_col = epatient_15,
epatient_16_col = epatient_16,
eresponse_05_col = eresponse_05,
earrest_01_col = earrest_01,
evitals_06_col = evitals_06,
evitals_07_col = evitals_07,
evitals_10_col = evitals_10,
evitals_12_col = evitals_12,
evitals_14_col = evitals_14,
evitals_23_col = evitals_23,
evitals_26_col = evitals_26,
transport_disposition_col = edisposition_30
)