respiratory_01 {nemsqar} | R Documentation |
Respiratory-01 Calculation
Description
The respiratory_01
function filters and analyzes data related to emergency
911 respiratory distress incidents, providing summary statistics for adult
and pediatric populations. This function uses specific data columns for 911
response codes, primary and secondary impressions, and vital signs to
calculate the proportion of cases with complete vital signs recorded,
stratified by age.
Usage
respiratory_01(
df = NULL,
patient_scene_table = NULL,
response_table = NULL,
situation_table = NULL,
vitals_table = NULL,
erecord_01_col,
incident_date_col = NULL,
patient_DOB_col = NULL,
epatient_15_col,
epatient_16_col,
eresponse_05_col,
esituation_11_col,
esituation_12_col,
evitals_12_col,
evitals_14_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"),
epatient_15 = c(34, 5, 45, 2, 60), # Ages
epatient_16 = c("Years", "Years", "Years", "Months", "Years"),
eresponse_05 = rep(2205001, 5),
esituation_11 = c(rep("J80", 3), rep("I50.9", 2)),
esituation_12 = c(rep("J80", 2), rep("I50.9", 3)),
evitals_12 = c(60, 59, 58, 57, 56),
evitals_14 = c(16, 15, 14, 13, 12)
)
# Run the function
# Return 95% confidence intervals using the Wilson method
respiratory_01(
df = test_data,
erecord_01_col = erecord_01,
epatient_15_col = epatient_15,
epatient_16_col = epatient_16,
eresponse_05_col = eresponse_05,
esituation_11_col = esituation_11,
esituation_12_col = esituation_12,
evitals_12_col = evitals_12,
evitals_14_col = evitals_14,
confidence_interval = TRUE
)