safety_02 {nemsqar} | R Documentation |
Safety-02 Calculation
Description
The safety_02
function calculates the Safety-02 metric, evaluating the
proportion of emergency medical calls involving transport where no lights and
sirens were used. This function categorizes the population into adult and
pediatric groups based on their age, and summarizes results with a total
population count as well.
Usage
safety_02(
df = NULL,
patient_scene_table = NULL,
response_table = NULL,
disposition_table = NULL,
erecord_01_col,
incident_date_col = NULL,
patient_DOB_col = NULL,
epatient_15_col,
epatient_16_col,
eresponse_05_col,
edisposition_18_col,
edisposition_28_col,
transport_disposition_cols,
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),
edisposition_18 = rep(4218015, 5),
edisposition_28 = rep(4228001, 5),
edisposition_30 = rep(4230001, 5)
)
# Run the function
# Return 95% confidence intervals using the Wilson method
safety_02(
df = test_data,
erecord_01_col = erecord_01,
epatient_15_col = epatient_15,
epatient_16_col = epatient_16,
eresponse_05_col = eresponse_05,
edisposition_18_col = edisposition_18,
edisposition_28_col = edisposition_28,
transport_disposition_cols = edisposition_30,
confidence_interval = TRUE
)