safety_04 {nemsqar} | R Documentation |
Safety-04 Calculation
Description
The safety_04
function processes EMS incident data for specific safety and
transport criteria, filtering by patient age and incident type to identify
cases that meet specified exclusion or inclusion criteria. This function
accommodates data with various EMS-specific codes, age descriptors, and
procedure identifiers.
Usage
safety_04(
df = NULL,
patient_scene_table = NULL,
response_table = NULL,
arrest_table = NULL,
injury_table = NULL,
procedures_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,
earrest_01_col,
einjury_03_col,
eprocedures_03_col,
edisposition_14_col,
transport_disposition_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),
earrest_01 = rep("No", 5),
einjury_03 = rep("non-injury", 5),
edisposition_14 = rep(4214001, 5),
edisposition_30 = rep(4230001, 5),
eprocedures_03 = rep("other response", 5)
)
# Run the function
# Return 95% confidence intervals using the Wilson method
safety_04(
df = test_data,
erecord_01_col = erecord_01,
epatient_15_col = epatient_15,
epatient_16_col = epatient_16,
eresponse_05_col = eresponse_05,
earrest_01_col = earrest_01,
einjury_03_col = einjury_03,
edisposition_14_col = edisposition_14,
transport_disposition_col = edisposition_30,
eprocedures_03_col = eprocedures_03,
confidence_interval = TRUE
)