pediatrics_03b {nemsqar} | R Documentation |
Pediatrics-03B Calculation
Description
The function calculates a pediatric metric focused on EMS responses, specifically targeting responses that involve patients under 18 years of age, where certain weight-based medications were administered. This function filters EMS data to identify relevant 911 responses and further narrows down the dataset to cases involving children, calculating the proportion of cases with documented weight among those where weight-based medications were administered.
Usage
pediatrics_03b(
df = NULL,
patient_scene_table = NULL,
response_table = NULL,
exam_table = NULL,
medications_table = NULL,
erecord_01_col,
incident_date_col = NULL,
patient_DOB_col = NULL,
epatient_15_col,
epatient_16_col,
eresponse_05_col,
eexam_01_col,
eexam_02_col,
emedications_03_col,
emedications_04_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 (Peds) with the following columns:
-
pop
: Population type (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",
"2025-06-01", "2025-12-15")),
patient_dob = as.Date(c("2021-01-01", "2020-01-01", "2022-02-01",
"2023-06-01", "2019-12-15")),
epatient_15 = c(4, 5, 3, 2, 6), # Ages
epatient_16 = c("Years", "Years", "Years", "Years", "Years"),
eresponse_05 = rep(2205001, 5),
emedications_03 = rep("stuff", 5),
emedications_04 = c("Inhalation", "pill", "liquid", "pill", "liquid"),
eexam_01 = c(60, 59, 58, 57, 56),
eexam_02 = c("Red", "Purple", "Grey", "Yellow", "Orange")
)
# Run the function
# Return 95% confidence intervals using the Wilson method
pediatrics_03b(
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,
emedications_03_col = emedications_03,
emedications_04_col = emedications_04,
eexam_01_col = eexam_01,
eexam_02_col = eexam_02,
confidence_interval = TRUE
)