asthma_01 {nemsqar} | R Documentation |
Asthma-01 Calculation
Description
Calculates the NEMSQA Asthma-01 measure.
Calculates key statistics related to asthma-related incidents in an EMS dataset, specifically focusing on cases where 911 was called for respiratory distress, and certain medications were administered. This function segments the data by age into adult and pediatric populations, computing the proportion of cases that received beta-agonist treatment.
Usage
asthma_01(
df = NULL,
patient_scene_table = NULL,
response_table = NULL,
situation_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,
esituation_11_col,
esituation_12_col,
emedications_03_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("Respiratory Distress", "Respiratory Distress",
"Chest Pain", "Respiratory Distress", "Respiratory Distress"),
esituation_12 = c("Asthma", "Asthma", "Other condition", "Asthma", "Asthma"),
emedications_03 = c("Albuterol", "Albuterol", "Epinephrine", "None",
"Albuterol")
)
# Run the function
# Return 95% confidence intervals using the Wilson method
asthma_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,
emedications_03_col = emedications_03,
confidence_interval = TRUE
)