pediatrics_03b_population {nemsqar} | R Documentation |
Pediatrics-03B Populations
Description
Filters data down to the target populations for Pediatrics-03B, and categorizes records to identify needed information for the calculations.
Identifies key categories related to diabetes/hypoglycemia incidents in an EMS dataset, specifically focusing on cases where 911 was called for diabetes/hypoglycemia distress, certain medications were administered, and a weight is taken. This function segments the data into pediatric populations, computing the proportion of cases that have a documented weight.
Usage
pediatrics_03b_population(
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
)
Arguments
df |
A data frame or tibble containing emergency response records.
Default is |
patient_scene_table |
A data.frame or tibble containing only ePatient
and eScene fields as a fact table. Default is |
response_table |
A data.frame or tibble containing only the eResponse
fields needed for this measure's calculations. Default is |
exam_table |
A data.frame or tibble containing only the eExam fields
needed for this measure's calculations. Default is |
medications_table |
A data.frame or tibble containing only the
eMedications fields needed for this measure's calculations. Default is
|
erecord_01_col |
Column for unique EMS record identifiers. |
incident_date_col |
Column that contains the incident date. This
defaults to |
patient_DOB_col |
Column that contains the patient's date of birth. This
defaults to |
epatient_15_col |
Column giving the calculated age value. |
epatient_16_col |
Column giving the provided age unit value. |
eresponse_05_col |
Column containing the EMS response codes. |
eexam_01_col |
Column containing documented weight information. |
eexam_02_col |
Another column for weight documentation, if applicable. |
emedications_03_col |
Column indicating medication administration. |
emedications_04_col |
Column listing medications administered. |
Value
A list that contains the following:
a tibble with counts for each filtering step,
a tibble for each population of interest
a tibble for the initial population
a tibble for the total dataset with computations
Author(s)
Nicolas Foss, Ed.D., MS
Examples
# create tables to test correct functioning
patient_table <- tibble::tibble(
erecord_01 = c("R1", "R2", "R3", "R4", "R5"),
incident_date = as.Date(c("2025-01-01", "2025-01-05",
"2025-02-01", "2025-01-01",
"2025-06-01")
),
patient_dob = as.Date(c("2000-01-01", "2020-01-01",
"2023-02-01", "2023-01-01",
"1970-06-01")
),
epatient_15 = c(25, 5, 2, 2, 55), # Ages
epatient_16 = c("Years", "Years", "Years", "Years", "Years")
)
response_table <- tibble::tibble(
erecord_01 = c("R1", "R2", "R3", "R4", "R5"),
eresponse_05 = rep(2205001, 5)
)
exam_table <- tibble::tibble(
erecord_01 = c("R1", "R2", "R3", "R4", "R5"),
eexam_01 = c(60, 59, 58, 57, 56),
eexam_02 = c("Red", "Purple", "Grey", "Yellow", "Orange")
)
medications_table <- tibble::tibble(
erecord_01 = c("R1", "R2", "R3", "R4", "R5"),
emedications_03 = rep("stuff", 5),
emedications_04 = c("Inhalation", "pill", "liquid", "pill", "liquid"),
)
# test the success of the function
result <- pediatrics_03b_population(patient_scene_table = patient_table,
response_table = response_table,
exam_table = exam_table,
medications_table = medications_table,
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
)
# show the results of filtering at each step
result$filter_process