seizure_02_population {nemsqar} | R Documentation |
Seizure-02 Populations
Description
Filters data down to the target populations for Seizure-02, and categorizes records to identify needed information for the calculations.
Identifies key categories 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.
Usage
seizure_02_population(
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
)
Arguments
df |
A data frame where each row is an observation, containing all necessary columns for analysis. |
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 |
situation_table |
A data.frame or tibble containing only the esituation
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 |
The column containing unique record identifiers for each encounter. |
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 name for patient age in numeric form. |
epatient_16_col |
Column name for age unit (e.g., |
eresponse_05_col |
Column name for response codes; "911" call codes are filtered. |
esituation_11_col |
Column name for primary impressions. |
esituation_12_col |
Column name for secondary impressions. |
emedications_03_col |
Column name for medications administered; ideally a list column or string with comma-separated values. |
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
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
response_table <- tibble::tibble(
erecord_01 = c("R1", "R2", "R3", "R4", "R5"),
eresponse_05 = rep(2205001, 5)
)
# situation table
situation_table <- tibble::tibble(
erecord_01 = c("R1", "R2", "R3", "R4", "R5"),
esituation_11 = rep("G40", 5),
esituation_12 = rep("r56", 5),
)
# medications table
medications_table <- tibble::tibble(
erecord_01 = c("R1", "R2", "R3", "R4", "R5"),
emedications_03 = rep(3322, 5)
)
# test the success of the function
result <- seizure_02_population(patient_scene_table = patient_table,
response_table = response_table,
situation_table = situation_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,
esituation_11_col = esituation_11,
esituation_12_col = esituation_12,
emedications_03_col = emedications_03
)
# show the results of filtering at each step
result$filter_process