safety_04_population {nemsqar} | R Documentation |
Safety-04 Populations
Description
Filters data down to the target populations for Safety-04, and categorizes records to identify needed information for the calculations.
Identifies key categories related to a 911 request or interfacility request for patients less than 8 years of age during which patients are transported using a pediatric restraint device. This function segments the data by age into adult and pediatric populations.
Usage
safety_04_population(
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
)
Arguments
df |
A data frame or tibble containing EMS data where each row represents an individual observation. |
patient_scene_table |
A data frame or tibble containing fields from epatient and escene needed for this measure's calculations. |
response_table |
A data frame or tibble containing fields from eresponse needed for this measure's calculations. |
arrest_table |
A data frame or tibble containing fields from earrest needed for this measure's calculations. |
injury_table |
A data frame or tibble containing fields from einjury needed for this measure's calculations. |
procedures_table |
A data frame or tibble containing fields from eprocedures needed for this measure's calculations. |
disposition_table |
A data frame or tibble containing fields from edisposition needed for this measure's calculations. |
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 indicating the patient age. |
epatient_16_col |
Column name for the unit of age (e.g., "Years," "Months"). |
eresponse_05_col |
Column containing response transport codes. |
earrest_01_col |
Column with cardiac arrest status information. |
einjury_03_col |
Column describing traumatic injuries, expected as a list or text-separated entries. |
eprocedures_03_col |
Column listing procedures, assumed to contain multiple procedure codes/texts in each cell. |
edisposition_14_col |
Column for transport dispositions. |
transport_disposition_col |
Columns for primary and secondary transport dispositions. |
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)
)
# disposition table
disposition_table <- tibble::tibble(
erecord_01 = c("R1", "R2", "R3", "R4", "R5"),
edisposition_14 = rep(4214001, 5),
edisposition_30 = rep(4230001, 5),
)
# arrest table
arrest_table <- tibble::tibble(
erecord_01 = c("R1", "R2", "R3", "R4", "R5"),
earrest_01 = rep("No", 5)
)
# injury table
injury_table <- tibble::tibble(
erecord_01 = c("R1", "R2", "R3", "R4", "R5"),
einjury_03 = rep("non-injury", 5)
)
# procedures table
procedures_table <- tibble::tibble(
erecord_01 = c("R1", "R2", "R3", "R4", "R5"),
eprocedures_03 = rep("other response", 5)
)
# test the success of the function
result <- safety_04_population(patient_scene_table = patient_table,
response_table = response_table,
arrest_table = arrest_table,
injury_table = injury_table,
procedures_table = procedures_table,
disposition_table = disposition_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,
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
)
# show the results of filtering at each step
result$filter_process