tbi_01_population {nemsqar} | R Documentation |
TBI-01 Populations
Description
This function screens for potential traumatic brain injury (TBI) cases based on specific criteria in a patient dataset. It produces a subset of the data with calculated variables for TBI identification.
Usage
tbi_01_population(
df = NULL,
patient_scene_table = NULL,
response_table = NULL,
situation_table = NULL,
disposition_table = NULL,
vitals_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,
transport_disposition_col,
evitals_06_col,
evitals_12_col,
evitals_16_col,
evitals_23_col,
evitals_26_col
)
Arguments
df |
A data frame or tibble containing the patient data. |
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 |
disposition_table |
A data.frame or tibble containing only the
edisposition fields needed for this measure's calculations. Default is
|
vitals_table |
A data.frame or tibble containing only the evitals fields
needed for this measure's calculations. Default is |
erecord_01_col |
Column name in df with the patient’s unique record ID. |
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 in df with the patient’s age value. |
epatient_16_col |
Column name in df with the patient’s age unit (e.g., years, months). |
eresponse_05_col |
Column name in df with response codes for the type of EMS call. |
esituation_11_col |
Column name in df with the primary provider impression. |
esituation_12_col |
Column name in df with the secondary provider impression. |
transport_disposition_col |
Column name in df with the transport disposition. |
evitals_06_col |
Column name in df with systolic blood pressure (SBP). |
evitals_12_col |
Column name in df with pulse oximetry values. |
evitals_16_col |
Column name in df with ETC02 values. values. |
evitals_23_col |
Column name in df with Glasgow Coma Scale (GCS) scores. |
evitals_26_col |
Column name in df with AVPU (alert, verbal, painful, unresponsive) 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 = c(rep("S02", 3), rep("S06", 2)),
esituation_12 = c(rep("S09.90", 2), rep("S06.0X9", 3)),
)
# vitals table
vitals_table <- tibble::tibble(
erecord_01 = c("R1", "R2", "R3", "R4", "R5"),
evitals_06 = c(85, 80, 100, 90, 82),
evitals_12 = c(95, 96, 97, 98, 99),
evitals_16 = c(35, 36, 37, 38, 39),
evitals_23 = rep(8, 5),
evitals_26 = c("Verbal", "Painful", "Unresponsive", "Verbal", "Painful")
)
# disposition table
disposition_table <- tibble::tibble(
erecord_01 = c("R1", "R2", "R3", "R4", "R5"),
edisposition_30 = c(4230001, 4230003, 4230001, 4230007, 4230007)
)
# test the success of the function
result <- tbi_01_population(patient_scene_table = patient_table,
response_table = response_table,
situation_table = situation_table,
vitals_table = vitals_table,
disposition_table = disposition_table,
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,
evitals_06_col = evitals_06,
evitals_12_col = evitals_12,
evitals_16_col = evitals_16,
evitals_23_col = evitals_23,
evitals_26_col = evitals_26,
transport_disposition_col = edisposition_30
)
# show the results of filtering at each step
result$filter_process