stroke_01_population {nemsqar} | R Documentation |
Stroke-01 Populations
Description
Filters data down to the target populations for Stroke-01, and categorizes records to identify needed information for the calculations.
Identifies key categories related to stroke-related incidents in an EMS dataset, specifically focusing on cases where 911 was called for stroke, and a stroke scale was administered. .
Usage
stroke_01_population(
df = NULL,
patient_scene_table = NULL,
response_table = NULL,
situation_table = NULL,
vitals_table = NULL,
erecord_01_col,
eresponse_05_col,
esituation_11_col,
esituation_12_col,
evitals_23_col,
evitals_26_col,
evitals_29_col,
evitals_30_col
)
Arguments
df |
A data frame or tibble containing the dataset. Each row should represent a unique patient encounter. |
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 |
vitals_table |
A data.frame or tibble containing only the evitals fields
needed for this measure's calculations. Default is |
erecord_01_col |
The column containing unique record identifiers for each encounter. |
eresponse_05_col |
The column containing EMS response codes, which should include 911 response codes. |
esituation_11_col |
The column containing the primary impression codes or descriptions related to the situation. |
esituation_12_col |
The column containing secondary impression codes or descriptions related to the situation. |
evitals_23_col |
The column containing the Glasgow Coma Scale (GCS) score. |
evitals_26_col |
The column containing the AVPU (alert, verbal, pain, unresponsive) scale value. |
evitals_29_col |
The column containing the stroke scale score achieved during assessment. |
evitals_30_col |
The column containing stroke scale type descriptors (e.g., FAST, NIH, etc.). |
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("I60", 3), rep("I61", 2)),
esituation_12 = c(rep("I63", 2), rep("I64", 3)),
)
# vitals table
vitals_table <- tibble::tibble(
erecord_01 = c("R1", "R2", "R3", "R4", "R5"),
evitals_23 = c(16, 15, 14, 13, 12),
evitals_26 = c("Alert", "Painful", "Verbal", "Unresponsive", "Alert"),
evitals_29 = rep("positive", 5),
evitals_30 = rep("a pain scale", 5)
)
# test the success of the function
result <- stroke_01_population(patient_scene_table = patient_table,
response_table = response_table,
situation_table = situation_table,
vitals_table = vitals_table,
erecord_01_col = erecord_01,
eresponse_05_col = eresponse_05,
esituation_11_col = esituation_11,
esituation_12_col = esituation_12,
evitals_29_col = evitals_29,
evitals_23_col = evitals_23,
evitals_26_col = evitals_26,
evitals_30_col = evitals_30
)
# show the results of filtering at each step
result$filter_process