The stroke_01 function processes EMS dataset to identify potential stroke
cases based on specific criteria and calculates the stroke scale measures. It
filters the data for 911 response calls, identifies stroke-related
impressions and scales, and aggregates results by unique patient encounters.
Usage
stroke_01(
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
NULL.- response_table
A data frame or tibble containing only the eresponse fields needed for this measure's calculations. Default is
NULL.- situation_table
A data.frame or tibble containing only the esituation fields needed for this measure's calculations. Default is
NULL.- vitals_table
A data.frame or tibble containing only the evitals fields needed for this measure's calculations. Default is
NULL.- 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.).
- ...
Additional arguments passed to
dplyr::summarize()function for further customization of results.
Value
A tibble summarizing results for the total population with the following columns:
measure: The name of the measure being calculated.
pop: Population type (All).
numerator: Count of incidents where beta-agonist medications were
administered.
denominator:
Total count of incidents.
prop: Proportion of incidents involving beta-agonist medications.
prop_label: Proportion formatted as a percentage with a specified number
of decimal places.
Examples
# Synthetic test data
test_data <- tibble::tibble(
erecord_01 = c("R1", "R2", "R3", "R4", "R5"),
epatient_15 = c(34, 5, 45, 2, 60), # Ages
epatient_16 = c("Years", "Years", "Years", "Months", "Years"),
eresponse_05 = rep(2205001, 5),
esituation_11 = c(rep("I60", 3), rep("I61", 2)),
esituation_12 = c(rep("I63", 2), rep("I64", 3)),
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)
)
# Run the function
stroke_01(
df = test_data,
erecord_01_col = erecord_01,
eresponse_05_col = eresponse_05,
esituation_11_col = esituation_11,
esituation_12_col = esituation_12,
evitals_23_col = evitals_23,
evitals_26_col = evitals_26,
evitals_29_col = evitals_29,
evitals_30_col = evitals_30
)
#>
#> ── Stroke-01 ───────────────────────────────────────────────────────────────────
#>
#> ── Gathering Records for Stroke-01 ──
#>
#> Running `stroke_01_population()` [Working on 1 of 11 tasks] ●●●●──────────────…
#> Running `stroke_01_population()` [Working on 2 of 11 tasks] ●●●●●●────────────…
#> Running `stroke_01_population()` [Working on 3 of 11 tasks] ●●●●●●●●●─────────…
#> Running `stroke_01_population()` [Working on 4 of 11 tasks] ●●●●●●●●●●●●──────…
#> Running `stroke_01_population()` [Working on 5 of 11 tasks] ●●●●●●●●●●●●●●●───…
#> Running `stroke_01_population()` [Working on 6 of 11 tasks] ●●●●●●●●●●●●●●●●●─…
#> Running `stroke_01_population()` [Working on 7 of 11 tasks] ●●●●●●●●●●●●●●●●●●…
#> Running `stroke_01_population()` [Working on 8 of 11 tasks] ●●●●●●●●●●●●●●●●●●…
#> Running `stroke_01_population()` [Working on 9 of 11 tasks] ●●●●●●●●●●●●●●●●●●…
#> Running `stroke_01_population()` [Working on 10 of 11 tasks] ●●●●●●●●●●●●●●●●●…
#> Running `stroke_01_population()` [Working on 11 of 11 tasks] ●●●●●●●●●●●●●●●●●…
#>
#>
#>
#> ── Calculating Stroke-01 ──
#>
#>
#> ✔ Function completed in 0.16s.
#>
#> # A tibble: 1 × 6
#> measure pop numerator denominator prop prop_label
#> <chr> <chr> <int> <int> <dbl> <chr>
#> 1 Stroke-01 All 5 5 1 100%