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Trauma-03 Calculation

Source: R/trauma_03.R
trauma_03.Rd

This function calculates the "Trauma-03" measure, which evaluates pain scale reassessment for trauma patients, using a comprehensive data frame with EMS records. The function processes input data to create both fact and dimension tables, identifies eligible patients, and summarizes results for adult and pediatric populations.

Usage

trauma_03(
  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,
  esituation_02_col,
  eresponse_05_col,
  edisposition_28_col,
  transport_disposition_col,
  evitals_01_col,
  evitals_27_col = NULL,
  evitals_27_initial_col = NULL,
  evitals_27_last_col = NULL,
  ...
)

Arguments

df

A data frame or tibble containing EMS data with all relevant columns. Default is NULL.

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.

disposition_table

A data frame or tibble containing only the edisposition 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 representing the EMS record unique identifier.

incident_date_col

Column that contains the incident date. This defaults to NULL as it is optional in case not available due to PII restrictions.

patient_DOB_col

Column that contains the patient's date of birth. This defaults to NULL as it is optional in case not available due to PII restrictions.

epatient_15_col

The column for patient age numeric value.

epatient_16_col

The column for patient age unit (e.g., "Years", "Months").

esituation_02_col

The column containing information on the presence of injury.

eresponse_05_col

The column representing the 911 response type.

edisposition_28_col

The column for patient care disposition details.

transport_disposition_col

The column for patient transport disposition.

evitals_01_col

The column for the time of pain scale measurement.

evitals_27_col

The column for the full set of pain scale scores.

evitals_27_initial_col

The column for the initial pain scale score.

evitals_27_last_col

The column for the last pain scale score.

...

Additional arguments passed to helper functions for further customization.

Value

A tibble summarizing results for three population groups (All, Adults, and Peds) with the following columns:

measure: The name of the measure being calculated. pop: Population type (All, Adults, Peds). numerator: Count of incidents where there was a reduction in patient pain. denominator: Total count of incidents. prop: Proportion of incidents where there was a reduction in patient pain. prop_label: Proportion formatted as a percentage with a specified number of decimal places.

Author

Nicolas Foss, Ed.D., MS

Examples

# Synthetic test data
# for testing a single pain scale column
  test_data2 <- 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_02 = rep("Yes", 5),
    evitals_01 = lubridate::as_datetime(c("2025-01-01 12:00:00", "2025-01-05
    18:00:00", "2025-02-01 06:00:00", "2025-01-01 01:00:00", "2025-06-01
    14:00:00")),
    edisposition_28 = rep(4228001, 5),
    edisposition_30 = c(4230001, 4230003, 4230001, 4230007, 4230007)
  )

  # Expand data so each erecord_01 has 2 rows (one for each pain score)
  test_data_expanded2 <- test_data2 |>
    tidyr::uncount(weights = 2) |>  # Duplicate each row twice
    # Assign pain scores
    dplyr::mutate(evitals_27 = c(0, 0, 2, 1, 4, 3, 6, 5, 8, 7)) |>
    dplyr::group_by(erecord_01) |>
    dplyr::mutate(
    # Lower score = later time
      time_offset = dplyr::if_else(dplyr::row_number() == 1, -5, 0),
      evitals_01 = evitals_01 + lubridate::dminutes(time_offset)
    ) |>
    dplyr::ungroup() |>
    dplyr::select(-time_offset)  # Remove temporary column

# Run function with the single pain score column
  trauma_03(
    df = test_data_expanded2,
    erecord_01_col = erecord_01,
    epatient_15_col = epatient_15,
    epatient_16_col = epatient_16,
    eresponse_05_col = eresponse_05,
    esituation_02_col = esituation_02,
    evitals_01_col = evitals_01,
    evitals_27_initial_col = NULL,
    evitals_27_last_col = NULL,
    evitals_27_col = evitals_27,
    edisposition_28_col = edisposition_28,
    transport_disposition_col = edisposition_30
  )
#> 
#> ── Trauma-03 ───────────────────────────────────────────────────────────────────
#> 
#> ── Gathering Records for Trauma-03 ──
#> 
#> Running `trauma_03_population()`  [Working on 1 of 17 tasks] ●●●───────────────…
#> Running `trauma_03_population()`  [Working on 2 of 17 tasks] ●●●●●─────────────…
#> Running `trauma_03_population()`  [Working on 3 of 17 tasks] ●●●●●●────────────…
#> Running `trauma_03_population()`  [Working on 4 of 17 tasks] ●●●●●●●●──────────…
#> Running `trauma_03_population()`  [Working on 5 of 17 tasks] ●●●●●●●●●●────────…
#> Running `trauma_03_population()`  [Working on 6 of 17 tasks] ●●●●●●●●●●●●──────…
#> Running `trauma_03_population()`  [Working on 7 of 17 tasks] ●●●●●●●●●●●●●─────…
#> Running `trauma_03_population()`  [Working on 8 of 17 tasks] ●●●●●●●●●●●●●●●───…
#> Running `trauma_03_population()`  [Working on 9 of 17 tasks] ●●●●●●●●●●●●●●●●●─…
#> Running `trauma_03_population()`  [Working on 10 of 17 tasks] ●●●●●●●●●●●●●●●●●…
#> Running `trauma_03_population()`  [Working on 11 of 17 tasks] ●●●●●●●●●●●●●●●●●…
#> Running `trauma_03_population()`  [Working on 12 of 17 tasks] ●●●●●●●●●●●●●●●●●…
#> Running `trauma_03_population()`  [Working on 13 of 17 tasks] ●●●●●●●●●●●●●●●●●…
#> Running `trauma_03_population()`  [Working on 17 of 17 tasks] ●●●●●●●●●●●●●●●●●…
#> 
#> 
#> 
#> ── Calculating Trauma-03 ──
#> 
#> 
#> ✔ Function completed in 0.19s.
#> 
#> # A tibble: 3 × 6
#>   measure   pop    numerator denominator  prop prop_label
#>   <chr>     <chr>      <int>       <int> <dbl> <chr>     
#> 1 Trauma-03 Adults         2           2     1 100%      
#> 2 Trauma-03 Peds           1           1     1 100%      
#> 3 Trauma-03 All            4           4     1 100%