nemsqar (version 1.1.0)

trauma_01_population: Trauma-01 Population

Description

Filters data down to the target populations for Trauma-08, and categorizes records to identify needed information for the calculations.

Identifies key categories to records that are 911 requests for patients with injury who were assessed for pain based on specific criteria and calculates related ECG measures. This function segments the data by age into adult and pediatric populations.

Usage

trauma_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,
  esituation_02_col,
  eresponse_05_col,
  evitals_23_col,
  evitals_26_col,
  evitals_27_col,
  edisposition_28_col,
  transport_disposition_col
)

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

Arguments

df

A data frame or tibble containing EMS records. 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

Column name representing the EMS record ID.

incident_date_col

Column name for the incident date. Default is NULL.

patient_DOB_col

Column name for the patient's date of birth. Default is NULL.

epatient_15_col

Column name for the patient's age in numeric format.

epatient_16_col

Column name for the unit of age (e.g., "Years", "Months").

esituation_02_col

Column name indicating if the situation involved an injury.

eresponse_05_col

Column name for the type of EMS response (e.g., 911 call).

evitals_23_col

Column name for the Glasgow Coma Scale (GCS) total score.

evitals_26_col

Column name for AVPU (Alert, Voice, Pain, Unresponsive) status.

evitals_27_col

Column name for the pain scale assessment.

edisposition_28_col

Column name for patient care disposition details.

transport_disposition_col

Column name for transport disposition details.

Author

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_02 = rep("Yes", 5),
  )

  # vitals table
  vitals_table <- tibble::tibble(

    erecord_01 = c("R1", "R2", "R3", "R4", "R5"),
    evitals_23 = rep(15, 5),
    evitals_26 = rep("Alert", 5),
    evitals_27 = c(0, 2, 4, 6, 8)
  )

  # disposition table
  disposition_table <- tibble::tibble(
    erecord_01 = c("R1", "R2", "R3", "R4", "R5"),
    edisposition_28 = rep(4228001, 5),
    edisposition_30 = c(4230001, 4230003, 4230001, 4230007, 4230007)
  )

  # test the success of the function
  result <- trauma_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,
                     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,
                     esituation_02_col = esituation_02,
                     evitals_23_col = evitals_23,
                     evitals_26_col = evitals_26,
                     evitals_27_col = evitals_27,
                     edisposition_28_col = edisposition_28,
                     transport_disposition_col = edisposition_30
                     )

# show the results of filtering at each step
result$filter_process