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Trauma-04 Calculations

Source: R/trauma_04.R
trauma_04.Rd

This function processes EMS data to generate a set of binary variables indicating whether specific trauma triage criteria are met. The output is a data frame enriched with these indicators for further analysis. The final outcome is whether or not the EMS record documents the use of a verified trauma center levels 1-5 in the hospital capability documentation.

Usage

trauma_04(
  df = NULL,
  patient_scene_table = NULL,
  response_table = NULL,
  situation_table = NULL,
  vitals_table = NULL,
  exam_table = NULL,
  procedures_table = NULL,
  injury_table = NULL,
  disposition_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,
  eresponse_10_col,
  transport_disposition_col,
  edisposition_23_col = lifecycle::deprecated(),
  edisposition_02_col,
  trauma_center_facility_IDs,
  evitals_06_col,
  evitals_10_col,
  evitals_12_col,
  evitals_14_col,
  evitals_15_col,
  evitals_21_col,
  eexam_16_col,
  eexam_20_col,
  eexam_23_col,
  eexam_25_col,
  eprocedures_03_col,
  einjury_01_col,
  einjury_03_col,
  einjury_04_col,
  einjury_09_col,
  confidence_interval = FALSE,
  method = c("wilson", "clopper-pearson"),
  conf.level = 0.95,
  correct = TRUE,
  ...
)

Arguments

df

A dataframe or tibble contianing EMS data where each row represents an observation and columns represent features.

patient_scene_table

A data.frame or tibble containing at least ePatient, and eScene as a fact table.

response_table

A data.frame or tibble containing at least the eResponse fields needed for this measure's calculations.

situation_table

A data.frame or tibble containing at least the eSituation fields needed for this measure's calculations. Default is NULL.

vitals_table

A dataframe or tibble containing at least the eVitals fields needed.

exam_table

A data.frame or tibble containing only the eExam fields needed for this measure's calculations. Default is NULL.

procedures_table

A dataframe or tibble containing at least the eProcedures fields needed.

injury_table

A data frame or tibble containing fields from eInjury needed for this measure's calculations.

disposition_table

A data.frame or tibble containing only the edisposition fields needed for this measure's calculations.

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

Column representing the patient's numeric age agnostic of unit.

epatient_16_col

Column representing the patient's age unit ("Years", "Months", "Days", "Hours", or "Minutes").

esituation_02_col

Column indicating whether or not there was an injury.

eresponse_05_col

Column that contains eResponse.05 or the response type.

eresponse_10_col

Column name containing informatin about scene delays, if any, of the EMS unit associated with the EMS event.

transport_disposition_col

One or more unquoted column names (such as edisposition.12, edisposition.30) containing transport disposition for an EMS event identifying whether a transport occurred and by which unit.

edisposition_23_col

[Deprecated] Use edisposition_02_col instead. You must also pass a character vector of trauma center facility IDs to trauma_center_facility_IDs to ensure that destination facility IDs passed via edisposition_02_col are correctly identified as trauma centers as applicable.

edisposition_02_col

Column name containing the code of the destination the patient was delivered or transferred to.

trauma_center_facility_IDs

A character vector of trauma center facility IDs that will allow destination facilities documented in edisposition_02_col to be classified correctly as trauma centers when applicable.

evitals_06_col

Numeric column containing systolic blood pressure values.

evitals_10_col

Column name containing the patient's heart rate expressed as a number per minute.

evitals_12_col

Numeric column containing pulse oximetry values.

evitals_14_col

Column name containing the patient's respiratory rate expressed as a number per minute.

evitals_15_col

Column name containing the patient's respiratory effort.

evitals_21_col

Column name containing the patient's Glasgow Coma Score Motor response.

eexam_16_col

Column name containing the assessment findings associated with the patient's extremities.

eexam_20_col

Column name containing the assessment findings of the patient's neurological examination.

eexam_23_col

Column name containing the assessment findings associated with the patient's lungs.

eexam_25_col

Column name containing the assessment findings associated with the patient's chest.

eprocedures_03_col

Column containing procedure codes with or without procedure names.

einjury_01_col

Column name containing the category of the reported/suspected external cause of the injury.

einjury_03_col

Column describing Trauma triage criteria for the red boxes (Injury Patterns and Mental Status and Vital Signs) in the 2021 ACS National Guideline for the Field Triage of Injured Patients.

einjury_04_col

Column name containing Trauma triage criteria for the yellow boxes (Mechanism of Injury and EMS Judgment) in the current ACS National Guideline for the Field Triage of Injured Patients.

einjury_09_col

Column name containing the distance in feet the patient fell, measured from the lowest point of the patient to the ground.

confidence_interval

Logical. If TRUE, the function calculates a confidence interval for the proportion estimate.

method

Character. Specifies the method used to calculate confidence intervals. Options are "wilson" (Wilson score interval) and "clopper-pearson" (exact binomial interval). Partial matching is supported, so "w" and "c" can be used as shorthand.

conf.level

Numeric. The confidence level for the interval, expressed as a proportion (e.g., 0.95 for a 95% confidence interval). Defaults to 0.95.

correct

Logical. If TRUE, applies a continuity correction to the Wilson score interval when method = "wilson". Defaults to TRUE.

...

optional additional arguments to pass onto dplyr::summarize.

Value

A data.frame summarizing results for two population groups (All, Adults and Peds) with the following columns:

  • pop: Population type (All, Adults, and Peds).

  • numerator: Count of incidents meeting the measure.

  • denominator: Total count of included incidents.

  • prop: Proportion of incidents meeting the measure.

  • prop_label: Proportion formatted as a percentage with a specified number of decimal places.

  • lower_ci: Lower bound of the confidence interval for prop (if confidence_interval = TRUE).

  • upper_ci: Upper bound of the confidence interval for prop (if confidence_interval = TRUE).

Author

Nicolas Foss, Ed.D., MS

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),
    eresponse_10 = rep(2210011, 5),
    esituation_02 = rep("Yes", 5),
    evitals_06 = c(100, 90, 80, 70, 85),
    evitals_10 = c(110, 89, 88, 71, 85),
    evitals_12 = c(50, 60, 70, 80, 75),
    evitals_14 = c(30, 9, 8, 7, 31),
    evitals_15 = c("apneic", "labored", "rapid", "shallow", "weak/agonal"),
    evitals_21 = c(5, 4, 3, 2, 1),
    eexam_16 = c(3516043, 3516067, 3516043, 3516067, 3516067),
    eexam_20 = c(3520045, 3520043, 3520019, 3520017, 3520017),
    eexam_23 = c(3523011, 3523003, 3523001, 3523011, 3523003),
    eexam_25 = c(3525039, 3525023, 3525005, 3525039, 3525023),
    edisposition_02 = c(9908029, 9908027, 9908025, 9908023, 9876543),
    edisposition_30 = c(4230001, 4230003, 4230001, 4230007, 4230007),
    eprocedures_03 = c(424979004, 427753009, 429705000, 47545007, 243142003),
    einjury_01 = c("V20", "V36", "V86", "V39", "V32"),
    einjury_03 = c(2903011, 2903009, 2903005, 3903003, 2903001),
    einjury_04 = c(2904013, 2904011, 2904009, 2904007, 2904001),
    einjury_09 = c(11, 12, 13, 14, 15)
  )

  # Run function with the first and last pain score columns
  # Return 95% confidence intervals using the Wilson method
# test the success of the function
result <- trauma_04_population(
  df = test_data,
  erecord_01_col = erecord_01,
  incident_date_col = NULL,
  patient_DOB_col = NULL,
  epatient_15_col = epatient_15,
  epatient_16_col = epatient_16,
  eresponse_05_col = eresponse_05,
  eresponse_10_col = eresponse_10,
  esituation_02_col = esituation_02,
  evitals_06_col = evitals_06,
  evitals_10_col = evitals_10,
  evitals_12_col = evitals_12,
  evitals_14_col = evitals_14,
  evitals_15_col = evitals_15,
  evitals_21_col = evitals_21,
  eexam_16_col = eexam_16,
  eexam_20_col = eexam_20,
  eexam_23_col = eexam_23,
  eexam_25_col = eexam_25,
  edisposition_02_col = edisposition_02,
  trauma_center_facility_IDs = as.character(c(
    9908029,
    9908027,
    9908025,
    9908023,
    9908021
  )),
  transport_disposition_col = edisposition_30,
  eprocedures_03_col = eprocedures_03,
  einjury_01_col = einjury_01,
  einjury_03_col = einjury_03,
  einjury_04_col = einjury_04,
  einjury_09_col = einjury_09
)
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