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SEQIC Indicator 6 - Delayed Arrival Following Low GCS

Source: R/seqic_6.R
seqic_indicator_6.Rd

[Experimental]

Computes SEQIC Indicator 6 for trauma system quality monitoring. This indicator measures the proportion of patients presenting with a Glasgow Coma Scale (GCS) score < 9 who arrive at a trauma level I–IV center more than 180 minutes after injury. It excludes patients transferred out of the facility and focuses on those transferred into a facility.

Usage

seqic_indicator_6(
  data,
  level,
  included_levels = c("I", "II", "III", "IV"),
  unique_incident_id,
  transfer_out_indicator,
  receiving_indicator,
  low_GCS_indicator,
  time_from_injury_to_arrival,
  groups = NULL,
  calculate_ci = NULL,
  ...
)

Arguments

data

A data frame containing trauma incident records.

level

Column indicating the trauma center designation level (e.g., I, II, III, IV).

included_levels

Character vector indicating what facility levels to include in the analysis. Defaults to c("I", "II", "III", "IV").

unique_incident_id

Unique identifier for each record.

transfer_out_indicator

Column name indicating whether the patient was transferred out of the initial trauma center to definitive care. Logical, character, or factor type. Values representing "No" (e.g., FALSE, "No") indicate no transfer out.

receiving_indicator

Column name indicating whether the patient was transferred into the trauma center. Logical, character, or factor type. Values representing "Yes" (e.g., TRUE, "Yes") indicate transfer in.

low_GCS_indicator

Column name for identifying patients with a Glasgow Coma Scale score less than 9. Logical, character, or factor type.

time_from_injury_to_arrival

Column name representing the time in minutes from injury occurrence to arrival at the trauma center. Numeric type.

groups

Additional columns passed as a vector of strings to dplyr::summarize() via the .by argument for grouped summaries. Defaults to NULL.

calculate_ci

If NULL, 95% confidence intervals will not be calculated for the performance estimates. Otherwise, options of "wilson" or "clopper-pearson" can be supplied to utilize the corresponding methods to calculate the confidence intervals for the proportions. Defaults to NULL.

...

Arguments passed on to nemsqar::nemsqa_binomial_confint

conf.level

Numeric value between 0 and 1 indicating the confidence level. Defaults to 0.95 (95% confidence interval).

correct

Logical, indicating whether to apply continuity correction for Wilson intervals. Defaults to TRUE.

Value

A tibble summarizing SEQIC Indicator 6 results. Includes numerator, denominator, calculated proportion, and optionally 95% confidence intervals.

Details

This function:

  • Filters to trauma center records from facilities at trauma levels I–IV.

  • Deduplicates records using unique_incident_id.

  • Calculates:

    • Numerator: Patients with low GCS (< 9) who arrived more than 180 minutes after injury, were transferred in, and not transferred out.

    • Denominator: All patients with low GCS (< 9) who were transferred in and not transferred out.

  • Optionally calculates Wilson or Clopper-Pearson confidence intervals for the resulting proportion if calculate_ci is specified.

Note

Users must ensure input columns are appropriately coded and standardized. Transfer and GCS indicators should use consistent logical or textual representations.

Author

Nicolas Foss, Ed.D., MS

Examples

# Packages
library(dplyr)
library(traumar)

# Create test data for Indicator 6
test_data <- tibble::tibble(
  id = as.character(1:10),
  trauma_level = rep(c("I", "II", "III", "IV", "V"), times = 2),
  transfer_out = c("No", "No", "Yes", "No", "No", "No", "No", "No", "No",
  "No"),
  transfer_in = c("Yes", "Yes", "No", "Yes", "No", "Yes", "Yes", "Yes",
  "Yes", "Yes"),
  gcs_low = c(TRUE, TRUE, TRUE, FALSE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE),
  time_to_arrival = c(200, 100, 300, 190, 400, 181, 100, 179, 240, 178)
)

# Run the indicator function
traumar::seqic_indicator_6(
  data = test_data,
  level = trauma_level,
  unique_incident_id = id,
  transfer_out_indicator = transfer_out,
  receiving_indicator = transfer_in,
  low_GCS_indicator = gcs_low,
  time_from_injury_to_arrival = time_to_arrival
)
#> # A tibble: 1 × 4
#>   data              numerator_6 denominator_6 seqic_6
#>   <chr>                   <int>         <int>   <dbl>
#> 1 population/sample           3             6     0.5