seqic_indicator_8 {traumar}R Documentation

SEQIC Indicator 8 - Survival by Risk Group

Description

[Experimental]

Calculates the proportion of patients who survived based on risk groups existing in the data among trauma patients transported to Level I–IV trauma centers.

Usage

seqic_indicator_8(
  data,
  level,
  included_levels = c("I", "II", "III", "IV"),
  unique_incident_id,
  mortality_indicator,
  risk_group,
  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.

mortality_indicator

A logical, character, or factor variable indicating whether the patient died at the trauma center. Accepts values like TRUE/FALSE or "Yes"/"No".

risk_group

A character or factor column indicating the patient's risk group (e.g., "High", "Moderate", "Low"). See risk definitions below.

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.

Details

Value

A named list with two tibbles:

overall: A tibble summarizing overall mortality among trauma patients, grouped by the variables specified in groups. Columns include:

risk_group: A tibble summarizing mortality stratified by risk group and any additional grouping variables. Columns include:

Note

This function calculates survival outcomes for patients transported to trauma centers, stratified by risk of mortality. Risk groups—low, moderate, and high— are defined by the Iowa System Evaluation and Quality Improvement Committee (SEQIC) as described below. Users may also apply alternative risk stratification methods if preferred.

Users must ensure appropriate column names are passed and data is pre-processed to include the necessary fields without missing critical identifiers or timestamps.

Author(s)

Nicolas Foss, Ed.D., MS

Examples

# Packages
library(dplyr)
library(traumar)

# Simulated dataset for SEQIC Indicator 8
test_data <- tibble::tibble(
  id = as.character(1:12),
  trauma_level = c("I", "II", "III", "IV", "V", "II", "I", "III", "IV", "II",
  "I", "III"),
  mortality = c(FALSE, "No", TRUE, "Yes", FALSE, TRUE, "No", FALSE, "Yes",
  FALSE, TRUE, "No"),
  risk = c("High", "High", "Moderate", "Moderate", "Low", "Low", "High",
  "Moderate", "Low", "Moderate", "High", "Low")
)

# Run indicator 8 function
traumar::seqic_indicator_8(
  data = test_data,
  level = trauma_level,
  unique_incident_id = id,
  mortality_indicator = mortality,
  risk_group = risk
)


[Package traumar version 1.2.1 Index]