safety_01: Safety-01 Calculation

In nemsqar: National Emergency Medical Service Quality Alliance Measure Calculations

Safety-01 Calculation

Description

The safety_01 function calculates the proportion of 911 responses where "lights and sirens" were not used in an EMS dataset. It generates age-based population summaries, calculating the count and proportion of "lights and sirens" responses among all incidents, and within adult and pediatric groups.

Usage

safety_01(
  df = NULL,
  patient_scene_table = NULL,
  response_table = NULL,
  erecord_01_col,
  incident_date_col = NULL,
  patient_DOB_col = NULL,
  epatient_15_col,
  epatient_16_col,
  eresponse_05_col,
  eresponse_24_col,
  confidence_interval = FALSE,
  method = c("wilson", "clopper-pearson"),
  conf.level = 0.95,
  correct = TRUE,
  ...
)

Arguments

df	A data frame or tibble containing EMS data.
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.
erecord_01_col	Column name containing the unique patient record 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 containing age.
epatient_16_col	Column for age units.
eresponse_05_col	Column containing response mode codes (e.g., 911 response codes).
eresponse_24_col	Column detailing additional response descriptors as text.
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(s)

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_24 = rep("No Lights or Sirens", 5)
  )

# Run the function
# Return 95% confidence intervals using the Wilson method
  safety_01(
    df = test_data,
    erecord_01_col = erecord_01,
    epatient_15_col = epatient_15,
    epatient_16_col = epatient_16,
    eresponse_05_col = eresponse_05,
    eresponse_24_col = eresponse_24,
    confidence_interval = TRUE
  )

nemsqar documentation built on Aug. 8, 2025, 6:15 p.m.