respiratory_01: Respiratory-01 Calculation

In nemsqar: National Emergency Medical Service Quality Alliance Measure Calculations

Respiratory-01 Calculation

Description

The respiratory_01 function filters and analyzes data related to emergency 911 respiratory distress incidents, providing summary statistics for adult and pediatric populations. This function uses specific data columns for 911 response codes, primary and secondary impressions, and vital signs to calculate the proportion of cases with complete vital signs recorded, stratified by age.

Usage

respiratory_01(
  df = NULL,
  patient_scene_table = NULL,
  response_table = NULL,
  situation_table = NULL,
  vitals_table = NULL,
  erecord_01_col,
  incident_date_col = NULL,
  patient_DOB_col = NULL,
  epatient_15_col,
  epatient_16_col,
  eresponse_05_col,
  esituation_11_col,
  esituation_12_col,
  evitals_12_col,
  evitals_14_col,
  confidence_interval = FALSE,
  method = c("wilson", "clopper-pearson"),
  conf.level = 0.95,
  correct = TRUE,
  ...
)

Arguments

df	A data frame containing incident data with each row representing an observation.
patient_scene_table	A data.frame or tibble containing at least epatient and escene fields 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.
vitals_table	A data.frame or tibble containing at least the evitals fields needed for this measure's calculations.
erecord_01_col	Unique Patient ID
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 giving the calculated age value.
epatient_16_col	Column giving the provided age unit value.
eresponse_05_col	Column name for 911 response codes (e.g., 2205001, 2205003, 2205009).
esituation_11_col	Column name for primary impression codes related to respiratory distress.
esituation_12_col	Column name for secondary impression codes related to respiratory distress.
evitals_12_col	Column name for the first vital sign measurement.
evitals_14_col	Column name for the second vital sign measurement.
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),
  esituation_11 = c(rep("J80", 3), rep("I50.9", 2)),
  esituation_12 = c(rep("J80", 2), rep("I50.9", 3)),
  evitals_12 = c(60, 59, 58, 57, 56),
  evitals_14 = c(16, 15, 14, 13, 12)
)

# Run the function
# Return 95% confidence intervals using the Wilson method
respiratory_01(
  df = test_data,
  erecord_01_col = erecord_01,
  epatient_15_col = epatient_15,
  epatient_16_col = epatient_16,
  eresponse_05_col = eresponse_05,
  esituation_11_col = esituation_11,
  esituation_12_col = esituation_12,
  evitals_12_col = evitals_12,
  evitals_14_col = evitals_14,
  confidence_interval = TRUE
)

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