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Summarize Measure

Source: R/summarize_measure.R
summarize_measure.Rd

Calculates measure numerator, denominator, proportions, and optional confidence intervals for a NEMSQA measure. This function summarizes the information for a specified population and measure, returning a tibble with the calculated values. If requested, the function can also calculate confidence intervals for the proportions using either the Wilson score interval or the Clopper-Pearson exact binomial interval.

Usage

summarize_measure(
  data,
  measure_name,
  population_name,
  numerator_col,
  confidence_interval = FALSE,
  method = c("wilson", "clopper-pearson"),
  conf.level = 0.95,
  correct = TRUE,
  ...
)

Arguments

data

A dataframe or tibble containing the filtered and calculated fields for the population of interest.

measure_name

A string containing the description of the measure being calculated (e.g., "Airway-01").

population_name

A string containing the description of the population for which the measure is being calculated (e.g., "Adults", "Peds", or "All").

numerator_col

The tidyselect column containing the numerator data for the measure (e.g., the number of cases).

confidence_interval

[Experimental] A logical value indicating whether to calculate a confidence interval for the proportion estimate. Defaults to FALSE.

method

[Experimental] A string specifying the method to calculate the confidence intervals. Options are "wilson" (Wilson score interval) or "clopper-pearson" (exact binomial interval). Partial matching is allowed (e.g., "w" or "c"). Default is "wilson".

conf.level

[Experimental] A numeric value indicating the confidence level for the interval, expressed as a proportion (e.g., 0.95 for a 95% confidence interval). Defaults to 0.95.

correct

[Experimental] A logical value specifying whether to apply continuity correction to the Wilson score interval when method = "wilson". Default is TRUE.

...

(optional) Additional arguments passed to nemsqa_binomial_confint when calculating confidence intervals.

Value

A summarized data frame containing:

  • measure: The measure name.

  • pop: The population group.

  • numerator: The count of qualifying events.

  • denominator: The total count of records.

  • prop: The proportion of qualifying events.

  • prop_label: A formatted percentage representation of prop (when confidence_interval = FALSE).

  • lower_ci, upper_ci: The lower and upper confidence interval bounds (when confidence_interval = TRUE).

Author

Samuel Kordik, BBA, BS