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Tabulate Measure Results

Source: R/results_summarize.R
results_summarize.Rd

Calculates measure numerator, denominator, and proportions for a NEMSQA measure and each population (total, adult, and pediatric). The function returns a summarized result table for the selected populations, with optional confidence intervals for the proportions.

This function is used throughout the package to calculate measure results for different populations (e.g., total population, adults, and pediatric groups) based on the given input data. Each of the population arguments (total_population, adult_population, peds_population) defaults to NULL. If a population argument is NULL, it will be excluded from the results.

Usage

results_summarize(
  total_population = NULL,
  adult_population = NULL,
  peds_population = NULL,
  measure_name,
  population_names = c("all", "adults", "peds"),
  numerator_col,
  confidence_interval = FALSE,
  method = c("wilson", "clopper-pearson"),
  conf.level = 0.95,
  correct = TRUE,
  ...
)

Arguments

total_population

A dataframe or tibble containing the filtered and calculated fields for the total population. Defaults to NULL.

adult_population

A dataframe or tibble containing the filtered and calculated fields for the adult population. Defaults to NULL.

peds_population

A dataframe or tibble containing the filtered and calculated fields for the pediatric population. Defaults to NULL.

measure_name

A string containing the description of the measure being calculated.

population_names

A vector of strings specifying which populations (total, adult, peds) to include in the result. Default includes all populations.

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 include confidence intervals in the result. Defaults to FALSE.

method

[Experimental] A string specifying the method to calculate confidence intervals. Options are "wilson" or "clopper-pearson". Default is "wilson".

conf.level

[Experimental] A numeric value indicating the confidence level for the confidence intervals. Default is 0.95 (95% confidence).

correct

[Experimental] A logical value specifying whether to apply continuity correction when calculating confidence intervals. Default is TRUE.

...

(optional) Additional arguments passed to the summarize_measure function used for calculating measure results.

Value

A tibble containing the summarized measure results for the selected populations. The output includes:

  • measure: The measure name.

  • pop: The population group (e.g., "All", "Adults", "Peds").

  • numerator: The count of qualifying events.

  • denominator: The total number of records in the population.

  • prop: The proportion of qualifying events.

  • prop_label: A formatted percentage representation of prop.

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

If multiple populations are specified, their results are combined into a single tibble using dplyr::bind_rows().

Author

Samuel Kordik, BBA, BS