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Analyzing health care quality measures

QualityMeasure is an R package to help with analyzing health care quality measures. The package includes functions for calculating measure performance, both unadjusted and adjusted, and estimating reliability with several different methods. More detail on each reliability estimation method can be found in Comparing methods for assessing the reliability of health care quality measures.

This package is a work-in-progress. Please email me at nieser@stanford.edu with any questions if you plan to use this code.

The following code can be used to download the latest version of the package to your RStudio from Github.

library(devtools)
devtools::install_github('knieser/quality_measure_reliability')
library(QualityMeasure)

Tutorial

This package contains a vignette describing how this package can be used to estimate reliability: Example analysis

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Version

Install

install.packages('QualityMeasure')

Monthly Downloads

150

Version

2.0.1

License

GPL (>= 3)

Maintainer

Kenneth Nieser

Last Published

October 16th, 2025

Functions in QualityMeasure (2.0.1)

tutorial_profiling_results

Risk-adjusted profiling results for example data set used in tutorial
psychreadmission

Psychiatric 30-day, unplanned readmission data
tutorial_BB_results

Beta-Binomial reliability results for example data set used in tutorial
plotSSR

Example plot of values used to calcualte split-sample reliability.
plotReliability

Plot distributions of reliability estimates across entities
misclassification_analysis

Calculate misclassification probabilities (in progress)
tutorial_reliability_results_1

Reliability results for example data set used in tutorial
example_df_2

Example data set with a covariate used in tutorial
simulateData

Simulate data
controlRel

Parameters for reliability calculations
example_df_1

Example data set used in tutorial
calcResamplingIUR

Calculate reliability using resampling inter-unit reliability method
calcAOV

Calculate reliability using one-way ANOVA method
calcBetaBin

Calculate reliability using a Beta-Binomial model
calcHLMRel

Calculate reliability using a hierarchical linear regression model
calcHLGMRel

Calculate reliability using a hierarchical logistic regression model
plotEstimates

Plot estimates from regression model used for risk-adjustment
plotN

Plot sample size distribution across accountable entities
tutorial_BB_agg_results

Beta-Binomial reliability results for example aggregated data set used in tutorial
calcSSR

Calculate reliability using split-sample method
controlPerf

Parameters for performance calculations
model_performance

Calculate model performance
plotCalibration

Plot calibration curve for risk-adjustment model
calcPerformance

Calculate measure performance by accountable entity
colonoscopy

Colonoscopy follow-up data
plotPerformance

Plot measure performance across accountable entities
calcReliability

Calculate reliability of quality measure performance
plotPredictedDistribution

Plot densities of predicted values by outcome group
tutorial_reliability_results_2

Reliability results for example data set with risk adjustment used in tutorial