Quantitative Variable Distributions: Single Site, Anomaly Detection, Longitudinal Analysis

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PEDSnet

Abstract

This check provides raw data and visualizations to aid a user in evaluating whether the distribution of quantitative variables aligns with clinical expectations. It can summarize the distribution of a quantitative variable (like lab result values) or patient counts (like number of patients with an outpatient visit).


How to Access This Check

  1. You may access the module’s R package in GitHub.
    Or, run in R
install_github('ssdqa/https://github.com/ssdqa/quantvariabledistribution')
  1. Using the provided vignettes on GitHub or help in R, follow parameter input instructions for “Single Site”, “Anomaly Detection”, “Longitudinal” requirements.

Check Output

Visualization Output

This check outputs a line graph visualizing the proportion of values that are considered outliers (based on the number of standard devations they fall from the mean) across the time span. The outliers are stratified by upper and lower outlier types so the user can differentiate between outliers above and below the mean at each time point.

Raw Output

This check produces a raw data output containing 10 columns:

Column Data Type Definition
site character the name of the site being targeted OR “combined” if multiple sites were provided
value_type character the type of value being measured
outlier_type character a string indicating whether the outlier is in the upper (positive) or lower (negative) direction
total_vals numeric the total number of values
sd_threshold numeric the number of standard deviations a value should fall in either direction of the mean to be considered an outlier
time_start date the start of the time period being examined
time_increment character the length of each time period
n_outlier numeric the number of outlying values
prop_outlier numeric the proportion of outlying values
output_function character a string indicating the type of visualization that should be generated by qvd_output

Funder(s)

This research was made possible through the generous support of the Patient-Centered Outcomes Research Institute .

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