Duplicate Records: Multi Site, Anomaly Detection, Cross-Sectional Analysis


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Domain

Category

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Publisher

PEDSnet

Abstract

This check provides raw data and visualizations to aid a user in evaluating whether duplicate records are present in a dataset of interest. It summarizes the proportion of duplicate rows & patients with duplicate rows, as well as the median number of duplicate rows per patient.

Probe

Clinical Assessment

Access Package

# install.packages("devtools") devtools::install_github('ssdqa/duplicaterecords')

Visualization Output

This check outputs a dot plot representing anomalous proportions of patients or rows with duplicate values for a given duplicate definition per site. This graph summarizes the mean value for the duplicate definition by the dot size, the proportion of duplicate values by the dot color, and whether that definition is anomalous by replacing the dot with a star. A tooltip provides metadata for the definition and the site and precise values for proportion, mean proportion, median proportion, standard deviation and MAD upon hover.

Raw Output

This check produces a raw data output containing 14 columns:

Column Data Type Definition
site character the name of the site being targeted
duplicate_definition character an alias to describe the definition of duplication being investigated
duplicate_columns character the name(s) of the column(s) included or excluded to define duplication
total_rows numeric the total number of rows in the domain
total_pt numeric the total number of patients in the domain
duplicate_rows numeric the number of duplicate rows
duplicate_pt numeric the number of patients with at least one duplicate row
duplicate_row_prop numeric the proportion of duplicate rows
duplicate_pt_prop numeric the proportion of patients with at least one duplicate row
median_all_with0s numeric the median number of duplicate rows per patient, for all patients, across all sites
median_all_without0s numeric the median number of duplicate rows per patient, for only patients with evidence of duplication, across all sites
median_site_with0s numeric the median number of duplicate rows per patient, for all patients, across a specific site
median_site_without0s numeric the median number of duplicate rows per patient, for only patients with evidence of duplication, for a specific site
mean_val numeric the mean proportion of patients or rows (based on user selection) for each group across sites
median_val numeric the median proportion of patients or rows (based on user selection) for each group across sites
sd_val numeric the standard deviation of the proportion of patients or rows (based on user selection) for each group across sites
mad_val numeric the median absolute deviation of the proportion of patients or rows (based on user selection) for each group across sites
cov_val numeric the coefficient of variance of the proportion of patients or rows (based on user selection) for each group across sites
max_val numeric the maximum proportion of patients or rows (based on user selection) for each group across sites
min_val numeric the minimum prorportion of patients or rows (based on user selection) for each group across sites
range_val numeric the range of the proportion of patients or rows (based on user selection) for each group across sites
total_ct numeric the total number of group members
analysis_eligible character a string indicating whether the group is eligible for anomaly detection analysis
lower_tail numeric the lower bound used to identify low anomalies
upper_tail numeric the upper bound used to identify high anomalies
anomaly_yn character a string indicating whether the value is anomalous or not
output_function character a string indicating the type of visualization that should be generated by dr_output

Funder(s)

This research was made possible through the generous support of Patient-Centered Outcomes Research Institute. The statements presented in this work are solely the responsibility of the author(s) and do not necessarily represent the views of PCORI, its Board of Governors, or its Methodology Committee.

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Study-Specific Quality, Utility, and Breadth Assessment
Created:2025-11Affiliation:PEDSnet Data Coordinating Center
This suite of R packages allows one to investigate multiple facets of data quality and customize analyses based on your study-specific needs. Each module allows up to 8 different analyses in either the OMOP or PCORnet CDM, all aimed at taking a different view of the data while still addressing the same data quality probe.

##### [View pkgdown summary here.](https://ssdqa.github.io/squba/)

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Creative Commons license

Except where otherwised noted, this item's license is described as a CC-BY Attribution 4.0 License.

Cite this Data Quality Check

Wieand, K. & Razzaghi, H. (2026, March). Duplicate Records: Multi Site, Anomaly Detection, Cross-Sectional Analysis. [D Q Check]. PEDSpace Knowledge Bank. https://doi.org/10.24373/pdsp-713