Expected Variables Present: Multi-Site, Anomaly Detection, Cross-Sectional Analysis


Created

2024-06-05

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Domain

Category

Parameters

Publisher

PEDSnet

Abstract

This check provides raw data and visualizations to aid a user in evaluating whether expected concepts are present in a dataset of interest. It summarizes the proportion of patients with co-occurring variables. This check promotes the identification of anomalous data to compare among sites.

Data Requirements

cohort , omop_or_pcornet , evp_variable_file , multi_or_single_site , anomaly_or_exploratory , output_level , age_groups , p_value , time , time_span , time_period

Probe

Clinical Assessment

Access Package

# install.packages("devtools") devtools::install_github('ssdqa/https://github.com/ssdqa/conceptsetdistribution')

Visualization Output

This check outputs a dot plot representing anomalous proportions of patients (or rows) with a given variable per site. This graph summarizes the mean absolute deviation (MAD) value for the concept_id by the dot size, how often that concept_id is used proportionally by the dot color, and whether that concept_id is anomalous by replacing the dot with a star. A tooltip provides metadat for the mapped concet and the site and precise values for proportion, mean proportion, median proportion, standard deviation and MAD upon hover.

Raw Output

The raw data output of this check produces twenty_one columns of data:

Column Data Type Definition
site character the name of the site being targeted
total_pt_ct numeric the total number of patients from the cohort in the domain table
total_row_ct numeric the total number of rows associated with patients from the cohort in the domain table
variable_pt_ct numeric the number of patients with evidence of the variable
variable_row_ct numeric the number of rows with evidence of the variable
prop_pt_variable numeric the proportion of patients with evidence of the variable
prop_row_variable numeric the proportion of rows with evidence of the variable
variable character the name of the variable
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

Affiliation(s)

PEDSnet Data Coordinating Center

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.

Provenance

Description

Development Code

https://github.com/ssdqa/expectedvariablespresent

Clinical Subjects Headings

Related Data Quality Result

Thumbnail Image
Expected Variables Present Study Results II: PRESERVE
Created:2025-04-08Affiliation:PEDSnet Data Coordinating Center
The results of an Expected Variables Present check using the Multi-Site, Anomaly Detection, Cross-Sectional parameters. This check assesses anomalous proportions of patients with several study variables, like ABPM and census tract information.

Related Person

Related Code

Thumbnail Image
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/)

Related Data Quality Check

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Creative Commons license

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

Cite this Data Quality Check

PEDSnet Data Coordinating Center. (2024, June). Expected Variables Present: Multi-Site, Anomaly Detection, Cross-Sectional Analysis. [D Q Check]. PEDSpace Knowledge Bank. https://doi.org/10.24373/pdsp-461