Patient-Facts: Multi-Site, Anomaly Detection, Cross-Sectional Analysis


Created

2024-06-05

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Domain

Category

Parameters

Publisher

PEDSnet

Abstract

This check assesses how much clinical data is available for patients. It provides a screen shot of anomalous proportion of patients and clinical data for multiple sites.

Data Requirements

cohort , study_name , patient_level_tbl , visit_types , omop_or_pcornet , multi_or_single_site , time , time_span , time_period , p_value , age_groups , anomaly_or_exploratory , domain_tbl , visit_type_table

Probe

Clinical Assessment

Access Package

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

Visualization Output

This check outputs a dot plot representing anomalous proportions of patients with a given fact type for the user selected visit type. The shape of the dot represents whether the point is anomalous, the color of the dot represents the proportion of patients for a given domain, and the size of the dot represents the mean proportion across all sites (MAD). Hovering over the graph provides metadata about each data points including domain, site, proportion, mean proportion, median proportion and MAD.

Raw Output

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

Column Data Type Definition
site character the name of the site being targeted
domain character string indicating the domain
visit_type character string indicating the visit type
tot_pt numeric the total number of patients in the cohort at the site
n_pt_fact numeric the number of patients at the site with the domain of interest
prop_pt_fact numeric the proportion of patients at the site with the domain of interest
mean_val numeric the mean proportion of patients for each group across sites
median_val numeric the median proportion of patients for each group across sites
sd_val numeric the standard deviation of the proportion of patients for each group across sites
mad_val numeric the median absolute deviation of the proportion of patients for each group across sites
cov_val numeric the coefficient of variance of the proportion of patients for each group across sites
max_val numeric the maximum proportion of patients for each group across sites
min_val numeric the minimum prorportion of patients for each group across sites
range_val numeric the range of the proportion of patients 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/patientfacts

Clinical Subjects Headings

Related Data Quality Result

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Patient Facts Study Results Part II: SSDQA Comparison
Created:2025-09Affiliation:PEDSnet Data Coordinating Center
The results of a Patient Facts check using the Mulit-Site, Anomaly Detection, Cross-Sectional parameters. This check investigates anomalous proportions of patients with facts in relevant domains based on the visit type of interest.
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Patient Facts Study Results Part II: SSDQA Comparison
Created:2025-09Affiliation:PEDSnet Data Coordinating Center
The results of a Patient Facts check using the Multi-Site, Exploratory, Cross-Sectional parameters. This check investigates fact density at inpatient, ED, hematologist, and all visits. There was a special emphasis on labs to identify density of important study variables.
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Patient Facts Study Results Part III: SSDQA Comparison
Created:2025-10Affiliation:PEDSnet Data Coordinating Center
The results of a Patient Facts check using the Multi-Site, Anomaly Detection, Cross-Sectional parameters. This check investigates anomalous proportions of patients with facts in key domains and focusing on key study variables, like ANC, MCV, & hemoglobin labs and hydroxyurea.
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Patient Facts Study Results III: PRESERVE
Created:2025-04-08Affiliation:PEDSnet Data Coordinating Center
The results of a Patient Facts check using the Multi-Site, Anomaly Detection, Cross-Sectional parameters. This check evaluates anomalous utilization at inpatient, ED, outpatient, and outpatient nephrology visits across the patient follow-up period at each institution.

Related Person

Related Code

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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

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). Patient-Facts: Multi-Site, Anomaly Detection, Cross-Sectional Analysis. [D Q Check]. PEDSpace Knowledge Bank. https://doi.org/10.24373/pdsp-418