1. Risk-Based Monitoring (RBM) and Data Quality Analysis (CSM) of Clinical Trials using

2. JReview Developed from day 1 as a Clinical Research application
Understands ‘patient’, ‘baseline’, ‘endpoint’, etc.
Integrated with many clinical data sources
Dynamic multi-study pooling
Built-in ‘patient identification/drill down’
Patient review tracking
Many clinical data specific graphics, tabulations, profiles, risk assessments, etc. including defining critical data
Built in codelist/sas format awareness
SAS/R program integration
Patient Narratives
Works with CDISC as well as Legacy Data formats
Risk-Based Monitoring & Data Quality Analysis (CSM)

3. Special Graph Types for Clinical Data
Multiple scientific, clinically relevant graph types for clinical data visualization – with patient identification built in
Baseline/Endpoint plot
Shift Plot
Benefit-Risk Plot
Napoleon’s March Plot
Hy’s Law Plot, Composite Hy’s Law
Time-to-Event Plot
Forest Plot
Dot Plot
Box Plot
Tree Map Sunburst Plot
Trellis Plot …

4. Patient Profiles
Time-oriented (days on drug) graph display of user selected parameters
Dynamically choose categories and items to include
Drilldown to selected data of interest
Graphical or tabular (formatted) output
Export to Excel, HTML, PDF
Optional batch report option

5. JReview – Data Anomaly Detection
Companies have been using JReview for data anomaly detection for many years – using clinical data visualizations, exception reporting, etc.
Since we already had access to the clinical data for studies – we thought it would be good to add specific RBM definition and visualization capabilities to JReview 10 (2014)
Later – realizing that the RBM capabilities address data issues we thought of (supervised), we researched and developed an additional ‘unsupervised’ data quality analysis in JReview 13.1 (2018)

6. JReview 10 Out of the box Analytics support for Risk Based Monitoring
Centralized monitoring teams can define key risk categories and indicators from all clinical & operational source data available, set thresholds, and specify suggested actions
The JReview RBM Data Browser allows for the design of aggregated risk-based monitoring reports which can be scheduled in regular intervals to push monitoring activity plans out to site monitors/CRAs
Periodic ‘risk factor’ batch execution
Visualization of risk evolution by site/country/region based on multiple risk indicators & -categories

7. RBM Risk Indicator Definition
Key Risk Indicators, thresholds, & suggested actions Definition within JReview with test run  scheduled periodic execution

8. RBM Data Browser
Risk Indicator Result Visualization by site, country, or region - subset by attributes - interactively sort any columns for site ranking

9. Site Distribution Over Time
Site Distribution (Box Whiskers) over time – for selected site & RBM rule results table

10. RBM Treemap
Site – Risk Indicator weight visualization – Tree Map visualization

11. JReview 13.1
Data Quality Analysis – ‘Unsupervised Analysis’ Automated data quality analysis Wide variety of analyses in background Review results interactively High level combined results (global score) > detail results

12. Global Scores – Tree Map

13. Data Quality Checks – Categories & Weight

14. Other Info – Geographic Region, SAE, Discontinuation, etc.

15. Tables & Items to be included in Analyses

16. Duplicate Patient Identification Information

17. Overview of checks Methods where p-value is part of the result
digit preference
correlation check
variance distribution check
categorical variable check
p value combination
Methods that raise flags as results
duplicates check
inliers
integer check
outliers
SAE check
missing value check
baseline check