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New features in JMP Clinical 18.1.2 and JMP Clinical 18.2

On top of the current data quality reports, five additional reports have been added. While these five reports existed in JMP Clinical 8.1, they have been completely rewritten for JMP Clinical 18.1.2.

 

Weekdays and Holidays is looking for abnormal visits happening on weekends or during holidays, which may indicate clinical fraud. In JMP Clinical 8.1, this report focused mostly on worldwide and U.S. holidays. To allow for other possibilities, we implemented a way for customers to add holidays that would apply locally. However, it involved excessive manual effort. To overcome this burden, the python holidays package has been integrated into the system, allowing customers to create a reference data set of holidays that is country-specific. This data set can be updated over time as needed.

This graph shows an example:

 

Picture Weekdays and Holidays.png

 

The output is a volcano plot with an FDR threshold of approximately 2.9. Each site is tested for findings or study visits at either weekends or holidays and is represented with a dot. Each dot above the threshold is considered as significant, meaning there is a significance difference for this particular site compared to all other sites. A bar chart appears when hovering over a dot. We can see for the dot above the threshold that no findings visits happened on that particular holiday compared to all the other sites.

 

Correlated Findings looks for correlated elevation or decrease of findings tendencies. It compares the relationships of variables by domain of each site to all other sites to assess unusual data patterns to detect and correct quality issues, as shown in the graph below:

 

Correlated findings 1.png

The output is a volcano plot with an FDR threshold of approximately 2.6. Each site is tested for correlated findings and is represented with a dot. Each dot above the threshold is considered as significant, meaning there is a significance difference for this particular site compared to all other sites. A heat map appears when hovering over a dot, as shown here:

 

Correlated findings 2.png

It appears that more findings are correlated between pairs of findings from Site 28 compared to all the other sites. If we look at Site 28 for correlated findings between Alanine Aminotransferase and Aspartate Aminotransferase in each patient more closely, we see a lot of correlated trends (see graph below).  Interestingly, these enzymes will be directly correlated when the liver becomes toxified.

 

Correlated findings 3.png

 

Frequencies compares the frequencies of categorical findings data of each site to all other sites to assess any unusual data patterns to detect and correct quality issues. This report identifies unusual frequencies across the entire study or by study visit. This analysis is typically used on categorical variables, though an analysis on continuous outcomes can identify an over- or under-representation of certain values at a site compared to other sites. This test uses LB and EG data and can be filtered by Visit Number.

 

Frequencies 1.pngFrequencies 2.png

 

Summary Statistics compares the summary statistics of continuous findings data of each site to all other sites to assess any unusual data patterns. It looks for standardized differences in mean values for findings tests for sites compared to all other sites.

 

Summary Statistics.png

 

Screening Bias allows the analyst to identify any large within-site changes in values between two visits to identify regression to the mean in assessing study entry criteria. Analyses are performed using paired t-tests.

 

Screening Bias.png

 

 

 

 

 

Last Modified: Jan 22, 2025 12:53 AM