Risk-Based Monitoring and Fraud Detection in Clinical Trials Using JMP and SAS

4.5 Final Thoughts

While I addressed a variety of techniques to identify data anomalies resulting from potential fraud and other quality issues at the clinical sites, the list of methods I presented is by no means complete; in fact, I have only just scratched the surface! The literature contains many additional analyses useful for identifying unusual data arising in a clinical trial [1,3-5,17,18,27-29]. Though these analyses are often presented in the context of detecting issues as a result of misconduct at the clinical site, hopefully the presentation above has illustrated how these analytical techniques can be used to identify any number of quality issues that may arise in a clinical trial. I believe that these techniques should be applied ...