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

5.1 Introduction

In Chapter 4, I presented ways to identify various data anomalies that are specific to the clinical site: how the site adheres to the trial protocol, how site personnel collect and report data, and even how equipment may be performing. In this chapter, we focus on the study participants. Patient behavior can greatly affect the outcome of a clinical trial. This is true if patients are noncompliant in taking their study medication, or if they fail to properly complete or maintain a study diary to record various symptoms or episodes of their disease (a familiar example is the patient who completes his or her study diary in the clinic parking lot just prior to a visit). In this chapter, we focus solely on identifying patients who ...