OBJECTIVES: Routinely collected Electronic Health Record (EHR) data present opportunities for conducting clinical trials (eRCTs). However, their characteristics in comparison to traditional RCTs have implication for applying Good Clinical Practice (GCP) guidelines for regulating trial data. The aim of this review was to assess the differences between conventional RCTs and eRCTs in terms of threats and opportunities for how to safeguard the accuracy of data collected and prevent poor practice such as inventing data, from outcomes to whole patient records (fabrication); and changing data, such as modifying inclusion exclusion criteria for a patient (falsification).

METHODS: A methodological literature review of the characteristics of eRCTs compared to traditional RCTs and implications for the risk of fraud; and a review of methods that can be used to detect fraud in electronic data to ensure compliance with GCP.

RESULTS: The characteristics of eRCTs, such as the availability of longitudinal data available for the time periods before and after the study period and the rich and complex EHR data, makes false or fabricated data easier to audit and detect. For example, identifying how many potentially eligible patients failed to be recruited or discovering an invented patient by looking at the whole patient record. Established statistical methods designed to detect fraudulent activity, such as analysing patterns, could be used to identify errors and outliers. In addition, data can be verified independently through linked data sources and can be compared with that of non-participants.

CONCLUSIONS: Characteristics of eRCTs permit clinical data to be collected over long periods, facilitating trials that measure real-world clinical outcomes with long-term follow-up periods, at lower cost than conventional trials. There are some clear advantages of eRCTs for auditing and verifying data quality on which trials are based.