Validation of Electronic Systems to Collect Patient-Reported Outcome (PRO) Data—Recommendations for Clinical Trial Teams: Report of the ISPOR ePRO Systems Validation Good Research Practices Task Force

AbstractOutcomes research literature has many examples of high-quality, reliable patient-reported outcome (PRO) data entered directly by electronic means, ePRO, compared to data entered from original results on paper. Clinical trial managers are increasingly using ePRO data collection for PRO-based end points. Regulatory review dictates the rules to follow with ePRO data collection for medical label claims. A critical component for regulatory compliance is evidence of the validation of these electronic data collection systems. Validation of electronic systems is a process versus a focused activity that finishes at a single point in time. Eight steps need to be described and undertaken to qualify the validation of the data collection software in its target environment: requirements definition, design, coding, testing, tracing, user acceptance testing, installation and configuration, and decommissioning. These elements are consistent with recent regulatory guidance for systems validation. This report was written to explain how the validation process works for sponsors, trial teams, and other users of electronic data collection devices responsible for verifying the quality of the data entered into relational databases from such devices. It is a guide on the requirements and documentation needed from a data collection systems provider to demonstrate systems validation. It is a practical source of information for study teams to ensure that ePRO providers are using system validation and implementation processes that will ensure the systems and services: operate reliably when in practical use; produce accurate and complete data and data files; support management control and comply with any existing regulations. Furthermore, this short report will increase user understanding of the requirements for a technology review leading to more informed and balanced recommendations or decisions on electronic data collection methods