Methodology for Assessing Patient Centricity and Data Integrity in Clinical Trials With Decentralized Elements: A...

Decentralized elements enhanced patient centricity by shifting trial-related activities outside traditional trial sites. On the other hand, remote data collection poses potential risks to data integrity. Although these two are critical aspects of decentralized elements, methodologies for assessing them remain limited. We proposed a method to measure patient centricity by subtracting the participant's self-rated burden for trial-related procedures with decentralized elements from their estimated burden under the traditional approach. Additionally, we introduced an analytical framework to assess data integrity by considering the accurate performance rate, the sources of errors, and their cascading consequences. The feasibility and applicability of these methodologies were explored in a pilot clinical trial on mastic gum. Patient centricity was highest in wearable device-based drug adherence monitoring (4.30) and lowest in remote consent submission (1.80). For most trial-related procedures, patient centricity tended to be higher when participant engagement increased. However, blood sample collection recorded higher patient centricity when participants visited a nearby local hospital for nurse assistance (2.55) compared to the estimated burden of using a self-kit at home (2.35). Data integrity was lowest in wearable device-based drug adherence monitoring (88.6%), and the errors were attributable to the device being left behind, insufficient proficiency, broken WiFi connection, and depleted battery. Data integrity was second lowest in self-kit-based stool specimen collection (90.0%), and the errors led to successive delays in specimen delivery and microbiome analysis. The proposed methodologies will provide a foundation for assessing and predicting the impact of decentralized elements on clinical trials. Trial Registration: ClinicalTrials.gov identifier: NCT06005805.