Electronic Health Record based recruitment support systems: A scoping review to improve patient inclusion within clinical trials
Résumé
Objective Electronic Health Record (EHR) data is increasingly used to support patient recruitment in clinical trials (CTs). This scoping review focused on articles reporting an evaluation of EHR-based CT recruitment support systems (CTRSS). Methods Querying 3 biomedical literature databases using keywords as “clinical trial as topic”, “patient recruitment”, and “EHR” research articles describing evaluations of EHR-based CTRSS and published in English from 2013 to 2024 were included. Abstract screening was performed by 5 reviewers. Two reviewers performed full-text screening, data extraction and synthesis following 3 major themes: clinical workflow integration, technical aspects, and evaluation of EHR-based CTRSS. Results Of 927 screened articles, 44 qualified in scope, providing an evaluation of EHR-based CTRSS conducted within a diverse set of use cases, settings, and technologies. Results showed that 75% of the systems were CT rather than patient centric, and 20% provided patient eligibility information at clinically relevant timepoints in the patient journey and 9% sent notifications to the targeted users. EHR data was transformed according to standard models in 32% of the studies. Eligibility criteria transformation was computer assisted in 48% of the studies. The main patient-trial matching technique was querying structured data in 55% of the cases. Finally, the majority (61%) of evaluations were done retrospectively and led to a complete system evaluation from data transformation to patient – trial matching in 18%. Conclusion Despite the diversity of system scopes and designs, metrics for effective evaluation throughout the entire cycle of system implementation across user, technology, and society levels are emerging. Research effort is still needed to extend the scope, quality, and computability of both the source EHR-data and EC and to conduct harmonized evaluation of these systems to demonstrate their impact on recruitment rates, delays, and costs.
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