recruIT: A cloud-native clinical trial recruitment support system based on Health Level 7 Fast Healthcare Interoperability Resources (HL7 FHIR) and the Observational Medical Outcomes Partnership Common Data Model (OMOP CDM)

被引：0

作者：

Gulden C. ^{[1
]}

Macho P. ^{[2
]}

Reinecke I. ^{[3
]}

Strantz C. ^{[1
]}

Prokosch H.-U. ^{[1
]}

Blasini R. ^{[4
]}

机构：

[1] Friedrich-Alexander-Universität Erlangen-Nürnberg, Department of Medical Informatics, Biometrics and Epidemiology, Medical Informatics, Erlangen

[2] Medical Informatics, Institute of Medical Biostatistics, Epidemiology and Informatics, University Medical Center of the Johannes Gutenberg-University Mainz, Mainz

[3] Carl Gustav Carus Faculty of Medicine, Center for Medical Informatics, Institute for Medical Informatics and Biometry, Technische Universität Dresden, Dresden

[4] Institute of Medical Informatics, Justus Liebig University, Giessen

来源：

Computers in Biology and Medicine | 2024年 / 174卷

关键词：

44;

D O I：

10.1016/j.compbiomed.2024.108411

中图分类号：

学科分类号：

摘要：

Background: Clinical trials (CTs) are foundational to the advancement of evidence-based medicine and recruiting a sufficient number of participants is one of the crucial steps to their successful conduct. Yet, poor recruitment remains the most frequent reason for premature discontinuation or costly extension of clinical trials. Methods: We designed and implemented a novel, open-source software system to support the recruitment process in clinical trials by generating automatic recruitment recommendations. The development is guided by modern, cloud-native design principles and based on Health Level 7 (HL7) Fast Healthcare Interoperability Resources (FHIR) as an interoperability standard with the Observational Medical Outcomes Partnership (OMOP) Common Data Model (CDM) being used as a source of patient data. We evaluated the usability using the system usability scale (SUS) after deploying the application for use by study personnel. Results: The implementation is based on the OMOP CDM as a repository of patient data that is continuously queried for possible trial candidates based on given clinical trial eligibility criteria. A web-based screening list can be used to display the candidates and email notifications about possible new trial participants can be sent automatically. All interactions between services use HL7 FHIR as the communication standard. The system can be installed using standard container technology and supports more sophisticated deployments on Kubernetes clusters. End-users (n = 19) rated the system with a SUS score of 79.9/100. Conclusion: We contribute a novel, open-source implementation to support the patient recruitment process in clinical trials that can be deployed using state-of-the art technologies. According to the SUS score, the system provides good usability. © 2024 The Authors

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