TY - GEN
T1 - Lean Study Host
T2 - 57th Annual Hawaii International Conference on System Sciences, HICSS 2024
AU - Heine, Lukas
AU - Hörst, Fabian
AU - Nasca, Enrico
AU - Egger, Jan
AU - Siveke, Jens T.
AU - Kim, Moon
AU - Kleesiek, Jens
AU - Bahnsen, Fin H.
N1 - Publisher Copyright:
© 2024 IEEE Computer Society. All rights reserved.
PY - 2024
Y1 - 2024
N2 - Medical studies are an essential part of advancing research. A uniform, flexible software infrastructure that allows for straightforward data management stands at the core of studies that involve multiple sites. Such a solution must accommodate the specific technical needs of clinical practitioners and researchers, such as uploading, viewing, downloading, annotating, and sharing image material in various forms. The current tool landscape needs a solution that bridges the gap between intuitive data governance and usability without introducing undesired technical and legal overhead. We present “Lean Study Host” (LSH), a novel, open-source approach to clinical study data management that caters to clinicians, technical staff, and data protection officers. It seeks to reduce technical, administrative, and legal overhead to allow studies to focus more efforts on research. It combines a cloud-native, microservice-based architecture, deidentification, and on-premises hosting to keep data sovereignty within the local institution.
AB - Medical studies are an essential part of advancing research. A uniform, flexible software infrastructure that allows for straightforward data management stands at the core of studies that involve multiple sites. Such a solution must accommodate the specific technical needs of clinical practitioners and researchers, such as uploading, viewing, downloading, annotating, and sharing image material in various forms. The current tool landscape needs a solution that bridges the gap between intuitive data governance and usability without introducing undesired technical and legal overhead. We present “Lean Study Host” (LSH), a novel, open-source approach to clinical study data management that caters to clinicians, technical staff, and data protection officers. It seeks to reduce technical, administrative, and legal overhead to allow studies to focus more efforts on research. It combines a cloud-native, microservice-based architecture, deidentification, and on-premises hosting to keep data sovereignty within the local institution.
KW - CI/CD
KW - Data management platform
KW - FHIR
KW - Healthcare infrastructure
KW - Study management
UR - http://www.scopus.com/inward/record.url?scp=85199780105&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:85199780105
T3 - Proceedings of the Annual Hawaii International Conference on System Sciences
SP - 3235
EP - 3244
BT - Proceedings of the 57th Annual Hawaii International Conference on System Sciences, HICSS 2024
A2 - Bui, Tung X.
PB - IEEE Computer Society
Y2 - 3 January 2024 through 6 January 2024
ER -