Lean Study Host: Towards an Automated Pipeline for Multi-Center Study Hosting

Simple item page
dc.contributor.authorHeine, Lukas
dc.contributor.authorHörst, Fabian
dc.contributor.authorNasca, Enrico
dc.contributor.authorSiveke, Jens
dc.contributor.authorEgger, Jan
dc.contributor.authorKim, Moon
dc.contributor.authorBahnsen, Fin Hendrik
dc.contributor.authorKleesiek, Jens
dc.date.accessioned2023-12-26T18:40:01Z
dc.date.available2023-12-26T18:40:01Z
dc.date.issued2024-01-03
dc.identifier.doi10.24251/HICSS.2024.392
dc.identifier.isbn978-0-9981331-7-1
dc.identifier.other434dd64f-72e9-443c-a2d3-baecba54f97b
dc.identifier.urihttps://hdl.handle.net/10125/106775
dc.language.isoeng
dc.relation.ispartofProceedings of the 57th Hawaii International Conference on System Sciences
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 International
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subjectData Platforms and Ecosystems in Healthcare
dc.subjectci/cd
dc.subjectdata management platform
dc.subjectfhir
dc.subjecthealthcare infrastructure
dc.subjectstudy management
dc.titleLean Study Host: Towards an Automated Pipeline for Multi-Center Study Hosting
dc.typeConference Paper
dc.type.dcmiText
dcterms.abstractMedical 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.
dcterms.extent10 pages
prism.startingpage3235

Files

Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
0317.pdf
Size:
542.2 KB
Format:
Adobe Portable Document Format
Download

Collections

Data Platforms and Ecosystems in Healthcare