Location
Hilton Hawaiian Village, Honolulu, Hawaii
Event Website
https://hicss.hawaii.edu/
Start Date
3-1-2024 12:00 AM
End Date
6-1-2024 12:00 AM
Description
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.
Recommended Citation
Heine, Lukas; Hörst, Fabian; Nasca, Enrico; Siveke, Jens; Egger, Jan; Kim, Moon; Bahnsen, Fin Hendrik; and Kleesiek, Jens, "Lean Study Host: Towards an Automated Pipeline for Multi-Center Study Hosting" (2024). Hawaii International Conference on System Sciences 2024 (HICSS-57). 2.
https://aisel.aisnet.org/hicss-57/hc/ecosystems/2
Lean Study Host: Towards an Automated Pipeline for Multi-Center Study Hosting
Hilton Hawaiian Village, Honolulu, Hawaii
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.
https://aisel.aisnet.org/hicss-57/hc/ecosystems/2