In recent years clinical data warehouses (CDW) have become more and more popular to support scientific work in the medical domain. Despite the tool support for many subtasks it is still a laborious task to establish a CDW in an existing clinical data environment. We present a workflow which can be taken as a blueprint for newly established CDW projects and the implementation of this blueprint at the University Clinic Würzburg.
%0 Journal Article
%1 noauthororeditor
%A Fette, Georg
%A Ertl, Maximilian
%A Dietrich, Georg
%A Krebs, Jonathan
%A Toepfer, Martin
%A Störk, Stefan
%A Kaspar, Mathias
%A Puppe, Frank
%D 2016
%J European Journal of Epidemiology; Health—exploring complexity: an interdisciplinary systems approach HEC2016
%K myown
%P 54
%T An improved data workflow for a medical data warehouse
%V 31, Supplement 1
%X In recent years clinical data warehouses (CDW) have become more and more popular to support scientific work in the medical domain. Despite the tool support for many subtasks it is still a laborious task to establish a CDW in an existing clinical data environment. We present a workflow which can be taken as a blueprint for newly established CDW projects and the implementation of this blueprint at the University Clinic Würzburg.
@article{noauthororeditor,
abstract = {In recent years clinical data warehouses (CDW) have become more and more popular to support scientific work in the medical domain. Despite the tool support for many subtasks it is still a laborious task to establish a CDW in an existing clinical data environment. We present a workflow which can be taken as a blueprint for newly established CDW projects and the implementation of this blueprint at the University Clinic Würzburg.},
added-at = {2017-07-04T11:12:09.000+0200},
author = {Fette, Georg and Ertl, Maximilian and Dietrich, Georg and Krebs, Jonathan and Toepfer, Martin and Störk, Stefan and Kaspar, Mathias and Puppe, Frank},
biburl = {https://www.bibsonomy.org/bibtex/2162a2bc96506a7cdcdfd969e7ff2888b/jonathan.krebs},
interhash = {4a46621e8fdb0e0f4f6bcebdf3379b69},
intrahash = {162a2bc96506a7cdcdfd969e7ff2888b},
journal = {European Journal of Epidemiology; Health—exploring complexity: an interdisciplinary systems approach HEC2016},
keywords = {myown},
month = {August},
pages = 54,
timestamp = {2017-07-04T11:12:09.000+0200},
title = {An improved data workflow for a medical data warehouse},
volume = {31, Supplement 1},
year = 2016
}