TY  - JOUR
A1  - Datta, Suparno
A1  - Sachs, Jan Philipp
A1  - Freitas da Cruz, Harry
A1  - Martensen, Tom
A1  - Bode, Philipp
A1  - Morassi Sasso, Ariane
A1  - Glicksberg, Benjamin S.
A1  - Böttinger, Erwin
T1  - FIBER
T2  - JAMIA open
N2  - Objectives: 
The development of clinical predictive models hinges upon the availability of comprehensive clinical data. Tapping into such resources requires considerable effort from clinicians, data scientists, and engineers. Specifically, these efforts are focused on data extraction and preprocessing steps required prior to modeling, including complex database queries. A handful of software libraries exist that can reduce this complexity by building upon data standards. However, a gap remains concerning electronic health records (EHRs) stored in star schema clinical data warehouses, an approach often adopted in practice. In this article, we introduce the FlexIBle EHR Retrieval (FIBER) tool: a Python library built on top of a star schema (i2b2) clinical data warehouse that enables flexible generation of modeling-ready cohorts as data frames. 

Materials and Methods: 
FIBER was developed on top of a large-scale star schema EHR database which contains data from 8 million patients and over 120 million encounters. To illustrate FIBER's capabilities, we present its application by building a heart surgery patient cohort with subsequent prediction of acute kidney injury (AKI) with various machine learning models. 

Results:
Using FIBER, we were able to build the heart surgery cohort (n = 12 061), identify the patients that developed AKI (n = 1005), and automatically extract relevant features (n = 774). Finally, we trained machine learning models that achieved area under the curve values of up to 0.77 for this exemplary use case.

Conclusion: 
FIBER is an open-source Python library developed for extracting information from star schema clinical data warehouses and reduces time-to-modeling, helping to streamline the clinical modeling process.
KW  - databases
KW  - factual
KW  - electronic health records
KW  - information storage and
KW  - retrieval
KW  - workflow
KW  - software/instrumentation
Y1  - 2021
UR  - https://publishup.uni-potsdam.de/frontdoor/index/index/docId/60447
SN  - 2574-2531
VL  - 4
IS  - 3
PB  - Oxford Univ. Press
CY  - Oxford
ER  -