Authors:
Vincent Menger
1
;
Marco Spruit
2
;
Jonathan de Bruin
3
;
Thomas Kelder
4
and
Floor Scheepers
5
Affiliations:
1
Department of Information and Computing Sciences, Utrecht University, Princetonplein 5, Utrecht, The Netherlands, Department of Psychiatry, University Medical Center Utrecht, Utrecht and The Netherlands
;
2
Department of Information and Computing Sciences, Utrecht University, Princetonplein 5, Utrecht and The Netherlands
;
3
Department of Information and Technology Services, Utrecht University, Utrecht and The Netherlands
;
4
EdgeLeap B.V., Utrecht and The Netherlands
;
5
Department of Psychiatry, University Medical Center Utrecht, Utrecht and The Netherlands
Keyword(s):
EHR, Data Management, Infrastructure, Open Source, Repeatability, Data Preparation, Data Analysis.
Related
Ontology
Subjects/Areas/Topics:
Artificial Intelligence
;
Biomedical Engineering
;
Data Mining
;
Databases and Datawarehousing
;
Databases and Information Systems Integration
;
Enterprise Information Systems
;
Health Information Systems
;
Healthcare Management Systems
;
Sensor Networks
;
Signal Processing
;
Soft Computing
;
Software Systems in Medicine
Abstract:
Healthcare organizations have in recent years started assembling their Electronic Health Record (EHR) data in data repositories to unlock their value using data analysis techniques. There are however a number of technical, organizational and ethical challenges that should be considered when reusing EHR data, which infrastructure technology consisting of appropriate software and hardware components can address. In a case study in the University Medical Center Utrecht (UMCU) in the Netherlands, we identified nine requirements of a modern technical infrastructure for reusing EHR data: (1) integrate data sources, (2) preprocess data, (3) store data, (4) support collaboration and documentation, (5) support various software and tooling packages, (6) enhance repeatability, (7) enhance privacy and security, (8) automate data process and (9) support analysis applications. We propose the CApable Reuse of EHR Data (CARED) framework for infrastructure that addresses these requirements, which con
sists of five consecutive data processing layers, and a control layer that governs the data processing. We then evaluate the framework with respect to the requirements, and finally describe its successful implementation in the Psychiatry Department of the UMCU along with three analysis cases. Our CARED research infrastructure framework can support healthcare organizations that aim to successfully reuse their EHR data.
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