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HEALTH BANK - A Workbench for Data Science Applications in Healthcare
Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
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2015 (English)In: Industry Track Workshop, CEUR Workshop Proceedings , 2015, Vol. 1381, 1-18 p.Conference paper, Published paper (Refereed)
Abstract [en]

The enormous amounts of data that are generated in the healthcare process and stored in electronic health record (EHR) systems are an underutilized resource that, with the use of data science applica- tions, can be exploited to improve healthcare. To foster the development and use of data science applications in healthcare, there is a fundamen- tal need for access to EHR data, which is typically not readily available to researchers and developers. A relatively rare exception is the large EHR database, the Stockholm EPR Corpus, comprising data from more than two million patients, that has been been made available to a lim- ited group of researchers at Stockholm University. Here, we describe a number of data science applications that have been developed using this database, demonstrating the potential reuse of EHR data to support healthcare and public health activities, as well as facilitate medical re- search. However, in order to realize the full potential of this resource, it needs to be made available to a larger community of researchers, as well as to industry actors. To that end, we envision the provision of an in- frastructure around this database called HEALTH BANK – the Swedish Health Record Research Bank. It will function both as a workbench for the development of data science applications and as a data explo- ration tool, allowing epidemiologists, pharmacologists and other medical researchers to generate and evaluate hypotheses. Aggregated data will be fed into a pipeline for open e-access, while non-aggregated data will be provided to researchers within an ethical permission framework. We believe that HEALTH BANK has the potential to promote a growing industry around the development of data science applications that will ultimately increase the efficiency and effectiveness of healthcare.

Place, publisher, year, edition, pages
CEUR Workshop Proceedings , 2015. Vol. 1381, 1-18 p.
Series
CEUR Workshop Proceedings, ISSN 1613-0073 ; 1381
Keyword [en]
electronic health record, data science, health intelligence, infrastructure, data mining, text mining, predictive modeling, clinical text, health bank, health record research
National Category
Information Systems
Research subject
Computer and Systems Sciences
Identifiers
URN: urn:nbn:se:su:diva-122827OAI: oai:DiVA.org:su-122827DiVA: diva2:868614
Conference
CAiSE Industry Track, CAiSE-IT 2015 - co-located with 27th Conference on Advanced Information Systems Engineering, CAiSE 2015; Stockholm; Sweden; 11 June 2015 through ; Code 112715 -------------------------------------------------------------------------------- CAiSE Industry Track, CAiSE-IT 2015 - co-located with 27th Conference on Advanced Information Systems Engineering, CAiSE 2015; Stockholm; Sweden; 11 June 2015 through.
Available from: 2015-11-11 Created: 2015-11-10 Last updated: 2015-12-08Bibliographically approved

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Dalianis, HerculesHenriksson, AronKvist, MariaVelupillai, SumithraWeegar, Rebecka
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