Integrating healthcare data for enhanced citizen-centred care and analytics
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The potential of healthcare systems worldwide is expanding as new medical devices and data sources are regularly presented to healthcare providers which could be used to personalise, improve and revise treatments further. However, there is presently a large gap between the data collected, the systems that store the data, and any ability to perform big data analytics to combinations of such data. This paper suggests a novel approach to integrate data from multiple sources and formats, by providing a uniform structure to the data in a healthcare data lake with multiple zones reflecting how refined the data is: from raw to curated when ready to be consumed or used for analysis. The integration further requires solutions that can be proven to be secure, such as patient-centric data sharing agreements (smart contracts) on a blockchain, and novel privacy-preserving methods for extracting metadata from data sources, originally derived from partially-structured or from completely unstructured data. Work presented here is being developed as part of an EU project with the ultimate aim to develop solutions for integrating healthcare data for enhanced citizen-centred care and analytics across Europe.
Kuster Filipe Bowles , J , Mendoza Santana , J J , Vermeulen , A F , Webber dos Santos , T C & Blackledge , E 2020 , Integrating healthcare data for enhanced citizen-centred care and analytics . in M Hägglund , P Gallos , K Häyrinen , K Saranto , P Scott , A Värri , J Delgado , U-M Kinnunen , L B Pape-Haugaard & L-M Peltonen (eds) , Integrated Citizen Centered Digital Health and Social Care : Citizens as Data Producers and Service co-Creators . Studies in Health Technology and Informatics , vol. 275 , IOS Press , pp. 17-21 , EFMI 2020 Special Topic Conference , 26/11/20 . https://doi.org/10.3233/SHTI200686conference
Integrated Citizen Centered Digital Health and Social Care
Copyright © 2020 The European Federation for Medical Informatics (EFMI) and IOS Press. This article is published online with Open Access by IOS Press and distributed under the terms of the Creative Commons Attribution Non-Commercial License 4.0 (CC BY-NC 4.0).
DescriptionThis research is funded by the EU H2020 project SERUMS: Securing Medical Data in Smart Patient-Centric Healthcare Systems (grant code 826278).
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