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19-08-2020 | Regular Paper

Ubiquitous Health Profile (UHPr): a big data curation platform for supporting health data interoperability

Authors: Fahad Ahmed Satti, Taqdir Ali, Jamil Hussain, Wajahat Ali Khan, Asad Masood Khattak, Sungyoung Lee

Published in: Computing | Issue 11/2020

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Abstract

The lack of Interoperable healthcare data presents a major challenge, towards achieving ubiquitous health care. The plethora of diverse medical standards, rather than common standards, is widening the gap of interoperability. While many organizations are working towards a standardized solution, there is a need for an alternate strategy, which can intelligently mediate amongst a variety of medical systems, not complying with any mainstream healthcare standards while utilizing the benefits of several standard merging initiates, to eventually create digital health personas. The existence and efficiency of such a platform is dependent upon the underlying storage and processing engine, which can acquire, manage and retrieve the relevant medical data. In this paper, we present the Ubiquitous Health Profile (UHPr), a multi-dimensional data storage solution in a semi-structured data curation engine, which provides foundational support for archiving heterogeneous medical data and achieving partial data interoperability in the healthcare domain. Additionally, we present the evaluation results of this proposed platform in terms of its timeliness, accuracy, and scalability. Our results indicate that the UHPr is able to retrieve an error free comprehensive medical profile of a single patient, from a set of slightly over 116.5 million serialized medical fragments for 390,101 patients while maintaining a good scalablity ratio between amount of data and its retrieval speed.

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Appendix
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Metadata
Title
Ubiquitous Health Profile (UHPr): a big data curation platform for supporting health data interoperability
Authors
Fahad Ahmed Satti
Taqdir Ali
Jamil Hussain
Wajahat Ali Khan
Asad Masood Khattak
Sungyoung Lee
Publication date
19-08-2020
Publisher
Springer Vienna
Published in
Computing / Issue 11/2020
Print ISSN: 0010-485X
Electronic ISSN: 1436-5057
DOI
https://doi.org/10.1007/s00607-020-00837-2

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