Data Provenance in Healthcare: Approaches, Challenges, and Future Directions

Journal article

Mansoor Ahmed (PhD), Amil Dar, Markus Helfert, Khan, A. and Jungsuk Kim 2023. Data Provenance in Healthcare: Approaches, Challenges, and Future Directions. Sensors. 23 (14), pp. 1-26. https://doi.org/10.3390/s23146495
AuthorsMansoor Ahmed (PhD), Amil Dar, Markus Helfert, Khan, A. and Jungsuk Kim
Abstract

Data provenance means recording data origins and the history of data generation and processing. In healthcare, data provenance is one of the essential processes that make it possible to track the sources and reasons behind any problem with a user’s data. With the emergence of the General Data Protection Regulation (GDPR), data provenance in healthcare systems should be implemented to give users more control over data. This SLR studies the impacts of data provenance in healthcare and GDPR-compliance-based data provenance through a systematic review of peer-reviewed articles. The SLR discusses the technologies used to achieve data provenance and various methodologies to achieve data provenance. We then explore different technologies that are applied in the healthcare domain and how they achieve data provenance. In the end, we have identified key research gaps followed by future research directions.

KeywordsData provenance ; healthcare ; provenance technologies; cryptography; ontologies; blockchain
Year2023
JournalSensors
Journal citation23 (14), pp. 1-26
PublisherMDPI
ISSN1424-8220
Digital Object Identifier (DOI)https://doi.org/10.3390/s23146495
Web address (URL)https://www.mdpi.com/1424-8220/23/14/6495
Output statusPublished
Publication dates18 Jul 2023
Publication process dates
Deposited24 Aug 2023
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