Future-generation healthcare systems will be highly distributed, combining centralised hospital systems with decentralised homework rk-and environment-based monitoring and diagnostics systems. These will reduce costs and injuryrelated risks whilst both improving quality of service, and reducing the response time for diagnostics and treatments made available to patients. To make this vision possible, medical data must be accessed and shared over a variety of mediums including untrusted networks. In this paper, we present the design and initial implementation of the SERUMS tool-chain for accessing, storing, communicating and analysing highly confidential medical data in a safe, secure and privacypreserving way. In addition, we describe a data fabrication framework for generating large volumes of synthetic but realistic data, that is used in the design and evaluation of the tool-chain. We demonstrate the present version of our technique on a use case derived from the Edinburgh Cancer Centre, NHS Lothian, where information about the effects of chemotherapy treatments on cancer patients is collected from different distributed databases, analysed and adapted to improve ongoing treatments.

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.

To facilitate personalised healthcare provision across Europe, we envision solutions that enable the secure integration and sharing of medical health records. These solutions should address privacy concerns, such as granular access control to personal data, establishing what should be accessible when and by whom, whilst complying with collective regulatory frameworks such as the European General Data Protection Regulation (GDPR) and adhering to international standards on how to manage information security. The proposed healthcare system design integrates technologies such as blockchain and scalable data lakes with adequate system routines to guarantee the secure access of confidential data. In this paper, we present the essential architectural components for the secure integration of medical records in a blockchain-based platform. We present a patient-centric data retrieval approach which incorporates a structured format to compose access rules.

Designing patient-centric healthcare systems which consider the smart integration of distributed medical data is challenging. This includes handling numerous architectural dependencies and requirements as a result of blending a variety of future generation technologies. Examples of recent approaches are proposals of a unified format for medical records to facilitate efficient healthcare provision, transparent data access control using blockchain technology, and emergent authentication mechanisms and privacy-preserving techniques for data analytics. The Serums project proposes an innovative design for a Smart Health Centre System in a distributed development effort. The goal is a comprehensive solution for integration and access of transnational medical records. This paper focuses on the architectural design workflow as a way of delivering artefacts for development iterations and contribute towards module integration planning in the software development process. Our experience shows that in data integration projects for healthcare provision, system architects and developers can profit from the designed viewpoints as artefacts to reveal integration challenges and highlight quality attributes.

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