Optimized continuous homecare provisioning through distributed data-driven semantic services and cross-organizational workflows

Mathias De BrouwerMathias De Brouwer, Pieter BontePieter Bonte, Dörthe ArndtDörthe Arndt, Miel Vander SandeMiel Vander Sande, Anastasia DimouAnastasia Dimou, Ruben VerborghRuben Verborgh, Filip De TurckFilip De Turck, Femke OngenaeFemke Ongenae

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Mathias De Brouwer, Pieter Bonte, Dörthe Arndt, Miel Vander Sande, Anastasia Dimou, Ruben Verborgh, Filip De Turck, Femke Ongenae
Optimized continuous homecare provisioning through distributed data-driven semantic services and cross-organizational workflows
Journal of Biomedical Semantics, 15(9), June 2024

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KurzfassungAbstract
Background
In healthcare, an increasing collaboration can be noticed between different caregivers, especially considering the shift to homecare. To provide optimal patient care, efficient coordination of data and workflows between these different stakeholders is required. To achieve this, data should be exposed in a machine-interpretable, reusable manner. In addition, there is a need for smart, dynamic, personalized and performant services provided on top of this data. Flexible workflows should be defined that realize their desired functionality, adhere to use case specific quality constraints and improve coordination across stakeholders. User interfaces should allow configuring all of this in an easy, user-friendly way.
Methods A distributed, generic, cascading reasoning reference architecture can solve the presented challenges. It can be instantiated with existing tools built upon Semantic Web technologies that provide data-driven semantic services and constructing cross-organizational workflows. These tools include RMLStreamer to generate Linked Data, DIVIDE to adaptively manage contextually relevant local queries, Streaming MASSIF to deploy reusable services, AMADEUS to compose semantic workflows, and RMLEditor and Matey to configure rules to generate Linked Data.
Results A use case demonstrator is built on a scenario that focuses on personalized smart monitoring and cross-organizational treatment planning. The performance and usability of the demonstrator’s implementation is evaluated. The former shows that the monitoring pipeline efficiently processes a stream of 14 observations per second: RMLStreamer maps JSON observations to RDF in 13.5 ms, a C-SPARQL query to generate fever alarms is executed on a window of 5 s in 26.4 ms, and Streaming MASSIF generates a smart notification for fever alarms based on severity and urgency in 1539.5 ms. DIVIDE derives the C-SPARQL queries in 7249.5 ms, while AMADEUS constructs a colon cancer treatment plan and performs conflict detection with it in 190.8 ms and 1335.7 ms, respectively.
Conclusions
Existing tools built upon Semantic Web technologies can be leveraged to optimize continuous care provisioning. The evaluation of the building blocks on a realistic homecare monitoring use case demonstrates their applicability, usability and good performance. Further extending the available user interfaces for some tools is required to increase their adoption.
Forschungsgruppe:Research Group: Computational LogicComputational Logic

@article{BBASDVTO2024,
  author  = {Mathias De Brouwer and Pieter Bonte and D{\"{o}}rthe Arndt and Miel
             Vander Sande and Anastasia Dimou and Ruben Verborgh and Filip De
             Turck and Femke Ongenae},
  title   = {Optimized continuous homecare provisioning through distributed
             data-driven semantic services and cross-organizational workflows},
  journal = {Journal of Biomedical Semantics},
  volume  = {15},
  number  = {9},
  year    = {2024},
  month   = {June},
  doi     = {https://doi.org/10.1186/s13326-024-00303-4}
}