An Event-driven Health Service Bus

Abstract

The enormous set of health and wellbeing data sources, as well as the diversity of the data, calls for an effective, time-aware integration paradigm that aids at the manipulation of the information by experts as a whole and not as individual pieces of knowledge. In this paper, we present the Health Service Bus, a service-based platform built on top of the Enterprise Service Bus architecture. Treating new information, either humangenerated (e.g., doctors, dieticians, etc.) or device-generated (i.e., smart wristbands or connected scales) as events allows for in-time action and treatment. Platform interoperability is ensured both on service level, since any service irrespective of its specification can be plugged into the Health Service Bus seamlessly, and on data level, since health standards, such as HL7 FHIR and LOINC, are leveraged.

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

“…Using a publish/subscribe model, the services are able to communicate with each other using event driven paradigm. In healthcare IBM provided an early implementation of the ESB to create the IBM Healthcare Service Bus [56] which enables the integration of multiple services by using web services description language (WSDL) [86], simple object access protocol (SOAP) [87], and HL7 Standards. The service has now been upgraded [38] to become completely deployable on the cloud and to provide support for many healthcare standards suchs as HL7v2.X, Fast Healthcare Interoperability Resources (FHIR) [36], Digital Imaging and Communications in Medicine (DICOM), and others.…”

“…The HSB uses SNOMED CT for providing terminological services, which are also embedded into the ESB as XML messages and used with a custom ontology mapping tool called OWLmt to provide semantic interoperability between patient records. In [56] an event-based HSB based on the JBossESB is presented which converts heterogeneous data into RDF quads, before utilizing the health and lifelogging data (HLD) Ontology for building a semantically linked graph of health and lifelog data. The authors have used LOINC as the terminological handler, which is used to provide semantically annotated versions of input sensory data from wearable devices, before creating the RDF quads and applying semantic integration using the HLD ontology.…”