SANDS: A service-oriented architecture for clinical decision support in a National Health Information Network

• Authors: Adam Wright;Dean F. Sittig
• Venue: Journal of Biomedical Informatics
• Year: 2008

In this paper, we describe and evaluate a new distributed architecture for clinical decision support called SANDS (Service-oriented Architecture for NHIN Decision Support), which leverages current health information exchange efforts and is based on the principles of a service-oriented architecture. The architecture allows disparate clinical information systems and clinical decision support systems to be seamlessly integrated over a network according to a set of interfaces and protocols described in this paper. The architecture described is fully defined and developed, and six use cases have been developed and tested using a prototype electronic health record which links to one of the existing prototype National Health Information Networks (NHIN): drug interaction checking, syndromic surveillance, diagnostic decision support, inappropriate prescribing in older adults, information at the point of care and a simple personal health record. Some of these use cases utilize existing decision support systems, which are either commercially or freely available at present, and developed outside of the SANDS project, while other use cases are based on decision support systems developed specifically for the project. Open source code for many of these components is available, and an open source reference parser is also available for comparison and testing of other clinical information systems and clinical decision support systems that wish to implement the SANDS architecture. The SANDS architecture for decision support has several significant advantages over other architectures for clinical decision support. The most salient of these are: 1.Greater modularity than other architectures, allowing for work to be distributed. 2.The potential for creating and sustaining a commercial market for clinical decision support. 3.Reduced cost and risk of trying new decision support systems because of its ability to easily integrate a variety of decision support services, and to easily remove them, if desired, as well. 4.Significant freedom for developers of clinical decision support systems to choose the way they represent knowledge and internally implement their system, in comparison to other approaches which constrain such developers to a particular knowledge representation formalism. 5.Unification of the direction and agenda of decision support research and development with promising near-term efforts to improve interoperability of clinical systems.