Background: Recently, the Austrian Patient Summary (APS) and Austrian Microbiology Report (AMR) document definitions were added to the Austrian national electronic health record repository. How to employ these standardized, structured patient data in clinical decision support (CDS) systems remains an interesting research subject. Objectives: To create a proof of concept for the emergency use of APS and AMR documents in a variety of CDS platforms and standards in an intensive care setting, in order to generate new insights by linking individual documents to different CDS approaches. Methods: APS and AMR definitions were stored using MongoDB, a document-oriented database system. For implementation of the clinical use case CDS, we selected the Drools business rule management system, as well as the ArdenSuite software for implementing the HL7 Arden Syntax for Medical Logic Systems standard. Results: Due to its manifold features, implementation of the CDS use case in Drools could be done quite efficiently without the need for additional coding of technical or algorithmic code, which results in smaller rules. In contrast, the use case implementations in Arden Syntax using the ArdenSuite required additional technical coding, distracting from the medical knowledge implementation. The Arden Syntax as a knowledge definition standard is, however, better understandable due to its resemblance to natural language compared to the Java-like definition language used in Drools. Conclusion: With the nation-wide availability of structured documents, the foundation for the implementation of clinical decision support systems has been laid. Commonly used open-source platforms offer extensive possibilities for the implementation of CDS systems. This evaluation of modern business rule management systems will advance the implementation of powerful clinical decision support solutions valuable to all stakeholders.

ELGA GmbH Austria

HL7 Austria Austria

Institute of eHealth Department of Applied Computer Science FH Joanneum University of Applied Computer Sciences GmbH Graz Austria

Section for Artificial Intelligence and Decision Support Center for Medical Statistics Informatics and Intelligent Systems Medical University of Vienna Vienna Austria

Citace poskytuje Crossref.org

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