A workflow management system for the OR based on the OMG standards BPMN, CMMN, and DMN

M. Wiemuth; O. Burgert

doi:10.1117/12.2512724

8 March 2019 A workflow management system for the OR based on the OMG standards BPMN, CMMN, and DMN

M. Wiemuth, O. Burgert

Proceedings Volume 10951, Medical Imaging 2019: Image-Guided Procedures, Robotic Interventions, and Modeling; 1095127 (2019) https://doi.org/10.1117/12.2512724
Event: SPIE Medical Imaging, 2019, San Diego, California, United States

Abstract

Workflow driven support systems in the peri-operative area have the potential to optimize clinical processes and to allow new situation-adaptive support systems. We started to develop a workflow management system supporting all involved actors in the operating theatre with the goal to synchronize the tasks of the different stakeholders by giving relevant information to the right team members. Using the OMG standards BPMN, CMMN and DMN gives us the opportunity to bring established methods from other industries into the medical field. The system shows each addressed actor their information in the right place at the right time to make sure every member can execute their task in time to ensure a smooth workflow. The system has the overall view of all tasks. Accordingly, a workflow management system including the Camunda BPM workflow engine to run the models, and a middleware to connect different systems to the workflow engine and some graphical user interfaces to show necessary information or to interact with the system are used. The complete pipeline is implemented with a RESTful web service. The system is designed to include different systems like hospital information system (HIS) via the RESTful web service very easily and without loss of data. The first prototype is implemented and will be expanded.

Citation Download Citation

M. Wiemuth and O. Burgert "A workflow management system for the OR based on the OMG standards BPMN, CMMN, and DMN", Proc. SPIE 10951, Medical Imaging 2019: Image-Guided Procedures, Robotic Interventions, and Modeling, 1095127 (8 March 2019); https://doi.org/10.1117/12.2512724

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