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Purpose
Supporting the surgeon during surgery is one of the main goals of intelligent ORs. The OR-Pad project aims to optimize the information flow within the perioperative area. A shared information space should enable appropriate preparation and provision of relevant information at any time before, during, and after surgery.
Methods
Based on previous work on an interaction concept and system architecture for the sterile OR-Pad system, we designed a user interface for mobile and intraoperative (stationary) use, focusing on the most important functionalities like clear information provision to reduce information overload. The concepts were transferred into a high-fidelity prototype for demonstration purposes. The prototype was evaluated from different perspectives, including a usability study.
Results
The prototype’s central element is a timeline displaying all available case information chronologically, like radiological images, labor findings, or notes. This information space can be adapted for individual purposes (e.g., highlighting a tumor, filtering for own material). With the mobile and intraoperative mode of the system, relevant information can be added, preselected, viewed, and extended during the perioperative process. Overall, the evaluation showed good results and confirmed the vision of the information system.
Conclusion
The high-fidelity prototype of the information system OR-Pad focuses on supporting the surgeon via a timeline making all available case information accessible before, during, and after surgery. The information space can be personalized to enable targeted support. Further development is reasonable to optimize the approach and address missing or insufficient aspects, like the holding arm and sterility concept or new desired features.
Motivation
In order to enable context-aware behavior of surgical assistance systems, the acquisition of various information about the current intraoperative situation is crucial. To achieve this, the complex task of situation recognition can be delegated to a specialized system. Consequently, a standardized interface is required for the seamless transfer of the recognized contextual information to the assistance systems, enabling them to adapt accordingly.
Methods
Our group analyzed four medical interface standards to determine their suitability for exchanging intraoperative contextual information. The assessment was based on a harmonized data and service model derived from the requirements of expected context-aware use cases. The Digital Imaging and Communications in Medicine (DICOM) and IEEE 11073 for Service-oriented Device Connectivity (SDC) were identified as the most appropriate standards.
Results
We specified how DICOM Unified Procedure Steps (UPS), can be used to effectively communicate contextual information. We proposed the inclusion of attributes to formalize different granularity levels of the surgical workflow.
Conclusions
DICOM UPS SOP classes can be used for the exchange of intraoperative contextual information between a situation recognition system and surgical assistance systems. This can pave the way for vendor-independent context awareness in the OR, leading to targeted assistance of the surgical team and an improvement of the surgical workflow.
This project aims to evaluate existing big data infrastructures for their applicability in the operating room to support medical staff with context-sensitive systems. Requirements for the system design were generated. The project compares different data mining technologies, interfaces, and software system infrastructures with a focus on their usefulness in the peri-operative setting. The lambda architecture was chosen for the proposed system design, which will provide data for both postoperative analysis and real-time support during surgery.
In der Medizin existieren verschiedene Reifegradmodelle, die die Digitalisierung von Krankenhäusern unterstützen können. Die Anforderungen an ein Reifegradmodell für diesen Zweck umfassen Aspekte aus allgemeinen und spezifischen Bereichen des Krankenhauses. Die Analyse der Reifegradmodelle HIN, CCMM, EMRAM und O-EMRAM zeigt große Lücken im Bereich des OP sowie fehlende Aspekte in der Notaufnahme auf. Ein umfassendes Reifegradmodell wurde nicht gefunden. Durch eine Kombination aus HIN und CCMM könnten fast alle Bereiche ausreichend abgedeckt werden. Zusätzliche Ergänzungen durch spezialisierte Reifegradmodelle oder sogar die Entwicklung eines umfassenden Reifegradmodells wären sinnvoll.
Purpose: Medical processes can be modeled using different methods and notations.Currently used modeling systems like Business Process Model and Notation (BPMN) are not capable of describing the highly flexible and variable medical processes in sufficient detail.
Methods: We combined two modeling systems, Business Process Management (BPM) and Adaptive Case Management (ACM), to be able to model non-deterministic medical processes. We used the new Standards Case Management Model and Notation (CMMN) and Decision Management Notation (DMN).
Results: First, we explain how CMMN, DMN and BPMN could be used to model non-deterministic medical processes. We applied this methodology to model 79 cataract operations provided by University Hospital Leipzig, Germany, and four cataract operations provided by University Eye Hospital Tuebingen, Germany. Our model consists of 85 tasks and about 20 decisions in BPMN. We were able to expand the system with more complex situations that might appear during an intervention.
Conclusion: An effective modeling of the cataract intervention is possible using the combination of BPM and ACM. The combination gives the possibility to depict complex processes with complex decisions. This combination allows a significant advantage for modeling perioperative processes.
Painting galleries typically provide a wealth of data composed of several data types. Those multivariate data are too complex for laymen like museum visitors to first, get an overview about all paintings and to look for specific categories. Finally, the goal is to guide the visitor to a specific painting that he wishes to have a more closer look on. In this paper we describe an interactive visualization tool that first provides such an overview and lets people experiment with the more than 41,000 paintings collected in the web gallery of art. To generate such an interactive tool, our technique is composed of different steps like data handling, algorithmic transformations, visualizations, interactions, and the human user working with the tool with the goal to detect insights in the provided data. We illustrate the usefulness of the visualization tool by applying it to such characteristic data and show how one can get from an overview about all paintings to specific paintings.
Physicians in interventional radiology are exposed to high physical stress. To avoid negative long-term effects resulting from unergonomic working conditions, we demonstrated the feasibility of a system that gives feedback about unergonomic
situations arising during the intervention based on the Azure Kinect camera. The overall feasibility of the approach could be shown.
Continuous monitoring of individual vital parameters can provide information for the assessment of one’s health and indications of medical problems in the context of personalized medicine. Correlations between parameters and health issues are to be evaluated. As one project in this topic area, a telemedicine platform is implemented to gather data of outpatients via wearables and accumulate them for physicians and researchers to review. This work extracts requirements, draws use case scenarios, and shows the current system architecture consisting of a patient application, a physician application with a web server, and a backend server application. In further work, the prototype will assist to develop a vendor-free and open monitoring solution. A conclusion on functionality and usability will be evaluated in an imminent first study.
Context-aware systems to support actors in the operating room depending on the status of the intervention require knowledge about the current situation in the intra-operative area. In literature, solutions to achieve situation awareness already exist for specific use cases, but applicability and transferability to other conditions are less addressed. It is assumed that a unified solution that can be adapted to different processes and sensors would allow for greater flexibility, applicability, and thus transferability to different applications. To enable a flexible and intervention-independent system, this work proposes a concept for an adaptable situation recognition system. The system consists of four layers with several modular components for different functionalities. The feasibility is demonstrated via prototypical implementation and functional evaluation of a first basic framework prototype. Further development goal is the stepwise extension of the prototype.
The focus of the developed maturity model was set on processes. The concept of the widespread CMM and its practices has been transferred to the perioperative domain and the concept of the new maturity model. Additional optimization goals and technological as well as networking-specific aspects enable a process- and object-focused view of the maturity model in order to ensure broad coverage of different subareas. The evaluation showed that the model is applicable to the perioperative field. Adjustments and extensions of the maturity model are future steps to improve the rating and classification of the new maturity model.