# Use of Process Modelling for Optimization of Molecular Tumor Boards
## 4 Discussion  
Here, we created an optimized version of the process of an entire MTB at the UCCH based on the shortcomings of the current process using the graphical representation standard BPMN. Our core aim was to increase the efficiency of the MTB physician by introducing improved software support and automation. The performed workflow analysis revealed a high degree of inefficiency and disorganization for the MTB physician. The entire process of preparing the MTB report as well as the subsequent tumor documentation are currently performed entirely by the physician alone. Variants of the current diagnosis are typed manually into both the MTB report and the GTDS, increasing the likelihood of transfer errors. Without an administration software in place, MTB patients need to be tracked manually, tying up valuable resources of the MTB physician. The envisaged automation of variant calling, data integration, and quality control using the MIRACUM Pipeline, and the variant annotation by the KC will increase efficiency and are essential to scaling up the process of personalized treatment recommendations in oncology. Since the molecular diagnosis is automatically transferred to the MTB report and GTDS in the optimized process, genetic variations no longer need to be typed in manually. Furthermore, the MTB software tracks all patients who are to receive a personalized therapy recommendation. Therefore, the optimized MTB process will improve patient safety, the reproducibility of the process, and provide a more accurate interpretation of the molecular data. In addition, it will lead to a significant increase in efficiency for the MTB physician, thus optimizing costs for the healthcare system. The process of workflow visualization was complex and challenging. We therefore chose the SOA using BPMN as different studies showed a reduction of costs, IT infrastructure integration, and better business alignment with IT upon the implementation of SOA in the industry [18]. Although SOA has been slow in making its way into healthcare, it is now widely and successfully used in clinical decision support [12]. For personalized medicine, however, there is no published data on the benefits of SOA. Additionally, the BPMN standard for business process modelling that we used is still only rarely used in healthcare, which can be attributed to difficulties in its user-centric design [12], as every pool of a lane in BPMN needs to include a user (see Methods section). Having many different users within a process can make it challenging to represent especially larger processes. We solved this problem by splitting the overall process into different sub-processes, which were displayed in separate pools. This demonstrates the suitability of BPMN to represent a complex healthcare process. The accuracy of the chosen representation enabled us to identify the weaknesses of the current process and to target them for optimization. The BPMN process provided a consistent visual representation of all stakeholders throughout the project cycle, facilitating communication between IT staff and physicians, thus supporting interdisciplinary coordination. There were several challenges which the use of BPMN helped to overcome. For one, the technical challenges of the project included the use of several different networks and IT systems. As patient data had to be documented with the highest data protection standards while having to access external research databases, different IT systems had to be used in different networks. Moreover, interoperability and the optimal embedding of IT solutions into the process was of utmost importance. Furthermore, due to the scope constraints of the project, the novel structured documentation needed to be performed outside the hospital information system, creating the need for a separate documentation software (MTB-Software). Another major advantage of process visualization using BPMN is the quick and effective adaptability of the process to changing conditions, in line with the fast advances in the field of personalized oncology.