Optimizing the analytical value of oncology-related data based on an in-memory analysis layer - MOCCA: The Munich online comprehensive cancer analysis platform.

BACKGROUND: In order to supply information for internal and external audit purposes, tumor documentation software supplying structured information from the associated centers' oncology patients exists in many comprehensive cancer centers. However, the documentation data contents of such systems often remain unused and unknown by most of the sites' clinicians. OBJECTIVE: To improve access to such data for analytical purposes, a pre-rollout of an analysis layer based on the business intelligence software called QlikView has been implemented. This software allows real-time analysis and real-time inspection of the oncology-related data. The system is meant to increase access to the data while simultaneously providing tools for user-friendly real-time analytics. METHODS: The system combines in-memory capabilities (based on the QlikView software) with innovative techniques that compress the complexity of the data, consequently improving its readability, as well as its accessibility for designated end users. Aside from the technical and conceptual part, the software's implementation necessitated a complex system of permission and governance. RESULTS: A continuously running system including daily updates with a user-friendly web interface and a real-time usage was established. This paper introduces its main components and major design ideas. A commented video summarizing and presenting the work can be found within the multimedia appendix. CONCLUSIONS: The system has been well received by a focus group of physicians within an initial pre-rollout. Aside from improving data transparency, the system's main benefits are its quality and process control capabilities, knowledge discovery, and hypothesis generation. Limitations such as run time, governance or misinterpretation of data are considered. CLINICALTRIAL: not applicable.