Optimizing the Analytical Value of Oncology-Related Data Based on an In-Memory Analysis Layer: Development and Assessment of the Munich Online Comprehensive Cancer Analysis Platform.

Daniel Nasseh,Nicole Erickson,Ranko Cadenovic,Sophie Schneiderbauer,Theres Fey,Volker Heinemann,Michael Mueller,Claus Belka,Laurence Buysse,Sebastian Marschner,Karsten Kortuem,Michael Lange,Diana Schweizer,Maximilian Niyazi

doi:10.2196/16533

Abstract

BackgroundMany comprehensive cancer centers incorporate tumor documentation software supplying structured information from the associated centers’ oncology patients for internal and external audit purposes. However, much of the documentation data included in these systems often remain unused and unknown by most of the clinicians at the sites.ObjectiveTo improve access to such data for analytical purposes, a prerollout of an analysis layer based on the business intelligence software QlikView was implemented. This software allows for the real-time analysis and inspection of oncology-related data. The system is meant to increase access to the data while simultaneously providing tools for user-friendly real-time analytics.MethodsThe system combines in-memory capabilities (based on 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 components, the software’s implementation necessitated a complex system of permission and governance.ResultsA continuously running system including daily updates with a user-friendly Web interface and 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.ConclusionsThe system has been well-received by a focus group of physicians within an initial prerollout. 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.

Highlights

In recent years, hospitals have been gradually transitioning from paper-based toward electronic documentation systems
To provide general access to the data, the first step was to set up a server within the clinical intranet, which continuously runs an instance of the QlikView Enterprise Edition
QlikView was chosen because it comes with a toolbox, enabling the construction of the contents that can be saved within a proprietary data container (*.qvw file) [9]

Summary

Introduction

Hospitals have been gradually transitioning from paper-based toward electronic documentation systems. Objective: To improve access to such data for analytical purposes, a prerollout of an analysis layer based on the business intelligence software QlikView was implemented. This software allows for the real-time analysis and inspection of oncology-related data. Methods: The system combines in-memory capabilities (based on QlikView software) with innovative techniques that compress the complexity of the data, improving its readability as well as its accessibility for designated end users. 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

Objectives

Methods

Results

Discussion

Conclusion