gms | German Medical Science

22. Deutscher Kongress für Versorgungsforschung

Deutsches Netzwerk Versorgungsforschung e. V.

04.10. - 06.10.2023, Berlin

A database for oncological research and quality assurance: Implementation and first experiences at a University Clinical Cancer Registry

Meeting Abstract

  • Anna Saibold - Department of Information Technology, University Hospital Regensburg, Regensburg, Germany; Bavarian Cancer Research Center (BZKF), Regensburg, Germany; Center for Clinical Studies, University Hospital Regensburg, Regensburg, Germany
  • Julia Maurer - Bavarian Cancer Research Center (BZKF), Regensburg, Germany; University Cancer Center Regensburg, University Hospital Regensburg, Regensburg, Germany
  • Michael Koller - Center for Clinical Studies, University Hospital Regensburg, Regensburg, Germany
  • Karolina Müller - Center for Clinical Studies, University Hospital Regensburg, Regensburg, Germany
  • Oliver Kölbl - Department of Radiation Oncology, University Hospital Regensburg, Regensburg, Germany
  • Veronika Vielsmeier - Department of Otorhinolaryngology, Head and Neck Surgery, University Hospital Regensburg, Regensburg, Germany
  • Tobias Pukrop - Department of Internal Medicine 3, University Hospital Regensburg, Regensburg, Germany
  • Oliver Spies - Department of Information Technology, University Hospital Regensburg, Regensburg, Germany
  • Vivien Eilers - Department of Information Technology, University Hospital Regensburg, Regensburg, Germany
  • Cathleen Brese - University Cancer Center Regensburg, University Hospital Regensburg, Regensburg, Germany
  • Denise Amann - University Cancer Center Regensburg, University Hospital Regensburg, Regensburg, Germany

22. Deutscher Kongress für Versorgungsforschung (DKVF). Berlin, 04.-06.10.2023. Düsseldorf: German Medical Science GMS Publishing House; 2023. Doc23dkvf044

doi: 10.3205/23dkvf044, urn:nbn:de:0183-23dkvf0447

Published: October 2, 2023

© 2023 Saibold et al.
This is an Open Access article distributed under the terms of the Creative Commons Attribution 4.0 License. See license information at http://creativecommons.org/licenses/by/4.0/.


Outline

Text

Background and current research: Basic requirements for an oncological data register are fulfilling legal and certification purposes. Additionally, real-world data for cancer research and treatment as well as the interoperability of oncological data are of rising importance.

Scientific question, objectives, hypothesis: The necessity to organize and manage the mentioned data in an appropriate database and software, led to the decision to establish a University Clinical Cancer Registry at a University hospital. The paper summarizes recommendations for implementation of clinical data bases in similar settings with interdisciplinary responsibilities organized in working groups based on the gathered experiences.

Method: All required steps were organized in a project plan. First step in implementing an oncological data register was the acquisition of an appropriate tumor documentation and database software. Therefore, an evaluation matrix was designed by a multidisciplinary group of experts. Potential database software was identified and rated according to the established matrix as well as additional relevant aspects. In the second step, the selected software was implemented and digitally available data was migrated after an adaptation and verification process. Parallel, a uniformed process for handling rising research questions and statistical support was established. In the final step, the mentioned implementation and processes were evaluated in two exemplary use cases with focus on clinical wide analyses to current relevant scientific topics.

Results: After a testing phase through various user groups, one product was considered most suited to build up an oncological data repository, especially due to the opportunity for adjustability to support research and treatment. The newly added and the successfully migrated data can be used for certification and research purposes. Three documents were introduced in the clinical workflow for data analysis: proposal for data extraction, procedural instructions, and statistical training material. First experiences with the data extraction process in form of use cases showed that the workflow and the underlying documents are feasible. Furthermore, scientists profited from the transparency of the data extraction process and the statistical support.

Discussion: Through description of the process, insights can be gained as guidance for implementations of clinical data bases in similar settings. Based on our experience, we can highly recommend the approach mentioned before. Especially organizing the necessary steps in form of a project plan in connection with the evaluation matrix were extremely helpful. The most time-consuming process was the data migration from an existing, outdated data base to our new database that is in compliance with the current regulatory guidelines. Finally, it is very important to implement use cases and a statistical evaluation concept into the overall project plan from the very beginning.

Implication for research: An oncological data register can be a powerful tool for the legally required cancer registration, the certification of medical centers as well as registry-based oncological research.

Funding: Other funding; BZKF (Bayerisches Zentrum für Krebsforschung), Regensburg, Germany