Electronic Support for Retrospective Analysis in the Field of Radiation Oncology: Proof of Principle Using an Example of Fractionated Stereotactic Radiotherapy of 251 Meningioma Patients - Rutzner, Sandra; Fietkau, Rainer; Ganslandt, Thomas; Prokosch, Hans-Ulrich; Lubgan, Dorota (Frontiers in Oncology, 2017)
Introduction: The purpose of this study is to verify the possible benefit of a clinical data warehouse (DWH) for retrospective analysis in the field of radiation oncology. Material and methods: We manually and electronically (using DWH) evaluated demographic-, radiotherapy- and outcome data from 251 meningioma patients, who were irradiated from January 2002 until January 2015 at the department of Radiation Oncology of the Erlangen University Hospital. Furthermore, we linked the Oncology-Information-System (OIS) MOSAIQ® to the DWH in order to gain access to irradiation data. We compared the manual and electronic data retrieval method in terms of congruence of data, corresponding time and personal (physician, physicist, scientific associate) requirements. Results: The electronically supported data retrieval (DWH) showed an average of 93.9% correct data and significantly (p=0.009) better result compared to manual data retrieval (91.2%). Utilizing a DWH enables the user to replace large amounts of manual activities (668 hours), offers the ability to significantly reduce data collection time and labour demand (35 hours), while simultaneously improving data quality. In our case work time for manually data retrieval was 637 hours for the scientific assistant, 26 h for the medical physicist and 5 hours for the physician (total 668 hours). Conclusion: Our study shows that a DWH is particularly useful for retrospective analysis in the radiation oncology field. Routine clinical data for a large patient group can be provided ready for analysis to the scientist and data collection time can be significantly reduced. Furthermore, linking multiple data sources in a DWH offers the ability to improve data quality for retrospective analysis and future research can be simplified.