Click here to


Are you sure ?

Yes, do it No, cancel

Development of An Independent Patient Data Validation Approach for Large Scale Radiotherapy Data Migration

R Khan*, Y Wu , B Bottani , B Sun , S Mutic , C Alexander , D Bollinger , L Santanam , Washington University School of Medicine, St Louis, MO


(Sunday, 7/29/2018) 3:00 PM - 6:00 PM

Room: Exhibit Hall

Purpose: Clinical databases are an integral part of radiation oncology. Large scale data migration from one database to another is a complex process. The validation of data integrity may end up as medical physicist responsibility. The main objective of this work is to present a practical, systematic approach to validate data migrated across two databases.

Methods: Clinical radiotherapy data including patient demographics, documents, treatment fields, radiation doses, and patient schedules were transferred from four separate Sources -A,B,C,D (Mosaiqᵀᴹ (Elekta,Stockholm) to single Target (Ariaᵀᴹ,Varian,CA). Though, both radiotherapy patient management systems are built upon Microsoft SQL language, field mapping across two is not a 1-1 relationship. This may lead to record loss, data misinterpretation, or erroneous transfer to target database. We designed and implemented a multi-pronged approach to ensure data integrity in Target. This includes three separate validations: go live partial validation, complete automatic algorithmic validation, and manual verification of random patient data from all four source databases. For full automated verification, an in-house database comparator algorithm was developed using Microsoft SQL. A manual final validation was done for ~2.7% of all patients.

Results: Around 400 on treatment patient records were critically validated both manually and automatically prior to treating the patients for the first time during the go-live with new system. For total of 54598 patients from all Sources full automatic algorithmic validation was done. Finally, 1500 patients both current and historical patients randomly selected across years 2004-2017, therapy equipment, techniques, modalities and all four sources were manually checked. Through, this approach, we independently verified existence of patients across two SQL based databases observed. About 5-10 % of manually check patients had delivered dose verification issues due to different field interpretation across platforms.

Conclusion: We have designed and implemented a novel multistep approach to clinical database validation transferred for multiple sources.


PACS, Quality Control


IM- Dataset analysis/biomathematics: Informatics

Contact Email