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Advanced Detection of Potential Errors During Patient Treatment Planning

J Liang

D Lack , J Liang*, L Benedetti , C Knill , D Yan , Beaumont Healty System, Royal Oak, MI


TU-FG-702-3 (Tuesday, August 1, 2017) 1:45 PM - 3:45 PM Room: 702

Purpose: Data errors caught late in the planning process require time to correct, resulting in treatment delays of up to 1 weeks’ time. In this work we identify causes of potential data errors in the planning process and develop a software tool that automatically detects these errors in advance.

Methods: There are 2 major categories of data errors which require user intervention. These can be classified as 1) data transfer errors, 2) TPS errors. Using root analyses, the causes of these potential data errors were determined. For data transfer errors, the main causes identified were: incorrect patient identifier entry, image slice missing from dataset, and incorrect dicom tag generated at CT console. For TPS errors, the main causes identified were: incorrect CT-density table application and image file imported to incorrect patient. This information was incorporated into a windows-based software tool developed using SQL and FTP services that is scheduled to run daily. The SQL service accesses the unix-based TPS’s Postgres database and windows-based Mosaiq MSSQL databases, and the read-only FTP service scans the TPS unix file system for potential data errors. Detected errors are automatically sent to a physicist for review and once confirmed, the responsible clinician is notified to correct the error and educated to prevent errors in the future.

Results: The software tool has been running automatically since 2015. In 2016, 84 planning errors were detected within which the most frequent errors were the incorrect patient identifier entry (35 occurrences) followed by the incorrect CT-density table application (17 occurrences) and image slice missing (16 occurrences).

Conclusion: The planning error tracking tool successfully detects errors during the planning process, improving the accuracy and efficiency of clinical treatment. This important QA tool will focus our efforts on the areas in the clinical treatment planning process that need the most improvement.

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