Frequency of errors in the transfer of treatment parameters from the treatment planning system to the oncology information system in a multi‐vendor environment. Issue 4 (16th December 2022)

• Record Type: Journal Article
• Authors: Donahue, William P.; Draeger, Emily; Han, Dae Yup; Chen, Zhe
• Is Part Of: Journal of applied clinical medical physics. Volume 24:Issue 4(2023)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2022-12-16
• Subjects: data transfer -- initial plan check; Medical physics -- Periodicals; Clinical medicine -- Periodicals; Health Physics; Clinical Medicine; Electronic journals; Periodicals; Periodicals; Fulltext; Internet Resources; 610.153
• DOI: 10.1002/acm2.13868
• Languages: English
• ISSNs: 1526-9914

Abstract

Abstract: Background: Technological advancements have made it possible to improve patient outcomes in radiotherapy, sparing both normal tissues and increasing tumour control. However, these advancements have resulted in an increase in the number of software systems used, which each require data inputs to function. For institutions with multiple vendors for their treatment planning systems and oncology information systems, the transfer of data between them is potentially error prone and can lead to treatment errors. Purpose: The goal of this work was to determine the frequency of errors in data transfers between the Varian Eclipse treatment planning system and the Elekta Mosaiq oncology information system. Methods: An in‐house program was used to quantify the number of errors for 2700 unique plans over an 8‐month period. Using this information, the frequency of the errors were calculated. A risk priority number was calculated using the calculated frequencies to determine the impact on the clinic. Results: The most common errors discovered were backup timer settings (10.7%), Field label (8.5%), DRR associations (3.3%), imaging field types (3.1%), dose rate (1%), Field Id (0.8%), imaging isocenter (0.7% and SSD (0.7%). Based on the risk priority numbers, the DRR association error was ranked as having the highest potential impact on the patient. Conclusions: The results of the work show that the most effort should be focused on checking the manual steps performed in the transfer process, while items that are imported directly from DICOM‐RT without modification are highly likely to be transferred accurately. The data can be used to help guide the implementation of future automated tools and process improvement in the clinic.