Automation of QC/QA process
Automation of QC/QA process
The complexity of the radiotherapy process continues to increase which requires a high level of safety and constant quality monitoring and improvement. During the last decades, the number of quality controls performed both patient and equipment specific has increased enormously. We generate a large amount of data that is too often poorly analysed to redesign Quality Controls or redefine their frequencies. Therefore, as a consequence, performing and analysing routine quality controls takes a lot of working time of Medical Physics staff. Most of the routine QC could be partially or fully automated. Automation should encompass all patient quality controls from treatment planning to delivery as well as the periodic controls on treatment units, imaging systems and treatment planning systems. The benefits of automating QC are not only related to time saving of both personnel and treatment machines but also on the consistency and robustness of the Quality controls. An automated Quality Assurance platform could also help in data sharing (alerts in case data is out of the shared data for that machine), and predictive modelling of equipment break downs or suboptimal treatment plans. Treatment plan evaluation could also be partly automated by the use of automated checklists and automated comparison with standards, again this will improve both the time needed for plan preparation, but also will have a high impact in reduction of errors.
In order to automate most of the QC tests there is a need of integrating information provided by different systems. Therefore, therefore vendors ought to provide stable APIs, and full access to data so that even with changes of versions of the systems automation still works. This is still not the case for major equipment vendors and compromises the potential of automation. The implementation of automation involves a considerable initial investment. Automation may also lead to a loss of flexibility, as any workflow modification may involve revisiting automation codes. Another potential disadvantage of automation is loss of knowledge of the sensitivity and specificity of the different QC tests which could lead to physicists over relaying on automated QA and not understanding the limitations of some tests.
Most departments, due to the scripting opportunity given by major treatment planning systems vendors, have implemented local solutions for automation of their QA processes. At the same time some measurement equipment vendors are providing QA platforms that integrated with measuring equipment, treatment planning systems and linac allow for the automation of QC both in measurements but also on the evaluation. Some examples on these two approaches will be discussed.