Although large volumes of information are entered into our electronic health care records, radiation oncology information systems and treatment planning systems on a daily basis, the goal of extracting and using this big data has been slow to emerge. Development of strategies to meet this goal is aided by examining issues with a data farming instead of a data mining conceptualization. Using this model, a vision of key data elements, clinical process changes, technology issues and solutions, and role for professional societies is presented. With a better view of technology, process and standardization factors, definition and prioritization of efforts can be more effectively directed.

Proper quality assurance (QA) of the radiotherapy process can be time-consuming and expensive. Many QA efforts, such as data export and import, are inefficient when done by humans. Additionally, humans can be unreliable, lose attention, and fail to complete critical steps that are required for smooth operations. In our group we have sought to break down the QA tasks into separate steps and to automate those steps that are better done by software running autonomously or at the instigation of a human. A team of medical physicists and software engineers worked together to identify opportunities to streamline and automate QA. Development efforts follow a formal cycle of writing software requirements, developing software, testing and commissioning. The clinical release process is separated into clinical evaluation testing, training, and finally clinical release. We have improved six processes related to QA and safety. Steps that were previously performed by humans have been automated or streamlined to increase first-time quality, reduce time spent by humans doing low-level tasks, and expedite QA tests. Much of the gains were had by automating data transfer, implementing computer-based checking and automation of systems with an event-driven framework. These coordinated efforts by software engineers and clinical physicists have resulted in speed improvements in expediting patient-sensitive QA tests.

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Purpose: To enhance patient safety and radiation therapy quality assurance by implementing an immediate computer‐based audit of radiation therapy treatment record. Provide an automatic second check of the RT record in a paperless environment. Replace some aspects of weekly physics chart checks with a computer‐based audit of the treatment. Method: A software agent receives signals from a system we have developed, EventNet, when sentinel events occur in the TMS. Audits are triggered when a “treatment canceled”, and one of the many “treatment complete” signals are received. The treatment canceled audit assumes the patient treatment was canceled and verifies that no treatment happened. The treatment completed audit assumes that a treatment occurred and checks the treatment history parameters and dose summary against the scheduled plans, session, daily and total doses. The agent extracts the plan(s) and the day's treatment history from the TMS with a DICOM query and sends that data to a web service that compares the history against the plan. If the audit succeeds, the agent quietly adds an entry to a log file. When it fails the agent alerts staff via pager, email, or SMS message. Results: The agent is able to catch events from the TMS and trigger one of two audit processes. Basic audits of the treatment histories works as designed. Intentional variation in treatment parameters in test cases are caught and trigger the immediate alert. Conclusion: Immediate audit of the RT record is better than waiting for weekly physics chart check to verify plan parameters. Rather than have a physicist seek out variations in treatments by checking every treated parameter, a software agent can provide a basic audit and alert the physicist if needed. This brings more focus on patient treatments that require oversight and could free up valuable time for other QA tasks.

Purpose: Quality assurance is an essential task in radiotherapy that often requires many manual tasks. We investigate the use of an event driven framework in conjunction with software agents to automate QA and eliminate wait times. Methods: An in house developed subscription‐publication service, EventNet, was added to the Aria OIS to be a message broker for critical events occurring in the OIS and software agents. Software agents operate without user intervention and perform critical QA steps. The results of the QA are documented and the resulting event is generated and passed back to EventNet. Users can subscribe to those events and receive messages based on custom filters designed to send passing or failing results to physicists or dosimetrists. Agents were developed to expedite the following QA tasks: Plan Revision, Plan 2nd Check, SRS Winston‐Lutz isocenter, Treatment History Audit, Treatment Machine Configuration. Results: Plan approval in the Aria OIS was used as the event trigger for plan revision QA and Plan 2nd check agents. The agents pulled the plan data, executed the prescribed QA, stored the results and updated EventNet for publication. The Winston Lutz agent reduced QA time from 20 minutes to 4 minutes and provided a more accurate quantitative estimate of radiation isocenter. The Treatment Machine Configuration agent automatically reports any changes to the Treatment machine or HDR unit configuration. The agents are reliable, act immediately, and execute each task identically every time. Conclusion: An event driven framework has inverted the data chase in our radiotherapy QA process. Rather than have dosimetrists and physicists push data to QA software and pull results back into the OIS, the software agents perform these steps immediately upon receiving the sentinel events from EventNet. Mr Keranen is an employee of Varian Medical Systems. Dr. Moran's institution receives research support for her effort for a linear accelerator QA project from Varian Medical Systems. Other quality projects involving her effort are funded by Blue Cross Blue Shield of Michigan, Breast Cancer Research Foundation, and the NIH.