Balancing the evolution of radiotherapy quality assurance: in reference to Ford et al.

In February 2007, a special symposium on quality assurance (QA) for radiation therapy, ‘‘Quality Assurance of Radiation Therapy: The Challenges of Advanced Technologies,’’ was held. The 3-day program, which was sponsored jointly by the American Society for Therapeutic Radiology and Oncology (ASTRO), American Association of Physicists in Medicine (AAPM), and National Cancer Institute (NCI), included more than 40 invited speakers from the radiation oncology and industrial engineering/human factor communities. The consensus finding of the symposium was that the current process of developing consensus recommendations for prescriptive QA tests remains valid for many of the devices and software systems used in modern RT, although for some technologies, QA guidance is incomplete or out of date (1). This symposium represented a turning point for the radiation oncology community—namely, the transition from exclusive performance-based QA to process-based QA. This paradigm change has evolved because traditional performance-based QA does not prevent process-based errors (2, 3). The symposium presentations ranged from basic device-centered QA, such as linear accelerator QA (4) to methods for developing a systematic approach to quality improvement that incorporates a series of industrial engineering–based tools. The goal of the new approach is to: improve outcomes, reduce risk and/or improve patient safety, improve throughput, and reduce cost. This approach includes process mapping and process flowcharting, failure modes and effects analysis (FMEA), value stream mapping, and fault tree analysis (FTA) (5, 6). Symposium attendees came away empowered to deploy these new methods in their own clinic. However, it has taken a few years to see manuscripts that detail how an institution applied these methods and the outcome. The delay is for two reasons: radiation oncology departments must still perform the mundane, performance QA and have not been able to slow down to make the transition, and the initial analysis to asses FTAs is time-consuming, although not unmanageable. One such presentation by Ford et al. (7) is presented in this issue. Radiation oncology has already moved beyond performance-based QA. Systematic QA tasks also include review of simulation planning and delivery systems, development and deployment of policies and procedures, continuing education, peer review of plans for therapy, and computerized treatment plans. In addition, departments have setup QA committees that review policies and procedures and review reported errors that have occurred. What has been missing is the comprehensive analysis of steps for a given activity, for which simple procedures cannot explain the individual tasks and personnel roles in enough detail to find possible modes of failure. Hence, the FMEA analysis presented in the Ford paper is timely, especially in light of the proliferation of new procedures and technology. However, processes and procedures for a new technology proves a greater challenge because a history of volatility (including near misses) does not yet exist (8). For example, implementation of record and verify systems has been, in most cases (with proper use), a mechanism to help avoid errors caused by direct transfer of digital information (technical instructions, alignment radiographs). However, its misuse could actually propagate errors (9). The methodology for how a clinic can analyze processes to examine vulnerability by FMEA will be described in a forthcoming report (TG-100) from the AAPM (6). In the meantime, the FMEA analysis of the article presented in this offers gives an outstanding example as how to preempt errors for procedures. As pointed out in the article (7), the authors developed a process map to possessing 269 nodes and identified 127 possible failure modes. This was an enormous undertaking by various staff members. It may not be practical to perform such an analysis for all procedures or clinics. For example, our institution (3) analyzed errors in terms of