TH-E-19A-01: Quality and Safety in Radiation Therapy

Authors


Abstract

Clinical radiotherapy data clearly demonstrate the link between the quality and safety of radiation treatments and the outcome for patients. The medical physicist plays an essential role in this process. To ensure the highest quality treatments, the medical physicist must understand and employ modern quality improvement techniques. This extends well beyond the duties traditionally associated with prescriptive QA measures. This session will review the current best practices for improving quality and safety in radiation therapy.

General elements of quality management will be reviewed including: what makes a good quality management structure, the use of prospective risk analysis such as FMEA, and the use of incident learning. All of these practices are recommended in society-level documents and are incorporated into the new Practice Accreditation program developed by ASTRO. To be effective, however, these techniques must be practical in a resource-limited environment. This session will therefore focus on practical tools such as the newly-released radiation oncology incident learning system, RO-ILS, supported by AAPM and ASTRO.

With these general constructs in mind, a case study will be presented of quality management in an SBRT service. An example FMEA risk assessment will be presented along with incident learning examples including root cause analysis.

As the physicist's role as “quality officer” continues to evolve it will be essential to understand and employ the most effective techniques for quality improvement. This session will provide a concrete overview of the fundamentals in quality and safety.

Learning Objectives:

  • 1.Recognize the essential elements of a good quality management system in radiotherapy.
  • 2.Understand the value of incident learning and the AAPM/ASTRO ROILS incident learning system.
  • 3.Appreciate failure mode and effects analysis as a risk assessment tool and its use in resource-limited environments.
  • 4.Understand the fundamental principles of good error proofing that extends beyond traditional prescriptive QA measures.

Ancillary