Improving patient safety and workflow efficiency with standardized pretreatment radiation therapist chart reviews.

PURPOSE: Radiation therapists play a critical role in ensuring patient safety; however, they are sometimes given insufficient time to perform quality assurance (QA) of a patient's treatment chart and documentation before the start of treatment. In this work, we show the benefits of introducing a formal therapist prestart QA checklist, completed in a quiet space well in advance of treatment, into our workflow. METHODS AND MATERIALS: A therapist prestart QA checklist was created by analyzing in-house variance reports and treatment unit delays over 6 months. Therapists were then given dedicated time and workspace to perform their checks within the dosimetry office of our department. The effectiveness of the checklist was quantified by recording the percentage of charts that underwent QA before treatment, the percentage of charts with errors needing intervention, and treatment unit delays during a nearly 2-year period. The frequency and types of errors found by the prestart QA were also recorded. RESULTS: Through the use of therapist prestart QA, instances of treatment unit delays were reduced by up to a factor of 9 during the first year of the program. At the outset of this new initiative, nearly 40% of charts had errors requiring intervention, with the majority being scheduling related. With upstream workflow changes and automation, this was reduced over the period of a year to about 10%. CONCLUSIONS: The number of treatment unit delays was dramatically reduced by using a formal therapist prestart QA checklist completed well in advance of treatment. The data collected via the checklist continue to be used for further quality improvement efforts.

Failure mode and effects analysis in a dual-product microsphere brachytherapy environment.

PURPOSE: We performed a failure mode and effects analysis (FMEA) during the addition of a new microspheres product into our existing microsphere brachytherapy program to identify areas for safety improvements. METHODS AND MATERIALS: A diverse group of team members from the microsphere program participated in the project to create a process map, identify and score failure modes, and discuss programmatic changes to address the highest ranking items. We developed custom severity ranking scales for staff- and institution-related failure modes to encompass possible risks that may exist outside of patient-based effects. RESULTS: Between both types of microsphere products, 173 failure mode/effect pairs were identified: 90 for patients, 35 for staff, and 48 for the institution. The SIR-Spheres program was ranked separately from the TheraSphere program because of significant differences in workflow during dose calculation, preparation, and delivery. High-ranking failure modes in each category were addressed with programmatic changes. CONCLUSIONS: The FMEA aided in identifying potential risk factors in our microsphere program and allowed a theoretically safer and more efficient design of the workflow and quality assurance for both our new SIR-Spheres program and our existing TheraSphere program. As new guidelines are made available, and our experience with the SIR-Spheres program increases, we will update the FMEA as an efficient starting point for future improvements.

Practical implementation of failure mode and effects analysis for safety and efficiency in stereotactic radiosurgery.

PURPOSE: To improve the safety and efficiency of a new stereotactic radiosurgery program with the application of failure mode and effects analysis (FMEA) performed by a multidisciplinary team of health care professionals. METHODS AND MATERIALS: Representatives included physicists, therapists, dosimetrists, oncologists, and administrators. A detailed process tree was created from an initial high-level process tree to facilitate the identification of possible failure modes. Group members were asked to determine failure modes that they considered to be the highest risk before scoring failure modes. Risk priority numbers (RPNs) were determined by each group member individually and then averaged. RESULTS: A total of 99 failure modes were identified. The 5 failure modes with an RPN above 150 were further analyzed to attempt to reduce these RPNs. Only 1 of the initial items that the group presumed to be high-risk (magnetic resonance imaging laterality reversed) was ranked in these top 5 items. New process controls were put in place to reduce the severity, occurrence, and detectability scores for all of the top 5 failure modes. CONCLUSIONS: FMEA is a valuable team activity that can assist in the creation or restructuring of a quality assurance program with the aim of improved safety, quality, and efficiency. Performing the FMEA helped group members to see how they fit into the bigger picture of the program, and it served to reduce biases and preconceived notions about which elements of the program were the riskiest.