Risk factors for near-miss events and safety incidents in pediatric radiation therapy

Quality management in radiotherapy treatment delivery

Radiation Oncology continues to rely on accurate delivery of radiation, in particular where patients can benefit from more modulated and hypofractioned treatments that can deliver higher dose to the target while optimising dose to normal structures. These deliveries are more complex, and the treatment units are more computerised, leading to a re-evaluation of quality assurance (QA) to test a larger range of options with more stringent criteria without becoming too time and resource consuming. This review explores how modern approaches of risk management and automation can be used to develop and maintain an effective and efficient QA programme. It considers various tools to control and guide radiation delivery including image guidance and motion management. Links with typical maintenance and repair activities are discussed, as well as patient-specific quality control activities. It is demonstrated that a quality management programme applied to treatment delivery can have an impact on individual patients but also on the quality of treatment techniques and future planning. Developing and customising a QA programme for treatment delivery is an important part of radiotherapy. Using modern multidisciplinary approaches can make this also a useful tool for department management.

Automatic couch position calculation using eclipse scripting for external beam radiotherapy

PURPOSE

The treatment couch position of a patient in external beam radiation therapy (EBRT) is usually acquired during initial treatment setup. This procedure has shown potential failure modes leading to near misses and adverse events in radiation treatment. This study aims to develop a method to automatically determine the couch position before setting up a patient for initial treatment.

METHODS

The Qfix couch-tops (kVue and DoseMax) have embedded reference marks (BBs) indicating its index levels and couch centerline. With the ESAPI, a C# script was programmed to automatically find the couch-top and embedded BBs in the planning CT and derive the treatment couch position according to treatment isocenter of a plan. Couch positions of EBRT plans with the kVue couch-top and SBRT plans using the DoseMax were calculated using the script. The calculation was evaluated by comparing calculated positions with couch coordinates captured during the initial treatment setup after image guidance. The calculations were further compared with daily treatment couch positions post image-guided adjustment for each treatment fraction.

RESULTS

For plans using the kVue couch-top for various treatment sites, the median (5-95 percentiles) differences between calculated and captured couch positions were 0.1 (-0.2 - 0.9), 0.5 (-1.1-2.0), 0.10 (-1.3-1.3) cm in the vertical, longitudinal, and lateral direction respectively. For the DoseMax couch-top, the median differences were 0.1 (-0.2-0.7), 0.2 (-0.3-1.1), and 0.2 (-0.7-0.9) cm in respective direction. The calculated positions were within 1 and 2 cm from the mean fraction positions for 95% patients on DoseMax and kVue couch-top respectively.

CONCLUSIONS

A method that automatically and accurately calculates treatment couch position from simulation CT was implemented in Varian Eclipse for Qfix couch-tops. This technique increases the efficiency of patient setup and enhances patient safety by reducing the risks of positioning errors.

Exploring the Potential Use of Near-Miss Information to Improve Construction Safety Performance

Construction project management usually has a high risk of safety-related accidents. An opportunity to proactively improve safety performance is with near-miss information, which is regarded as free lessons for safety management. The research status and practice; however, presents a lack of comprehensive understanding on what near-miss information means within the context of construction safety management. The objective of this study is to fill in this gap. The main findings enrich the comprehensive understanding of the near-miss definition, the near-miss causation model, and the process of near-miss management. Considering that near-misses are more tacit and obscure than accidents, the process for near-miss management involves eight stages: discovery, reporting, identification, prioritization, causal analysis, solution, dissemination, and evaluation. The first three stages aim to make near-misses explicit. The other five are adopted to better manage near-miss information, compiled in a well-designed near-miss database (NMDB). Finally, a case study was conducted to show how near-miss information can be utilized to assist in construction safety management. The main potential contributions here are twofold. Firstly, corresponding findings provide a knowledge framework of near-miss information for construction safety researchers who can go on to further study near-miss management. Secondly, the proposed framework contributes to the guidance and encouragement of near-miss practices on construction sites.