Selective de-implementation of routine in vivo dosimetry.

As cone-beam computed tomography (CBCT) has become the localization method for a majority of cases, the indications for diode-based confirmation of accurate patient set-up and treatment are now limited and must be balanced between proper resource allocation and optimizing efficiency without compromising safety. We undertook a de-implementation quality improvement project to discontinue routine diode use in non-intensity modulated radiotherapy (IMRT) cases in favor of tailored selection of scenarios where diodes may be useful. After analysis of safety reports from the last 5 years, literature review, and stakeholder discussions, our safety and quality (SAQ) committee introduced a recommendation to limit diode use to specific scenarios in which in vivo verification may add value to standard quality assurance (QA) processes. To assess changes in patterns of use, we reviewed diode use by clinical indication 4 months prior and after the implementation of the revised policy, which includes use of diodes for: 3D conformal photon fields set up without CBCT; total body irradiation (TBI); electron beams; cardiac devices within 10 cm of the treatment field; and unique scenarios on a case-by-case basis. We identified 4459 prescriptions and 1038 unique instances of diode use across five clinical sites from 5/2021 to 1/2022. After implementation of the revised policy, we observed an overall decrease in diode use from 32% to 13.2%, with a precipitous drop in 3D cases utilizing CBCT (from 23.2% to 4%), while maintaining diode utilization in the 5 selected scenarios including 100% of TBI and electron cases. By identifying specific indications for diode use and creating a user-friendly platform for case selection, we have successfully de-implemented routine diode use in favor of a selective process that identifies cases where the diode is important for patient safety. In doing so, we have streamlined patient care and decreased cost without compromising patient safety.

Adoption of an incident learning system in a regionally expanding academic radiation oncology department.

AIM AND BACKGROUND: We describe a successful implementation of a departmental incident learning system (ILS) across a regionally expanding academic radiation oncology department, dovetailing with a structured integration of the safety and quality program across clinical sites. MATERIALS AND METHODS M: Over 6 years between 2011 and 2017, a long-standing departmental ILS was deployed to 4 clinical locations beyond the primary clinical location where it had been established. We queried all events reported to the ILS during this period and analyzed trends in reporting by clinical site. The chi-square test was used to determine whether differences over time in the rate of reporting were statistically significant. We describe a synchronous development of a common safety and quality program over the same period. RESULTS: There was an overall increase in the number of event reports from each location over the time period from 2011 to 2017. The percentage increase in reported events from the first year of implementation to 2017 was 457% in site 1, 166.7% in site 2, 194.3% in site 3, 1025% in site 4, and 633.3% in site 5, with an overall increase of 677.7%. A statistically significant increase in the rate of reporting was seen from the first year of implementation to 2017 (p < 0.001 for all sites). CONCLUSIONS: We observed significant increases in event reporting over a 6-year period across 5 regional sites within a large academic radiation oncology department, during which time we expanded and enhanced our safety and quality program, including regional integration. Implementing an ILS and structuring a safety and quality program together result in the successful integration of the ILS into existing departmental infrastructure.

From Alpha to Omicron: A Radiation Oncology Network's Biocontainment-Based COVID-19 Experience.

Purpose: To develop the safest possible environment for treating urgent patients with COVID-19 requiring radiation, we describe the unique construction of negative air pressure computed tomography simulator and linear accelerator treatment vaults in addition to screening, delay, and treatment protocols and their evolution over the course of the COVID-19 pandemic. Methods and Materials: Construction of large high-efficiency particulate air filter air-flow systems into existing ductwork in computed tomography simulator rooms and photon and proton treatment vaults was completed to create negative-pressure rooms. An asymptomatic COVID-19 screening protocol was implemented for all patients before initiation of treatment. Patients could undergo simulation and/or treatment in the biocontainment environments according to a predefined priority scale and protocol. Patients treated under the COVID-19 protocol from June 2020 to January 2022 were retrospectively reviewed. Results: Negative air-flow environments were created across a regional network, including a multi-gantry proton therapy unit. In total, 6525 patients were treated from June 2020 through January 2022 across 5 separate centers. The majority of patients with COVID-19 had radiation treatment deferred when deemed safe. A total of 42 patients with COVID-19, who were at highest risk of an adverse outcome should there be a radiation delay, were treated under the COVID-19 biocontainment protocol in contrast to those who were placed on treatment break. For 61.9% of patients, these safety measures mitigated an extended break during treatment. The majority of patients (64.3%) were treated with curative intent. The median number of biocontainment sessions required by each patient was 6 (range, 1-15) before COVID-19 clearance and resumption of treatment in a normal air-flow environment. Conclusions: Constructing negative-pressure environments and developing a COVID-19 biocontainment treatment protocol allowed for the safe treatment of urgent radiation oncology patients with COVID-19 within our department and strengthens future biopreparedness. These biocontainment units set a high standard of safety in radiation oncology during the current or for any future infectious outbreak.

Patterns of Incident Reporting Across Clinical Sites in a Regionally Expanding Academic Radiation Oncology Department.

PURPOSE: We evaluated patterns of event reporting across five clinical locations within an academic radiation oncology department, with the goal of better understanding variability across sites. METHODS AND MATERIALS: We analyzed 1,351 events reported to a departmental incident learning system over 1 calendar year across the five locations with respect to volume of events, event type, process map location of origin and detection, and event reporter. RESULTS: We found marked variability in reporting patterns, including reporting rate, event type, event severity, event location of origin and detection within the departmental process map, and discipline of event reporters. These differences relate both to variability in process and workflow (reflected by frequency of specific workflow events at each site) and in reporting culture (reflected by volume or rate of event reporting, and discipline of event reporter). CONCLUSIONS: These data highlight the variability in reporting culture even within a single department, and therefore the need to tailor and individualize safety and quality programs to the unique clinical site, with the long-term goal of achieving a common culture of safety while supporting unique processes at individual locations. This work also raises concern about extrapolating single-institution incident learning system results without understanding the unique workflow and culture of clinical sites.

Real-time management of incident learning reports in a radiation oncology department.

PURPOSE: The optimal approach to managing incident learning system (ILS) reports remains unclear. Here, we describe our experience with prospective coding of events reported to the ILS with comparisons of risk scores on the basis of event type and process map location. METHODS AND MATERIALS: Reported events were coded by type, origin, and method of discovery. Events were given a risk priority number (RPN) and near-miss risk index (NMRI) score. We compared workflow versus near-miss events with respect to origin and detection in the process map and by risk scores. A χ2 test was used to compare the differences between workflow and near-miss events. A comparison of RPN scores was done by independent t test. RESULTS: During 2016, 1351 events were reported. Of these events, 1300 (96.2%) were workflow and 51 (3.8%) near-miss events. Workflow events were more likely to both originate (1041 of 1300 events; 81.2%) compared with near-miss events (31 of 51 events; 62.7%; P = .005) and be detected in pre-treatment (997 of 1300 events; 76.7%) compared with near-miss events (24 of 51 events; 47%; P < .001). Average occurrence (scale: 1-10) was 6.14 for workflow versus 3.33 for near-miss events (P < .001), average severity was 2.94 versus 7.35 (P < .001), and average detectability was 1.33 versus 4.67 (P < .001). Mean overall RPN was 22.4 for workflow versus 108.4 for near-miss events (P = .07) and mean NMRI was 1.16 versus 3.19, respectively. Events that originated and were detected in treatment delivery had the greatest mean overall RPN (38.2 and 32.1, respectively) and NMRI scores (1.62 and 1.6, respectively). CONCLUSIONS: Our experience demonstrates that workflow event reports are far more common than near-misses and that near-miss events are more likely to both originate and be discovered in later treatment phases. The frequency of workflow reports highlights the imperative need for safety and operational teams to work collaboratively to maximize the benefit of ILS. We suggest a potential utility of the RPN system to guide mitigation strategies for future near-miss events.

Interventional Radiation Oncology (IRO): Transition of a magnetic resonance simulator to a brachytherapy suite.

PURPOSE: As a core component of a new gynecologic cancer radiation program, we envisioned, structured, and implemented a novel Interventional Radiation Oncology (IRO) unit and magnetic resonance (MR)-brachytherapy environment in an existing MR simulator. METHODS AND MATERIALS: We describe the external and internal processes required over a 6-8 month time frame to develop a clinical and research program for gynecologic brachytherapy and to successfully convert an MR simulator into an IRO unit. RESULTS: Support of the institution and department resulted in conversion of an MR simulator to a procedural suite. Development of the MR gynecologic brachytherapy program required novel equipment, staffing, infrastructural development, and cooperative team development with anesthetists, nurses, therapists, physicists, and physicians to ensure a safe and functional environment. Creation of a separate IRO unit permitted a novel billing structure. CONCLUSIONS: The creation of an MR-brachytherapy environment in an MR simulator is feasible. Developing infrastructure includes several collaborative elements. Unique to the field of radiation oncology, formalizing the space as an Interventional Radiation Oncology unit permits a sustainable financial structure.

Identifying Predictive Factors for Incident Reports in Patients Receiving Radiation Therapy.

PURPOSE: To describe radiation therapy cases during which voluntary incident reporting occurred; and identify patient- or treatment-specific factors that place patients at higher risk for incidents. METHODS AND MATERIALS: We used our institution's incident learning system to build a database of patients with incident reports filed between January 2011 and December 2013. Patient- and treatment-specific data were reviewed for all patients with reported incidents, which were classified by step in the process and root cause. A control group of patients without events was generated for comparison. Summary statistics, likelihood ratios, and mixed-effect logistic regression models were used for group comparisons. RESULTS: The incident and control groups comprised 794 and 499 patients, respectively. Common root causes included documentation errors (26.5%), communication (22.5%), technical treatment planning (37.5%), and technical treatment delivery (13.5%). Incidents were more frequently reported in minors (age <18 years) than in adult patients (37.7% vs 0.4%, P<.001). Patients with head and neck (16% vs 8%, P<.001) and breast (20% vs 15%, P=.03) primaries more frequently had incidents, whereas brain (18% vs 24%, P=.008) primaries were less frequent. Larger tumors (17% vs 10% had T4 lesions, P=.02), and cases on protocol (9% vs 5%, P=.005) or with intensity modulated radiation therapy/image guided intensity modulated radiation therapy (52% vs 43%, P=.001) were more likely to have incidents. CONCLUSIONS: We found several treatment- and patient-specific variables associated with incidents. These factors should be considered by treatment teams at the time of peer review to identify patients at higher risk. Larger datasets are required to recommend changes in care process standards, to minimize safety risks.

Quality control quantification (QCQ): a tool to measure the value of quality control checks in radiation oncology.

PURPOSE: To quantify the error-detection effectiveness of commonly used quality control (QC) measures. METHODS: We analyzed incidents from 2007-2010 logged into a voluntary in-house, electronic incident learning systems at 2 academic radiation oncology clinics. None of the incidents resulted in patient harm. Each incident was graded for potential severity using the French Nuclear Safety Authority scoring scale; high potential severity incidents (score >3) were considered, along with a subset of 30 randomly chosen low severity incidents. Each report was evaluated to identify which of 15 common QC checks could have detected it. The effectiveness was calculated, defined as the percentage of incidents that each QC measure could detect, both for individual QC checks and for combinations of checks. RESULTS: In total, 4407 incidents were reported, 292 of which had high-potential severity. High- and low-severity incidents were detectable by 4.0 ± 2.3 (mean ± SD) and 2.6 ± 1.4 QC checks, respectively (P<.001). All individual checks were less than 50% sensitive with the exception of pretreatment plan review by a physicist (63%). An effectiveness of 97% was achieved with 7 checks used in combination and was not further improved with more checks. The combination of checks with the highest effectiveness includes physics plan review, physician plan review, Electronic Portal Imaging Device-based in vivo portal dosimetry, radiation therapist timeout, weekly physics chart check, the use of checklists, port films, and source-to-skin distance checks. Some commonly used QC checks such as pretreatment intensity modulated radiation therapy QA do not substantially add to the ability to detect errors in these data. CONCLUSIONS: The effectiveness of QC measures in radiation oncology depends sensitively on which checks are used and in which combinations. A small percentage of errors cannot be detected by any of the standard formal QC checks currently in broad use, suggesting that further improvements are needed. These data require confirmation with a broader incident-reporting database.