Using failure mode and effects analysis (FMEA) to generate an initial plan check checklist for improved safety in radiation treatment

The Future of Safety and Quality in Radiation Oncology

The increasing complexity of radiation therapy treatment presents new potentials for error and suboptimal care. High-performing programs thus not only require adherence to, but also ongoing improvement of, key safety and quality practices. In this article, we review these practices including standardization, risk analysis, peer review, and maintenance of strong safety culture, while also describing recent innovations and promising future directions. We specifically highlight the growing role of artificial intelligence in radiation oncology, both as a tool to deliver safe, high-quality care and as a potential new source of safety challenges.

Enhancing patient safety in radiotherapy: Implementation of a customized electronic checklist for radiation therapists

Introduction

The radiotherapy workflow involves the collaboration of multiple professionals and the execution of several steps to results in an effective treatment. In this study, we described the clinical implementation of an electronic checklist, developed to standardize the process of the chart review prior to the first treatment fraction by the radiation therapists (RTTs).

Materials and Methods

A customized electronic checklist was developed based on the recommendations of American Association of Physicists in Medicine (AAPM) Task Groups 275 and 315 and integrated into the Record and Verify System (RVS). The checklist consisted of 16 items requiring binary (yes/no) responses, with mandatory completion and review by RTTs prior to treatment. The utility of the checklist and its impact on workflow were assessed by analysing checklist reports, and by soliciting feedback to RTTs through an anonymized survey.

Results

During the first trial phase, from June to November 2023, 285 checklists were completed with a 98% compilation rate and 94.4% review rate. Forty errors were detected, mainly due to missing signed treatment plans and absence of Beam's Eye View documentation. Ninety percent of detected errors were fixed before the treatment start. In 4 cases, the problem could not be fixed before the first fraction, resulting in a suboptimal first treatment. The feedback survey showed that RTTs described the checklist as useful, with minimal impact on workload, and supported its implementation.

Discussion

The introduction of a customized electronic checklist improved the detection and correction of errors, thereby enhancing patient safety. The positive response from RTTs and the minimal impact on workflow underscore the value of the checklist as standard practice in radiotherapy departments.

Improving the safety of radiotherapy treatment processes via incident-driven FMEA feedback loops

BACKGROUND

Failure mode and effects analysis (FMEA) is a valuable tool for radiotherapy risk assessment, yet its outputs might be unreliable due to failures not being identified or due to a lack of accurate error rates.

PURPOSE

A novel incident reporting system (IRS) linked to an FMEA database was tested and evaluated. The study investigated whether the system was suitable for validating a previously performed analysis and whether it could provide accurate error rates to support the expert occurrence ratings of previously identified failure modes.

METHODS

Twenty-three pre-identified failure modes of our external beam radiotherapy process, covering the process steps from patient admission to treatment delivery, were proffered on dedicated FMEA feedback and incident reporting terminals generated by the IRS. The clinical setting involved a computed tomography scanner, dosimetry, and five linacs. Incoming reports were used as basis to identify additional failure modes or confirm initial ones. The Kruskal-Wallis H test was applied to compare the risk priorities of the retrospective and prospective failure modes. Wald's sequential probability ratio test was used to investigate the correctness of the experts' occurrence ratings by means of the number of incoming reports.

RESULTS

Over a 15-month period, 304 reports were submitted. There were 0.005 (confidence interval [CI], 0.0014-0.0082) reported incidents per imaging study and 0.0006 (CI, 0.0003-0.0009) reported incidents per treatment fraction. Sixteen additional failure modes could be identified, and their risk priorities did not differ from those of the initial failure modes (p = 0.954). One failure mode occurrence rating could be increased, whereas the other 22 occurrence ratings could not be disproved.

CONCLUSIONS

Our approach is suitable for validating FMEAs and deducing additional failure modes on a continual basis. Accurate error rates can only be provided if a sufficient number of reports is available.

Process failure mode and effects analysis for external beam radiotherapy: Introducing a literature-based template and a novel action priority

PURPOSE

The first aim of the study was to create a general template for analyzing potential failures in external beam radiotherapy, EBRT, using the process failure mode and effects analysis (PFMEA). The second aim was to modify the action priority (AP), a novel prioritization method originally introduced by the Automotive Industry Action Group (AIAG), to work with different severity, occurrence, and detection rating systems used in radiation oncology.

METHODS AND MATERIALS

The AIAG PFMEA approach was employed in combination with an extensive literature survey to develop the EBRT-PFMEA template. Subsets of high-risk failure modes found through the literature survey were added to the template where applicable. Our modified AP for radiation oncology (RO AP) was defined using a weighted sum of severity, occurrence, and detectability. Then, Monte Carlo simulations were conducted to compare the original AIAG AP, the RO AP, and the risk priority number (RPN). The results of the simulations were used to determine the number of additional corrective actions per failure mode and to parametrize the RO AP to our department's rating system.

RESULTS

An EBRT-PFMEA template comprising 75 high-risk failure modes could be compiled. The AIAG AP required 1.7 additional corrective actions per failure mode, while the RO AP ranged from 1.3 to 3.5, and the RPN required 3.6. The RO AP could be parametrized so that it suited our rating system and evaluated severity, occurrence, and detection ratings equally to the AIAG AP.

CONCLUSIONS

An adjustable EBRT-PFMEA template is provided which can be used as a practical starting point for creating institution-specific templates. Moreover, the RO AP introduces transparent action levels that can be adapted to any rating system.

Risk management of radioiodine treatment in differentiated thyroid cancer

INTRODUCTION

Patient safety is paramount in providing quality healthcare and constitutes a global concern for healthcare systems. Radioiodine treatment to patients with well-differentiated thyroid cancer is not without risks. The aim of this study is to identify, evaluate and mitigate the risks associated with this procedure.

MATERIALS AND METHODS

A single-centre descriptive study was conducted in which risk management was carried out by establishing a risk map using FMEA methodology.

RESULTS

Based on the process map 6 sub-processes and 23 failure modes in the three phases of the treatment process were analysed. According to risk priority number (RPN), the sub-process with the highest risk was administrative management (RPN 82), followed by treatment per se and post-treatment imaging (both with RPN 70). An overall process RPN of 300 (156 pre-treatment, 74 treatment and 70 post-treatment) was obtained. Failures directly related to the patient pose a high risk. The implementation of verification systems, performing tasks earlier and providing quality medical information are the most relevant preventive measures to be implemented.

CONCLUSIONS

The application of the FMEA methodology in the risk management for radioiodine treatment is a valuable tool for improving the quality and safety of this process. The risk map has been able to identify failures at different stages, assess their causes and effects, prioritise the risks identified and implement preventive and corrective measures that can be monitored, ensuring the effectiveness of the actions taken.

Multi-phase failure modes and effects analysis for low dose bilateral whole lung irradiation of COVID-19 positive patients requiring respiratory ventilation

PURPOSE

To identify high-priority risks in a clinical trial investigating the use of radiation to alleviate COVID-19 pneumonia using a multi-phase failure modes and effects analysis (FMEA).

METHODS

A comprehensive FMEA survey of 133 possible causes of failure was developed for the clinical trial workflow (Phase I). The occurrence, severity, and detection risk of each possible cause of failure was scored by three medical physicists. High-risk potential failure modes were identified using the risk priority number (RPN) and severity scores, which were re-scored by 13 participants in radiation oncology (Phase II). Phase II survey scores were evaluated to identify steps requiring possible intervention and examine risk perception patterns. The Phase II participants provided consensus scores as a group.

RESULTS

Thirty high-priority failure modes were selected for the Phase II survey. Strong internal consistency was shown in both surveys using Cronbach's alpha (αc ≥ 0.85). The 10 failures with the largest median RPN values concerned SARS-CoV-2 transmission (N = 6), wrong treatment (N = 3), and patient injury (N = 1). The median RPN was larger for COVID-related failures than other failure types, primarily due to the perceived difficulty of failure detection. Group re-scoring retained 8/10 of the highest-priority risk steps that were identified in the Phase II process, and discussion revealed interpretation differences of process steps and risk evaluation. Participants who were directly involved with the trial working group had stronger agreement on severity scores than those who were not.

CONCLUSIONS

The high ranking of failures concerning SARS-CoV-2 transmission suggest that these steps may require additional quality management intervention when treating critically ill COVID-19+ patients. The results also suggest that a multi-phase FMEA survey led by a facilitator may be a useful tool for assessing risks in radiation oncology procedures, supporting future efforts to adapt FMEA to clinical procedures.

ACPSEM position paper: pre-treatment patient specific plan checks and quality assurance in radiation oncology

The Australasian College of Physical Scientists and Engineers in Medicine (ACPSEM) has not previously made recommendations outlining the requirements for physics plan checks in Australia and New Zealand. A recent workforce modelling exercise, undertaken by the ACPSEM, revealed that the workload of a clinical radiation oncology medical physicist can comprise of up to 50% patient specific quality assurance activities. Therefore, in 2022 the ACPSEM Radiation Oncology Specialty Group (ROSG) set up a working group to address this issue. This position paper authored by ROSG endorses the recommendations of the American Association of Physicists in Medicine (AAPM) Task Group 218, 219 and 275 reports with some contextualisation for the Australia and New Zealand settings. A few recommendations from other sources are also endorsed to complete the position.

Evaluación de riesgos y mejora de la seguridad biológica y radiológica en la toma de radiografía torácica a pacientes con COVID-19

INTRODUCTION

Health workers are at high risk of becoming infected with COVID-19. The objective of the study was to evaluate the risks and improve the biological and radiological safety measures for taking chest X-rays in patients with COVID-19 in a Social Security hospital in Utcubamba (Peru).

MATERIAL AND METHODS

Quasi-experimental intervention study type before and after without a control group, carried out between May and September 2020. A process map and an analysis of failure modes and effects (FMEA) of radiological care were prepared. The gravity (G), occurrence (O), and detectability (D) values ??were found and the risk priority number (RPN) was calculated for each failure mode (FM). FM with RPN ≥ 100 and G ≥ 7 were prioritized. Improvement actions were implemented based on the recommendations of recognized institutions and the O and D values ??were re-evaluated.

RESULTS

The process map consisted of 6 threads and 30 steps. 54 FM were identified, 37 of whom had RPN ≥ 100 and 48 had G ≥ 7. Most of the errors occurred during the examination 50% (27). After entering the recommendations, 23 FM had RPN ≥ 100.

CONCLUSIONS

Although none of the measures applied through the FMEA made the failure mode impossible, they made it more detectable and less frequent and reduced the RPN for each failure mode; however, a periodic update of the process is necessary.

Frequency of errors in the transfer of treatment parameters from the treatment planning system to the oncology information system in a multi-vendor environment

BACKGROUND

Technological advancements have made it possible to improve patient outcomes in radiotherapy, sparing both normal tissues and increasing tumour control. However, these advancements have resulted in an increase in the number of software systems used, which each require data inputs to function. For institutions with multiple vendors for their treatment planning systems and oncology information systems, the transfer of data between them is potentially error prone and can lead to treatment errors.

PURPOSE

The goal of this work was to determine the frequency of errors in data transfers between the Varian Eclipse treatment planning system and the Elekta Mosaiq oncology information system.

METHODS

An in-house program was used to quantify the number of errors for 2700 unique plans over an 8-month period. Using this information, the frequency of the errors were calculated. A risk priority number was calculated using the calculated frequencies to determine the impact on the clinic.

RESULTS

The most common errors discovered were backup timer settings (10.7%), Field label (8.5%), DRR associations (3.3%), imaging field types (3.1%), dose rate (1%), Field Id (0.8%), imaging isocenter (0.7% and SSD (0.7%). Based on the risk priority numbers, the DRR association error was ranked as having the highest potential impact on the patient.

CONCLUSIONS

The results of the work show that the most effort should be focused on checking the manual steps performed in the transfer process, while items that are imported directly from DICOM-RT without modification are highly likely to be transferred accurately. The data can be used to help guide the implementation of future automated tools and process improvement in the clinic.

Medical physics practice guideline 4.b: Development, implementation, use and maintenance of safety checklists

The American Association of Physicists in Medicine (AAPM) is a nonprofit professional society whose primary purposes are to advance the science, education, and professional practice of medical physics. The AAPM has more than 8000 members and is the principal organization of medical physicists in the US. The AAPM will periodically define new practice guidelines for medical physics practice to help advance the science of medical physics and to improve the quality of service to patients throughout the US. Existing medical physics practice guidelines will be reviewed for the purpose of revision or renewal, as appropriate, on their fifth anniversary or sooner. Each medical physics practice guideline represents a policy statement by the AAPM, has undergone a thorough consensus process in which it has been subjected to extensive review, and requires the approval of the Professional Council. The medical physics practice guidelines recognize that the safe and effective use of diagnostic and therapeutic radiology requires specific training, skills, and techniques, as described in each document. Reproduction or modification of the published practice guidelines and technical standards by those entities not providing these services is not authorized. The following terms are used in the AAPM practice guidelines: Must and must not: Used to indicate that adherence to the recommendation is considered necessary to conform to this practice guideline. While must is the term to be used in the guidelines, if an entity that adopts the guideline has shall as the preferred term, the AAPM considers that must and shall have the same meaning. Should and should not: Used to indicate a prudent practice to which exceptions may occasionally be made in appropriate circumstances.

Financial and Safety Impact of Simulation-based Clinical Systems Testing on Pediatric Trauma Center Transitions

Simulation offers multiple tools that apply to medical settings, but little is known about the application of simulation to pediatric trauma workflow changes. Our institution recently underwent significant clinical changes in becoming an independent pediatric trauma center. We used a simulation-based clinical systems testing (SbCST) approach to manage change-associated risks. The purpose of this study was to describe our SbCST process, evaluate its impact on patient safety, and estimate financial costs and benefits.

Failure modes in stereotactic radiosurgery. A narrative review

OBJECTIVES

Stereotactic radiosurgery (SRS) refers to an advanced radiotherapy technique that requires a high level of precision and accuracy and a flawless workflow. Failures within the SRS process can lead to serious consequences due to high doses delivered per treatment. This narrative review aimed to identify the riskiest failure modes (FMs) and the stages at which they occur in the SRS process, as well as the strategies applied to mitigate the risks. It was based on the analysis of published failure mode and effects analysis (FMEA) data.

KEY FINDINGS

From the literature search in PubMed and Scopus, 7 articles met the eligibility criteria for inclusion in the qualitative synthesis. In total, 9 radiotherapy departments conducted FMEA in the SRS process. 4 of them were community hospitals and 5 were academic centers. Overall, 54 high-risk FMs were identified with treatment planning (FMs: 18), treatment delivery (FMs: 12), consultation and patient registration (FMs: 10) being the riskiest stages. 10 FMs were stereotactic specific, while the remaining 44 could be met in any radiotherapy technique. Failures associated with contouring, medical records review, target reirradiation, and patient positioning were mostly outlined. Risk mitigation strategies included timeouts, double-checks, checklists, training and changes in the working practice.

CONCLUSION

Our review demonstrated that crucial FMs can occur in all SRS stages. Although generalisations were challenging, the FMs analysis provided a significant source of information about potential high risks and continuous improvement strategies that can be applied both in the SRS and other radiotherapy processes.

IMPLICATIONS FOR PRACTICE

The results of this research will assist radiotherapy facilities in proactive risk management studies and will allow radiotherapy professionals to reflect on their practice and learn from others' experiences.

Failure modes and effects analysis for surface-guided DIBH breast radiotherapy

Despite breast cancer prevalence and widespread adoption of deep inspiration breath‐hold (DIBH) radiation techniques, few data exist on the error risks related to using surface‐guided (SG) DIBH during breast radiation therapy (RT). Due to the increasingly technical nature of these methods and being a paradigm shift from traditional breast setups/treatments, the associated risk for error is high. Failure modes and effects analysis (FMEA) has been used in identifying risky RT processes yet is time‐consuming to perform. A subset of RT staff and a hospital patient‐safety representative performed FMEA to study SG‐DIBH RT processes. After this group (cohort 1) analyzed these processes, additional scoring data were acquired from RT staff uninvolved in the original FMEA (cohort 2). Cohort 2 received abbreviated FMEA training while using the same process maps that cohort 1 had created, which was done with the goal of validating our results and exploring the feasibility of expedited FMEA training and efficient implementation elsewhere. An extensive review of the SG‐DIBH RT process revealed 57 failure modes in 16 distinct steps. Risks deemed to have the highest priority, large risk priority number (RPN), and severity were addressed with policy changes, checklists, and standardization; of these, most were linked with operator error via manual inputs and verification. Reproducibility results showed that 5% of the average RPN between cohorts 1 and 2 was statistically different. Unexpected associations were noted between RPN and RT staff role; 12% of the physicist and therapist average scores were statistically different. Different levels of FMEA training yielded similar scoring within one RT department, suggesting a time‐savings can be achieved with abbreviated training. Scores between professions, however, yielded significant differences suggesting the importance of involving staff across disciplines.

Combining Failure Modes and Effects Analysis and Cause-Effect Analysis: A Novel Method of Risk Analysis to Reduce Anaphylaxis Due to Contrast Media

BACKGROUND

Contrast media agents are essential for computed tomography-based diagnoses. However, they can cause fatal adverse effects such as anaphylaxis in patients. Although it is rare, the chances of anaphylaxis increase with the number of examinations. Thus, we aimed to design a quality-improvement initiative to reduce patient risk to these agents.

METHODS

We analysed computed tomography processes using contrast iodine in a tertiary-care academic hospital that performs approximately 14,000 computed tomography scans per year in Japan. We applied a combination of failure modes and effects analysis and cause-effect analysis to reduce the risk of patients developing allergic reactions to iodine-based contrast agents during computed tomography imaging.

RESULTS

Our multidisciplinary team comprising seven professionals analysed the data and designed a 56-process flowchart of computed tomography imaging with iodine. We obtained 177 failure modes, of which 15 had a risk-probability number higher than 100. We identified the two riskiest processes and developed cause-and-effect diagrams for both: one was related to exchange of information between the radiation and hospital information system regarding the patient's allergy, the other was due to education and structural deficiencies in observation following the exam.

CONCLUSION

The combined method of failure mode effect analysis and cause-and-effect analysis reveals high-risk processes and suggests measures to reduce these risks. Failure modes and effects analysis is not well-known in healthcare but has significant potential for improving patient safety. Our findings emphasise the importance of adopting new techniques to reduce patient risk and carry out best practices in radiology.