Identification of key potential risk areas and key potential failure modes in hemodialysis rooms by the FMEA method following routine prevention and control of the COVID-19 pandemic.

Hemodialysis is an important part of nosocomial infection prevention and control (IPC). This study aimed to identify the key potential risk areas and failure modes in hemodialysis rooms in hospitals and put forward a series of improvement measures to prevent and control the spread of the coronavirus disease 2019 (COVID-19). Hemodialysis patients are highly susceptible to COVID-19 and usually have a high incidence of severe illness and mortality after infection with COVID-19. Therefore, IPC in hemodialysis patients is of crucial strategic significance. Based on 30 domain experts' interviews and careful analysis of prevention and control documents, we constructed a comprehensive failure system for a model that identifies the potential risks for nosocomial COVID-19 infection in the hemodialysis room. Subsequently, a thorough risk assessment of the potential failure factors identified in our model was conducted. The failure key factors corresponding to the human element in medical waste (garbage) disposal (C2) are verified to be the highest risk factors. They are as follows: The cleaning staff did not dispose of different types of medical waste (garbage) (C21), did not wear masks according to the regulations (C22), and lacked knowledge and norms of nosocomial IPC (C23). This study provides valuable insights for hospital decision-makers on the potential failure factors related to COVID-19 infections in hemodialysis rooms. By working with hospital infection specialists, the suggested improvement measures can help reduce the risk of virus exposure among hospital medical staff, patients, and cleaning staff.

Identification of key potential infection processes and risk factors in the computed tomography examination process by FMEA method under COVID-19.

PURPOSE: To identify the key infection processes and risk factors in Computed Tomography (CT) examination process within the standard prevention and control measures for the COVID-19 epidemic, aiming to mitigate cross-infection occurrences in the hospital. METHOD: The case hospital has assembled a team of 30 experts specialized in CT examination. Based on the CT examination process, the potential failure modes were assessed from the perspective of severity (S), occurrence probability (O), and detectability (D); they were then combined with corresponding risk prevention measures. Finally, key infection processes and risk factors were identified according to the risk priority number (RPN) and expert analysis. RESULTS: Through the application of RPN and further analysis, four key potential infection processes were identified, including "CT request form (A1)," "during the scan of CT patient (B2)," "CT room and objects disposal (C2)," and "medical waste (garbage) disposal (C3)". In addition, eight key risk factors were also identified, including "cleaning personnel does not wear masks normatively (C32)," "nurse does not select the vein well, resulting in extravasation of the peripheral vein for enhanced CT (B25)," "patient cannot find the CT room (A13)," "patient has obtained a CT request form but does not know the procedure (A12)," "patient is too unwell to continue with the CT scan (B24)," "auxiliary staff (or technician) does not have a good grasp of the sterilization and disinfection standards (C21)," "auxiliary staff (or technician) does not sterilize the CT machine thoroughly (C22)," and "cleaning personnel lacks of knowledge of COVID-19 prevention and control (C33)". CONCLUSION: Hospitals can publicize the precautions regarding CT examination through various channels, reducing the incidence of CT examination failure. Hospitals' cleaning services are usually outsourced, and the educational background of the staff employed in these services is generally not high. Therefore, during training and communication, it is more necessary to provide a series of scope and training programs that are aligned with their understanding level. The model developed in this study effectively identifies the key infection prevention process and critical risk factors, enhancing the safety of medical staff and patients. This has significant research implications for the potential epidemic of major infectious diseases.

Reducing the Risk of Fall among Oncology Patients using Failure Modes and Effects Analysis.

OBJECTIVE: This project aimed to mitigate the risk of falls among oncology patients using Failure Modes and Effects Analysis (FMEA) in the outpatient setting.



Methods: The project was conducted within outpatient settings, specifically encompassing outpatient clinics, daycare, radiology and radiotherapy, and rehabilitation at the SQCCCRC. The project employed an observational analytical design to assess the fall risk assessment procedure in outpatient settings. The project integrated a 7-step procedure for conducting an FMEA methodology, including defining the system or process, identifying potential failure mode, evaluating the effects of each failure mode, Assigning severity, likelihood, and detection of occurrence ratings, and identifying and implement corrective actions. In addition, Risk Priority Numbers (RPNs) were used to identify the impact of the interventions in reducing the risk of patient fall assessment and management.



Result: In the patient fall screening process, interventions yielded substantial reductions in RPNs for failure modes like "Wrong assessment" (57% decrease) and "Complex risk assessment scale" (63% decrease), addressing knowledge gaps and simplifying risk assessment. Similarly, the "Missed fall assessment" failure mode saw an impressive 80% reduction in RPN, rectifying unclear processes and knowledge gaps. In the Fall risk precaution measures process, interventions led to noteworthy RPN reductions, such as 80% for "Unclear fall precaution measures-responsibilities" and 57% for "Missed bracelets for high risk," demonstrating successful risk mitigation. Moreover, interventions in the Patient Education process achieved significant RPN reductions (57% and 55%) for "No/improper education" and "Unuse of educational material and resources," enhancing staff education and patient awareness. The total reduction in RPNs was 62% in all failure modes in the fall assessment and management process.



Conclusion: Overall, FMEA is a valuable strategy for reducing fall risks among oncology patients, but its success depends on addressing these limitations and ensuring the thorough execution and maintenance of the identified corrective actions.

Development and clinical implementation of a digital system for risk assessments for radiation therapy.

Before introducing new treatment techniques, an investigation of hazards due to unintentional radiation exposures is a reasonable activity for proactively increasing patient safety. As dedicated software is scarce, we developed a tool for risk assessment to design a quality management program based on best practice methods, i.e., process mapping, failure modes and effects analysis and fault tree analysis. Implemented as a web database application, a single dataset was used to describe the treatment process and its failure modes. The design of the system and dataset allowed failure modes to be represented both visually as fault trees and in a tabular form. Following the commissioning of the software for our department, previously conducted risk assessments were migrated to the new system after being fully re-assessed which revealed a shift in risk priorities. Furthermore, a weighting factor was investigated to bring risk levels of the migrated assessments into perspective. The compensation did not affect high priorities but did re-prioritize in the midrange of the ranking. We conclude that the tool is suitable to conduct multiple risk assessments and concomitantly keep track of the overall quality management activities.

Improving the quality of hospital sterilization process using failure modes and effects analysis, fuzzy logic, and machine learning: experience in tertiary dental centre.

Activities practiced in the hospital generate several types of risks. Therefore, performing the risk assessment is one of the quality improvement keys in the healthcare sector. For this reason, healthcare managers need to design and perform efficient risk assessment processes. Failure modes and effects analysis (FMEA) is one of the most used risk assessment methods. The FMEA is a proactive technique consisting of the evaluation of failure modes associated with a studied process using three factors: occurrence, non-detection, and severity, in order to obtain the risk priority number using fuzzy logic approach and machine learning algorithms, namely the support vector machine and the k-nearest neighbours. The proposed model is applied in the case of the central sterilization unit of a tertiary national reference centre of dental treatment, where its efficiency is evaluated compared to the classical approach. These comparisons are based on expert advice and machine learning performance metrics. Our developed model proved high effectiveness throughout the results of the expert's vote (she agrees with 96% fuzzy-FMEA results against 6% with classical FMEA results). Furthermore, the machine learning metrics show a high level of accuracy in both training data (best rate is 96%) and testing data (90%). This study represents the first study that aims to perform artificial intelligence approach to risk management in the Moroccan healthcare sector. The perspective of this study is to promote the application of the artificial intelligence in Moroccan health management, especially in the field of quality and safety management.

Risk management patterns in radiation oncology-results of a national survey within the framework of the Patient Safety in German Radiation Oncology (PaSaGeRO) project.

PURPOSE: Risk management (RM) is a key component of patient safety in radiation oncology (RO). We investigated current approaches on RM in German RO within the framework of the Patient Safety in German Radiation Oncology (PaSaGeRO) project. Aim was not only to evaluate a status quo of RM purposes but furthermore to discover challenges for sustainable RM that should be addressed in future research and recommendations. METHODS: An online survey was conducted from June to August 2021, consisting of 18 items on prospective and reactive RM, protagonists of RM, and self-assessment concerning RM. The survey was designed using LimeSurvey and invitations were sent by e­mail. Answers were requested once per institution. RESULTS: In all, 48 completed questionnaires from university hospitals, general and non-academic hospitals, and private practices were received and considered for evaluation. Prospective and reactive RM was commonly conducted within interprofessional teams; 88% of all institutions performed prospective risk analyses. Most institutions (71%) reported incidents or near-events using multiple reporting systems. Results were presented to the team in 71% for prospective analyses and 85% for analyses of incidents. Risk conferences take place in 46% of institutions. 42% nominated a manager/committee for RM. Knowledge concerning RM was mostly rated "satisfying" (44%). However, 65% of all institutions require more information about RM by professional societies. CONCLUSION: Our results revealed heterogeneous patterns of RM in RO departments, although most departments adhered to common recommendations. Identified mismatches between recommendations and implementation of RM provide baseline data for future research and support definition of teaching content.

Risk analysis of the Unity 1.5 T MR-Linac adapt-to-position workflow.

BACKGROUND AND PURPOSE: Newer technologies allow for daily treatment adaptation, providing the ability to account for setup variations and organ motion but comes at the cost of increasing the treatment workflow complexity. One such technology is the adapt-to-position (ATP) workflow on the Unity MR-Linac. Prospective risk assessment of a new workflow allows clinics to catch errors before they occur, especially for processes that include novel and unfamiliar steps. METHODS: As part of a quality management program, failure modes and effects analysis was performed on the ATP treatment workflow following the recommendations of AAPM's Task Group 100. A multidisciplinary team was formed to identify and evaluate failure modes for all the steps taken during a daily treatment workflow. Failure modes of high severity and overall score were isolated and addressed. RESULTS: Mitigations were determined for high-ranking failure modes and implemented into the clinic. High-ranking failure modes existed in all steps of the workflow. Failure modes were then rescored to evaluate the effectiveness of the mitigations. CONCLUSION: Failure modes and effects analysis on the Unity MR-Linac highlighted areas in the ATP workflow that could be prone to failures and allowed our clinic to change the process to be more robust.

Failure modes and effects analysis of pediatric I-131 MIBG therapy: Program design and potential pitfalls.

BACKGROUND: There is growing interest among pediatric institutions for implementing iodine-131 (I-131) meta-iodobenzylguanidine (MIBG) therapy for treating children with high-risk neuroblastoma. Due to regulations on the medical use of radioactive material (RAM), and the complexity and safety risks associated with the procedure, a multidisciplinary team involving radiation therapy/safety experts is required. Here, we describe methods for implementing pediatric I-131 MIBG therapy and evaluate our program's robustness via failure modes and effects analysis (FMEA). METHODS: We formed a multidisciplinary team, involving pediatric oncology, radiation oncology, and radiation safety staff. To evaluate the robustness of the therapy workflow and quantitatively assess potential safety risks, an FMEA was performed. Failure modes were scored (1-10) for their risk of occurrence (O), severity (S), and being undetected (D). Risk priority number (RPN) was calculated from a product of these scores and used to identify high-risk failure modes. RESULTS: A total of 176 failure modes were identified and scored. The majority (94%) of failure modes scored low (RPN <100). The highest risk failure modes were related to training and to drug-infusion procedures, with the highest S scores being (a) caregivers did not understand radiation safety training (O = 5.5, S = 7, D = 5.5, RPN = 212); (b) infusion training of staff was inadequate (O = 5, S = 8, D = 5, RPN = 200); and (c) air in intravenous lines/not monitoring for air in lines (O = 4.5, S = 8, D = 5, RPN = 180). CONCLUSION: Through use of FMEA methodology, we successfully identified multiple potential points of failure that have allowed us to proactively mitigate risks when implementing a pediatric MIBG program.

Novel Method for Failure Modes Detection in UV-Cured Clear Coated Polymer for Automotive Interior Mechatronic Devices.

Plastic parts used in automotive interior are difficult to coat, due to their low surface energies as well as their sensitivity to temperature and solvents, rendering the development of coating systems for such substrates challenging. Automotive customer requirements are explicit and clear, mainly focused on functional and surface defects. A new failure modes detection methodology of UV clear coated polymers for automotive interior, obtained by a multi-step manufacturing process, is proposed. The polymer complex parts analyzed in this paper are manufactured in various steps as follows: two components plastic injection molding, primer coating, laser engraving, and UV-cured clear coating. The failure modes detection methodology of the parts within each process step is investigated using different tests and analyses as follows: surface tension test, painting adhesion test, optical 3D measuring, energy dispersive X-ray analysis (EDX), and microscopy. A design of the experiments (DoE) based on the Taguchi technique with the aim to detect the influence of the main factors that lead to surface defects was performed. The proposed methodology is validated by a case study. The results showed that the mold temperature and the laser engraving current have a significant influence on the surface defect occurrence. Additionally, a possible contamination of the molding tool can generate the defects. A solution to reduce the occurrence of the failures was proposed, reducing the defect rate from 50% to 0.9%.

Failure mode and effects analysis of telehealth service of minority elderly for sustainable digital transformation.

BACKGROUND: Telehealth services are time- and cost-saving solutions for disease management for older adults. Minority older individuals with multiple risk factors have an increasing demand for telehealth services. There are insufficient data on patient safety in telehealth services. This study aimed to enhance the quality of telehealth services by reducing errors and creating a safe user environment for low-income older adults. Failure mode and effects analysis tool (FMEA) was adopted to manage potential risks for sustainable digital transformation. METHOD: An eight-member multidisciplinary team conducted telehealth FMEA to determine risk priority numbers (RPNs). The process included identifying the potential cause and effect failure mode of each step; measuring severity, probability, and detectability scores for RPNs; and generating strategies to decrease potential failures. RESULTS: This study identified 24 risk factors and 34 causes in four major phases with a mean RPN of 90.7: preparation to measure biosignals, measurement of biosignals following instructions from a personal device, confirmation of measurement results, and intervention based on disease or condition type. Risk prioritization revealed four high failure modes and a total RPN of 362.7. Based on fundamental causes, risks were categorized as oblivescence, economic issues, and technology literacy. CONCLUSIONS: To correct these failure modes, stabilization of the platform, adding to the providers' manpower, and support for government policies are recommended. FMEA identifies and evaluates the potential risks of telehealth services. The selected priorities reduce the clinical risks of low-income elders who use telehealth services by weighting clinical actions.

Cystic fibrosis learning network telehealth innovation lab during the COVID-19 pandemic: a success QI story for interdisciplinary care and agenda setting.

INTRODUCTION: The Cystic Fibrosis Foundation chronic care guidelines recommend monitoring clinical status of a patient with cystic fibrosis (CF) through quarterly interdisciplinary visits. At the beginning of the COVID-19 pandemic, the Cystic Fibrosis Learning Network (CFLN) designed and initiated a telehealth (TH) innovation lab (TH ILab) to support transition from the classic CF care model of quarterly in-person office visits to a care model that included TH. AIM: The specific aims of the TH ILab were to increase the percentage of virtual visits with interdisciplinary care (IDC) from 60% to 85% and increase the percentage of virtual visits in which patients and families participated in shared agenda setting (AS) from 52% to 85% by 31 December 2020. METHODS: The model for improvement methodology was used to determine the ILab aims, theory, interventions and measures. In the testing phase of the ILab, data related to process and outcome measures as well as learnings from plan-do-study-act cycles were collected, analysed and shared weekly with the TH ILab teams. Participating centres created processes for IDC and AS for TH visits and developed and shared quality improvement tools specific to their local context with other centres during the ILab weekly meetings and via a secure CFLN-maintained platform. RESULTS: Both specific aims were achieved ahead of the expected target date. By August 2020, 85% of the TH ILab visits provided IDC and 92% of patients were seen for CF care by teams from the TH ILab that participated in AS. CONCLUSION: Shared learning through a collaborative, data-driven process in the CFLN TH ILab rapidly led to standardised TH IDC and AS, which achieved reliable and sustainable processes which could be reproduced by other networks.

Application of Integrated Emergency Care Model Based on Failure Modes and Effects Analysis in Patients With Ischemic Stroke.

Purpose: To explore the application value of an integrated emergency care model based on failure modes and effects analysis (FMEA) in patients with acute ischemic stroke (AIS). Methods: According to the convenience sampling method, 100 patients with AIS who visited the emergency department in our hospital from October 2018 to March 2019 were randomly selected as the control group and received routine emergency care mode intervention. Another 100 AIS patients who visited the emergency department from April to October 2019 were selected as the intervention group and received the integrated emergency care model based on FMEA. The total time spent from admission to completion of each emergency procedure [total time spent from admission to emergency physician reception (T0-1), total time spent from admission to stroke team reception (T0-2), total time spent from admission to imaging report out (T0-3), total time spent from admission to laboratory report out (T0-4), and total time spent from admission to intravenous thrombolysis (T0-5)] was recorded for both groups. The clinical outcome indicators (vascular recanalization rate, symptomatic intracerebral hemorrhage incidence, mortality rate) were observed for both groups. The National Institutes of Health Stroke Scale (NIHSS) score and Barthel score were evaluated for both groups after the intervention. The treatment satisfaction rate of the patients was investigated for both groups. Results: The total time of T0-1, T0-2, T0-3, T0-4, T0-5 in the intervention group (0.55 ± 0.15, 1.23 ± 0.30, 21.24 ± 3.01, 33.30 ± 5.28, 44.19 ± 7.02) min was shorter than that of the control group (1.22 ± 0.28, 4.01 ± 1.06, 34.12 ± 4.44, 72.48 ± 8.27, 80.31 ± 9.22) min (P < 0.05). The vascular recanalization rate in the intervention group (23.00%) was higher than that in the control group (12.00%) (P < 0.05). There was no statistical significance in the symptomatic intracerebral hemorrhage incidence and mortality rate in the two groups (P > 0.05). After intervention, the NIHSS score of the intervention group (2.95 ± 0.91) was lower than that of the control group (6.10 ± 2.02), and the Barthel score (77.58 ± 7.33) was higher than that of the control group (53.34 ± 5.12) (P < 0.05). The treatment satisfaction rate in the intervention group (95.00%) was higher than that of the control group (86.00%) (P < 0.05). Conclusion: Through FMEA, the failure mode that affects the emergency time of AIS patients is effectively analyzed and the targeted optimization process is proposed, which are important to enhance the efficiency and success rate of resuscitation of medical and nursing staff and improve the prognosis and life ability of patients.

Failure mode and effect analysis (FMEA) to identify and mitigate failures in a hospital rapid response system (RRS).

We performed FMEA on the existing RRS with the help of routine users of the RRS who acted as subject matter experts and evaluated the failures for their criticality using the Risk Priority Number approach based on their experience of the RRS. The FMEA found 35 potential failure modes and 101 failure mode effects across 13 process steps of the RRS. The afferent limb of RRS was found to be more prone to these failures (62, 61.4%) than the efferent limb of the RRS (39, 38.6%). Modification of calling criteria (12, 11.9%) and calculation of New Zealand Early Warning Scores (NZEWS) calculation (11, 10.9%) steps were found to potentially give rise to the highest number of these failures. Causes of these failures include human error and related factors (35, 34.7%), staff workload/staffing levels (30, 29.7%) and limitations due to paper-based charts and organisational factors (n = 30, 29.7%). The demonstrated electronic system was found to potentially eliminate or reduce the likelihood of 71 (70.2%) failures. The failures not eliminated by the electronic RRS require targeted corrective measures including scenario-based training and education, and revised calling criteria to include triggers for hypothermia and high systolic blood pressure.

Análisis de riesgo en la terapia paciente específica del hipertiroidismo en Cuba / Risk analysis in patient-specific therapy for hyperthyroidism in Cuba

Introducción: En Cuba, se prevé realizar la terapia paciente específica del hipertiroidismo. Se han desarrollado una metodología y herramientas computacionales con este propósito. El análisis del riesgo permitirá acometer con calidad y seguridad dicha práctica. Objetivo: Analizar los riesgos radiológicos en la terapia paciente específica del hipertiroidismo en Cuba. Material y Métodos: Se revisó y adaptó el modelo genérico de Medicina Nuclear paciente específica. Con el código cubano SECURE MR-FMEA versión 3.0 se determinaron el riesgo inherente y el residual, se identificaron las etapas del proceso, los sucesos iniciadores, las medidas y causas más contribuyentes, así como las consecuencias para los grupos expuestos. Resultados: Se obtuvo un nivel alto de riesgo que se controló con las medidas adicionadas. Las etapas más significativas son: la adquisición de imágenes pre- y post- tratamiento y la preparación del radiofármaco. Las medidas preventivas más importantes son: mantener una carga de trabajo moderada para el personal, las capacitaciones del físico médico y de los especialistas que realizan las revisiones del proyecto en la etapa de diseño del servicio. Los pacientes tienen consecuencias muy altas en 10,7 por ciento de las secuencias accidentales. Sin embargo, los trabajadores y el público presentan consecuencias medias en 29 por ciento y 16 por ciento, respectivamente. El incumplimiento de prácticas, protocolos, procedimientos o normas es la causa básica de fallo predominante. Conclusiones: Se facilita la toma de decisiones para la implementación del tratamiento paciente específico del hipertiroidismo en Cuba, a partir del empleo de la metodología que se propone en esta investigación(AU)

Introduction: In Cuba, there are plans to conduct patient-specific therapy for hyperthyroidism. A methodology and computational tools have been developed for this purpose. Risk analysis will allow us to undertake this practice with quality and safety. Objective: To analyze the radiological risks in the patient -specific therapy for hyperthyroidism in Cuba. Material and Methods: The generic patient-specific Nuclear Medicine model was reviewed and adapted. Inherent and residual risk were determined with the Cuban code SECURE MR-FMEA version 3.0; the stages of the process, the initiating events, the most contributing measures and causes, and the consequences for the exposed groups were identified. Results: A high level of risk was obtained, which was controlled with additional measures. The most significant stages are the acquisition of pre- and post-treatment images, and the preparation of the radiopharmaceutical. The most important preventive measures are: maintaining a moderate workload of the staff, and the training of the medical physicist and the specialists who perform the project reviews at the stages in service design. Patients have very high consequences in 10,7 percent of accidental sequences. However, the workers and the public show average consequences at 29 percent and 16 percent, respectively. Non-compliance with practices, protocols, procedures or standards is the predominant underlying cause of failure(AU)Conclusions: Decision-making for the implementation of patient-specific therapy for hyperthyroidism in Cuba, based on the use of the methodology proposed in this research, is facilitated(AU)

Impact of failure mode and effects analysis-based emergency management on the effectiveness of craniocerebral injury treatment.

BACKGROUND: Craniocerebral injuries encompass brain injuries, skull fractures, cranial soft tissue injuries, and similar injuries. Recently, the incidence of craniocerebral injuries has increased dramatically due to the increased numbers of traffic accidents and aerial work injuries, threatening the physical and mental health of patients. AIM: To investigate the impact of failure modes and effects analysis (FMEA)-based emergency management on craniocerebral injury treatment effectiveness. METHODS: Eighty-four patients with craniocerebral injuries, treated at our hospital from November 2019 to March 2021, were selected and assigned, using the random number table method, to study (n = 42) and control (n = 42) groups. Patients in the control group received conventional management while those in the study group received FMEA theory-based emergency management, based on the control group. Pre- and post-interventions, details regarding the emergency situation; levels of inflammatory stress indicators [Interleukin-6 (IL-6), C-reactive protein (CRP), and procalcitonin (PCT)]; incidence of complications; prognoses; and satisfaction regarding patient care were evaluated for both groups. RESULTS: For the study group, the assessed parameters [pre-hospital emergency response time (9.13 ± 2.37 min), time to receive a consultation (2.39 ± 0.44 min), time needed to report imaging findings (1.15 ± 4.44 min), and test reporting time (32.19 ± 6.23 min)] were shorter than those for the control group (12.78 ± 4.06 min, 3.58 ± 0.71 min, 33.49 ± 5.51 min, 50.41 ± 11.45 min, respectively; P < 0.05). Pre-intervention serum levels of IL-6 (78.71 ± 27.59 pg/mL), CRP (19.80 ± 6.77 mg/L), and PCT (3.66 ± 1.82 ng/mL) in the study group patients were not significantly different from those in the control group patients (81.31 ± 32.11 pg/mL, 21.29 ± 8.02 mg/L, and 3.95 ± 2.11 ng/mL respectively; P > 0.05); post-intervention serum indicator levels were lower in both groups than pre-intervention levels. Further, serum levels of IL-6 (17.35 ± 5.33 pg/mL), CRP (2.27 ± 0.56 mg/L), and PCT (0.22 ± 0.07 ng/mL) were lower in the study group than in the control group (30.15 ± 12.38 pg/mL, 3.13 ± 0.77 mg/L, 0.38 ± 0.12 ng/mL, respectively; P < 0.05). The complication rate observed in the study group (9.52%) was lower than that in the control group (26.19%, P < 0.05). The prognoses for the study group patients were better than those for the control patients (P < 0.05). Patient care satisfaction was higher in the study group (95.24%) than in the control group (78.57%, P < 0.05). CONCLUSION: FMEA-based craniocerebral injury management effectively shortens the time spent on emergency care, reduces inflammatory stress and complication risk levels, and helps improve patient prognoses, while achieving high patient care satisfaction levels.

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 (CT)-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. OBJECTIVE: We aimed to design a quality improvement initiative to reduce patient risk to contrast media agents. METHODS: We analysed CT processes using contrast iodine in a tertiary-care academic hospital that performs approximately 14 000 CT scans per year in Japan. We applied a combination of failure modes and effects analysis (FMEA) and cause-effect analysis to reduce the risk of patients developing allergic reactions to iodine-based contrast agents during CT imaging. RESULTS: Our multidisciplinary team comprising seven professionals analysed the data and designed a 56-process flowchart of CT 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 the 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 FMEA and cause-and-effect analysis reveals high-risk processes and suggests measures to reduce these risks. FMEA 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.

A Practical Tool for Risk Management in Clinical Laboratories.

Risk management constitutes an essential component of the Quality Management System (QMS) of medical laboratories. The international medical laboratory standard for quality and competence, International Standards Organization (ISO) 15189, in its 2012 version, specified risk management for the first time. Since then, there has been much focus on this subject. We authors aimed to develop a practical tool for risk management in a clinical laboratory that contains five major cyclical steps: risk identification, quantification, prioritization, mitigation, and surveillance. The method for risk identification was based on a questionnaire that was formulated by evaluating five major components of laboratory processes, namely i) Specimen, ii) Test system, iii) Reagent, iv) Environment, and v) Testing. All risks that would be identified using the questionnaire can be quantified by calculating the risk priority number (RPN) using the tool, failure modes, and effects analysis (FMEA). Based on the calculated RPN, identified risks then shall be prioritized and mitigated. Based on our collective laboratory management experience, we authors also enlisted and scheduled a few process-specific quality assurances (QA) activities. The listed QA activities intend to monitor new risk emergence and re-emergence of those previously mitigated ones. We authors believe that templates of risk identification, risk quantification, and risk surveillance presented in this article will serve as ready references for supervisors of clinical laboratories.

Systems engineering analysis of diagnostic referral closed-loop processes.

BACKGROUND: Closing loops to complete diagnostic referrals remains a significant patient safety problem in most health systems, with 65%-73% failure rates and significant delays common despite years of improvement efforts, suggesting new approaches may be useful. Systems engineering (SE) methods increasingly are advocated in healthcare for their value in studying and redesigning complex processes. OBJECTIVE: Conduct a formative SE analysis of process logic, variation, reliability and failures for completing diagnostic referrals originating in two primary care practices serving different demographics, using dermatology as an illustrating use case. METHODS: An interdisciplinary team of clinicians, systems engineers, quality improvement specialists, and patient representatives collaborated to understand processes of initiating and completing diagnostic referrals. Cross-functional process maps were developed through iterative group interviews with an urban community-based health centre and a teaching practice within a large academic medical centre. Results were used to conduct an engineering process analysis, assess variation within and between practices, and identify common failure modes and potential solutions. RESULTS: Processes to complete diagnostic referrals involve many sub-standard design constructs, with significant workflow variation between and within practices, statistical instability and special cause variation in completion rates and timeliness, and only 21% of all process activities estimated as value-add. Failure modes were similar between the two practices, with most process activities relying on low-reliability concepts (eg, reminders, workarounds, education and verification/inspection). Several opportunities were identified to incorporate higher reliability process constructs (eg, simplification, consolidation, standardisation, forcing functions, automation and opt-outs). CONCLUSION: From a systems science perspective, diagnostic referral processes perform poorly in part because their fundamental designs are fraught with low-reliability characteristics and mental models, including formalised workaround and rework activities, suggesting a need for different approaches versus incremental improvement of existing processes. SE perspectives and methods offer new ways of thinking about patient safety problems, failures and potential solutions.

Guidelines in Practice: Specimen Management.

Specimen management is a complex process that involves multiple steps and numerous health care personnel. Preventable specimen-related errors are common and can occur during any phase of the specimen management process. Perioperative nurses manage specimens during the preanalytical phase before specimens are delivered to the laboratory for analysis. Errors in the preanalytical phase may include mislabeling, miscommunication, loss of a specimen, improper fixation of the specimen, and transport failures. The AORN "Guideline for specimen management" provides guidance for managing specimens collected during surgical and other invasive procedures, including recommendations for handling specific types of specimens. This article discusses the guideline recommendations for intraoperative team communication, transfer from the sterile field, containment, transport, and quality. A scenario describes a facility team's use of a root cause analysis and a failure modes and effects analysis tool to assess the risk and effects of specimen errors and create a process improvement plan.

Failure mode and effect analysis for linear accelerator-based paraspinal stereotactic body radiotherapy.

INTRODUCTION: Paraspinal stereotactic body radiotherapy (SBRT) involves risks of severe complications. We evaluated the safety of the paraspinal SBRT program in a large academic hospital by applying failure modes and effects analysis. METHODS: The analysis was conducted by a multidisciplinary committee (two therapists, one dosimetrist, four physicists, and two radiation oncologists). The paraspinal SBRT workflow was segmented into four phases (simulation, treatment planning, delivery, and machine quality assurance (QA)). Each phase was further divided into a sequence of sub-processes. Potential failure modes (PFM) were identified from each subprocess and scored in terms of the frequency of occurrence, severity and detectability, and a risk priority number (RPN). High-risk PFMs were identified based on RPN and were studied for root causes using fault tree analysis. RESULTS: Our paraspinal SBRT process was characterized by eight simulations, 11 treatment planning, nine delivery, and two machine QA sub-processes. There were 18, 29, 19, and eight PFMs identified from simulation, planning, treatment, and machine QA, respectively. The median RPN of the PFMs was 62.9 for simulation, 68.3 for planning, 52.9 for delivery, and 22.0 for machine QA. The three PFMs with the highest RPN were: previous radiotherapy outside the institution is not accurately evaluated (RPN: 293.3), incorrect registration between diagnostic magnetic resonance imaging and simulation computed tomography causing incorrect contours (273.0), and undetected patient movement before ExacTrac baseline (217.8). Remedies to the high RPN failures were implemented, including staff education, standardized magnetic resonance imaging acquisition parameters, and an image fusion process, and additional QA on beam steering. CONCLUSIONS: A paraspinal SBRT workflow in a large clinic was evaluated using a multidisciplinary and systematic risk analysis, which led to feasible solutions to key root causes. Treatment planning was a major source of PFMs that systematically affect the safety and quality of treatments. Accurate evaluation of external treatment records remains a challenge.