Latent human error analysis and efficient improvement strategies by fuzzy TOPSIS in aviation maintenance tasks

Flight safety assessment based on a modified human error risk quantification approach

In risk and safety assessments of aviation systems, engineers generally pay more attention to the risks of hardware or software failure and focus less on the risks caused by human errors. In this paper, a (FRAHE) method is proposed for identifying this critical error type and determining the risk severity of human errors. This method accounts for the human error probability as well as the impacts of human errors on the system. The fuzzy inference approach is employed in this paper to address the uncertainty and issues of imprecision that arise from insufficient information and scarce error data and a risk assessment model of human error is developed. The model can be used to precisely describe the relationship between the output risk severity and the input risk indicators, including the human error probability, the error impact probability, and the human error consequence. A case study of the approach task is presented to demonstrate the availability and reasonability of the model. The risk-based modeling method can not only provide valuable information for reducing the occurrence of critical errors but also be used to conduct prospective analyses to prevent unsafe incidents or aviation accidents.

Human Error Analysis and Modeling of Medication-Related Adverse Events in Taiwan Using the Human Factors Analysis and Classification System and Logistic Regression

Medical institutions worldwide strive to avoid adverse medical events, including adverse medication-related events. However, studies on the comprehensive analysis of medication-related adverse events are limited. Therefore, we aimed to identify the error factors contributing to medication-related adverse events using the Human Factors Analysis and Classification System (HFACS) and to develop error models through logistic regression. These models calculate the probability of a medication-related adverse event when a healthcare system defect occurs. Seven experts with at least 12 years of work experience (four nurses and three pharmacists) were recruited to analyze thirty-seven medication-related adverse events. The findings indicate that decision errors, physical/mental limitations, failure to correct problems, and organizational processes were the four factors that most frequently contributed to errors at the four levels of the HFACS. Seven error models of two types (error occurrence and error analysis pathways) were established using logistic regression models, and the relative probabilities of failure factor occurrences were calculated. Based on our results, medical staff can use the error models as a new analytical approach to improve and prevent adverse medication events, thereby improving patient safety.

An integrated multi-criteria decision-making approach for identifying the risk level of musculoskeletal disorders among handheld device users

In work-from-home (WFH) situation due to coronavirus (COVID-19) pandemic, the handheld device (HHD) users work in awkward postures for longer hours because of unavailability of ergonomically designed workstations. This problem results in different type of musculoskeletal disorders (MSDs) among the HHD users. An integrated multi-criteria decision-making approach was offered for identifying the risk level of MSDs among HHD users. A case example implemented the proposed approach in which, firstly, the best-worst method (BWM) technique was used to prioritize and determine the relative importance (weightage) of the risk factors. The weightages of the risk factors further used to rank the seven alternatives (HHD users) using Vlse Kriterijumska Optimizacija Kompromisno Resenje (VIKOR) technique. The outcomes of the BWM investigation showed that the three most significant risk factors responsible for MSDs are duration of working, poor working posture and un-ergonomic design. The outcome of the VIKOR technique exhibited that computer professionals were at the highest risk among all users. The risk factor priority must be used for designing a working strategy for the WFH situation which will help to mitigate the risks of MSDs.

Radiographers' experience of preventing patient safety incidents in the context of radiological examinations

AIM

To describe factors that prevent patient safety incidents in connection with the radiological examination from the radiographer's perspective.

BACKGROUND

Radiology plays an important role in the care chain and involves diagnostic examinations and treatments using various radiation sources and different techniques. Risks for patient safety incidents exist in every phase of a radiological examination. Appropriate use of medical imaging requires a multidisciplinary approach involving staff of different categories to meet the medical objectives and the patient's care needs. In accordance with a Safety-II approach, it is therefore important to understand why things go right and ensure that they do by supporting the conditions for right things to happen.

DESIGN

A qualitative study with a descriptive design.

METHODS

Semi-structured interviews were conducted with 17 radiographers. The data were analysed using theoretical thematic analysis based on the Systems Engineering Initiative for Patient Safety model.

RESULTS

The analysis yielded 20 sub-themes, which describe different success factors contributing to patient safety.

CONCLUSION

Proactive work should focus on collaboration and sharing the necessary knowledge, internally and externally, for care in connection with the radiological examination. The radiological and peri-radiographic knowledge should include monitoring the patient's safety needs before, during and after the radiological examination. The referring clinician has a central role in writing relevant referrals and the radiographer's competence is crucial in monitoring the patient's safety needs. A good patient safety culture is required and working with standards is important.

Hyperoside ameliorates TNF‑α‑induced inflammation, ECM degradation and ER stress‑mediated apoptosis via the SIRT1/NF‑κB and Nrf2/ARE signaling pathways in vitro

Intervertebral disc degeneration (IDD) is the main pathogenesis of numerous cases of chronic neck and back pain, and has become the leading cause of spinal-related disability worldwide. Hyperoside is an active flavonoid glycoside that exhibits anti-inflammation, anti-oxidation and anti-apoptosis effects. The purpose of the present study was to investigate the effect of hyperoside on tumor necrosis factor (TNF)-α-induced IDD progression in human nucleus pulposus cells (NPCs) and its potential mechanism. The activity and apoptosis of NPCs were detected by Cell Counting Kit-8 and flow cytometry analyses, respectively. The expression of interleukin (IL)-6 and IL-1β was detected with ELISA kits. Western blotting was used to detect the expression levels of proteins. The results showed that hyperoside effectively alleviated TNF-α-induced NPC apoptosis, and hyperoside treatment inhibited the upregulation of inducible nitric oxide synthase, cyclooxygenase-2, IL-1β and IL-6 in TNF-α-stimulated NPCs. Compared with the findings in the TNF-α group, the intervention of hyperoside attenuated the upregulated expression of aggrecan and collagen II, and downregulated the expressions of matrix metalloproteinase (MMP) 3, MMP13 and a disintegrin and metalloproteinase with thrombospondin motifs 5. In addition, hyperoside upregulated sirtuin-1 (SIRT1) and nuclear factor E2-related factor 2 (Nrf2) protein expression, and inhibition of SIRT1 or Nrf2 signaling reversed the protective effect of hyperoside on TNF-α-induced NPCs. In summary, hyperoside ameliorated TNF-α-induced inflammation, extracellular matrix degradation, and endoplasmic reticulum stress-mediated apoptosis, which may be associated with the regulation of the SIRT1/NF-κB and Nrf2/antioxidant responsive element signaling pathways by hyperoside.

Analysis of Grid Response Strategies for the Safety Behavior Risk Events of Transportation System Based on System Dynamics—“the Assistant Watchman Does Not Appear as Required”

Employees are the most important and dynamic elements in the railway transportation system. How to achieve accurate control of inertial violation of “key person, key matter, key period”, and formulate more personalized risk response strategy is a thorny problem that faced by safety managers. The existing risk response usually takes control measures from the perspective of the system as a whole, ignoring the heterogeneity of risk, and the selection of response strategies only considers the target risks to be dealt with, ignoring the secondary risks that may occur in the process of risk response, or the residual risks formed by changing the existing risk, coupled with the lack of quantitative evaluation of risk response effect, resulting in poor risk response effect. By introducing the grid theory and taking the risk event of “the assistant watchman does not appear as required” at Huangyangcheng station of Shenshuo Railway as an example, this study constructs a grid response model of the assistant watchman risk events based on system dynamics. Through the grid division, the model accurately locates and classifies the assistant watchman on duty. Then, during the system dynamics simulation process, the hazard factor is regarded as a bridge, and the traditional virtual boundary of system simulation is transformed into accurate grid definition. By improving the response strategy of safety behavior risk event of the assistant watchman on duty in cell grid and using Vensim-PLE software for personalized simulation, the intervention of “the assistant watchman does not appear as required” risk event is transformed from qualitative analysis to dynamic quantitative mathematical model, so as to realize the personalized response simulation analysis of employees in the grid.

A comprehensive method for the quantification of medication error probability based on fuzzy SLIM

Medication errors can endanger the health and safety of patients and need to be managed appropriately. This study aimed at developing a new and comprehensive method for estimating the probability of medication errors in hospitals. An extensive literature review was conducted to identify factors affecting medication errors. Success Likelihood Index Methodology was employed for calculating the probability of medication errors. For weighting and rating of factors, the Fuzzy multiple attributive group decision making methodology and Fuzzy analytical hierarchical process were used, respectively. A case study in an emergency department was conducted using the framework. A total number of 17 factors affecting medication error were identified. Workload, patient safety climate, and fatigue were the most important ones. The case study showed that subtasks requiring nurses to read the handwritten of other nurses and physicians are more prone to human error. As there is no specific method for assessing the risk of medication errors, the framework developed in this study can be very useful in this regard. The developed technique was very easy to administer.

A hybrid model integrating FMEA and HFACS to assess the risk of inter-city bus accidents

The incidence of inter-city bus accidents receives a lot of attention from the public because they often cause heavy casualties. The Human Factors Analysis and Classification System (HFACS) is the prevailing tool used for traffic accident risk assessment. However, it has several shortcomings, for example: (1) it can only identify the potential failure modes, but lacks the capability for quantitative risk assessment; (2) it neglects the severity, occurrence and detection of different failure modes; (3) it is unable to identify the degree of risk and priorities of the failure modes. This study proposes a novel hybrid model to overcome these problems. First, the HFACS is applied to enumerate the failure modes of inter-city bus operation. Second, the Z-number-based best–worst method is used to determine the weights of the risk factors based on the failure mode and effects analysis results. Then, a Z-number-based weighted aggregated sum product Assessment is utilized to calculate the degree of risk of the failure modes and the priorities for improvement. The results of this study determine the top three ranking failure modes, which are personal readiness from pre-conditions for unsafe behavior, human resources from organizational influence, and driver decision-making error from unsafe behavior. Finally, data for inter-city buses in Taiwan in a case study to illustrate the usefulness and effectiveness of the proposed model. In addition, some management implications are provided.

Human Factor Risk Modeling for Shipyard Operation by Mapping Fuzzy Fault Tree into Bayesian Network

The operational activities conducted in a shipyard are exposed to high risk associated with human factors. To investigate human factors involved in shipyard operational accidents, a double-nested model was proposed in the present study. The modified human factor analysis classification system (HFACS) was applied to identify the human factors involved in the accidents, the results of which were then converted into diverse components of a fault tree and, as a result, a single-level nested model was established. For the development of a double-nested model, the structured fault tree was mapped into a Bayesian network (BN), which can be simulated with the obtained prior probabilities of parent nodes and the conditional probability table by fuzzy theory and expert elicitation. Finally, the developed BN model is simulated for various scenarios to analyze the identified human factors by means of structural analysis, path dependencies and sensitivity analysis. The general interpretation of these analysis verify the effectiveness of the proposed methodology to evaluate the human factor risks involved in operational accidents in a shipyard.

A novel distance learning ergonomics checklist and risk evaluation methodology: A case of Covid-19 pandemic

Many governments decided to cancel face-to-face teaching and learning activities in schools and universities. They replaced them with online teaching and distance learning activities to prevent the spread of Coronavirus disease 2019 (COVID-19). Due to this sudden change, students experienced some anthropometric, environmental, and psychosocial difficulties at home during the distance learning process. This study focuses on determining the importance of anthropometric, environmental, and psychosocial factors in the distance learning process during the COVID-19 pandemic. This study presents main factors and their subfactors affecting ergonomic conditions of university students during distance learning. A novel distance learning ergonomics checklist is proposed based on the Occupational Safety and Health Administration checklists. The data are collected via a questionnaire filled by 100 university students who attend the Ergonomics course online. Then, the integrated methodology includes Voting Analytic Hierarchy Process integrated Pythagorean Fuzzy Technique for Order Preference by Similarity to An Ideal Solution method is adopted to prioritize the factors determined. Thirty-nine different subfactors are evaluated under five titles, and the most important factors are determined using the proposed methodology. With the results achieved, it is seen that the suggested checklist and proposed methodology can be used by public and private education organizations as a guide for improving their distance learning strategies.

An Investigation of Human Errors in Medication Adverse Event Improvement Priority Using a Hybrid Approach

The aim of this study was to analyze and provide an in-depth improvement priority for medication adverse events. Thus, the Human Factor Analysis and Classification System with subfactors was used in this study to analyze the adverse events. Subsequently, the improvement priority for the subfactors was determined using the hybrid approach in terms of the Analytical Hierarchy Process and the fuzzy Technique for Order of Preference by Similarity to Ideal Solution. In Of the 157 medical adverse events selected from the Taiwan Patient-safety Reporting system, 25 cases were identified as medication adverse events. The Human Factor Analysis and Classification System and root cause analysis were used to analyze the error factors and subfactors that existed in the medication adverse events. Following the analysis, the Analytical Hierarchy Process and the fuzzy Technique for Order of Preference by Similarity to Ideal Solution were used to determine the improvement priority for subfactors. The results showed that the decision errors, crew resource management, inadequate supervision, and organizational climate contained more types of subfactors than other error factors in each category. In the current study, 16 improvement priorities were identified. According to the results, the improvement priorities can assist medical staff, researchers, and decisionmakers in improving medication process deficiencies efficiently.

Developing a Multi-Criteria Decision Making approach to compare types of classroom furniture considering mismatches for anthropometric measures of university students

The mismatch between students’ anthropometric measures and school furniture dimensions have been investigated in many countries. In Iran, collegians spend at least a quarter of the day hours at university in the sitting position, so it is essential to evaluate furniture mismatch among university students. In Iranian universities, the use of chairs with an attached table is widespread, while the study of mismatches in these chairs among the collegian community is rare. This study was aimed to compare and rank different classroom furniture types based on the mismatch between collegians’ anthropometric measures and the dimensions of classroom furniture among Industrial Engineering students by developing a Multi-Criteria Decision Making approach in an integrated Methodology. The sample consisted of 111 participants (71 males, 40 females). Ten anthropometric measures were gathered, together with eight furniture dimensions for four types of chairs. Mismatch analyses were carried out using mismatch equations, and the Simple Additive Weighting method was used as a base method to solve the decision-making problem. The results indicated that Underneath Desk Height and Seat to Desk Clearance showed the highest levels of the match, while Seat Width presents the highest levels of low mismatch. According to the results, Type 1 and Type 3 were the best current classroom furniture. The Sensitivity Analysis was performed in two ways: changing the weights of criteria in nine scenarios and comparing the results with five other MCDM methods. The proposed MCDM approach can be used widely in furniture procurement processes and educational environments.

Relationship between safety measures and human error in the construction industry: working at heights

In recent years, falling from heights has been reported as the primary cause of fatalities within the Australian construction industry. While there is substantial literature exploring safety and human error in an attempt to decrease the occurrences of accidents through the implementation of organizational and physical hazard-related strategies, little attention has been brought towards the impact of psychological distress on the relationship between human error and safety measures. Therefore, this article aims at examining the relationship between safety measures and human error with the objective of identifying the impact of psychological distress among workers working at heights within the construction industry on the relationship. This study found that human error can occur as a result of psychological distress and therefore provides a foundation for future research to explore whether proper implementation of psychological safety measures could decrease the occurrence of human failures and accidents when working at heights.

An integrated offshore oil spill response decision making approach by human factor analysis and fuzzy preference evaluation

Human factors/errors (such as inappropriate actions by operators and unsafe supervision by organizations) are a primary cause of oil spill incidents. To investigate the influences of active operational failures and unsafe latent factors in offshore oil spill accidents, an integrated human factor analysis and decision support process has been developed. The system is comprised of a Human Factors Analysis and Classification System (HFACS) framework to qualitatively evaluate the influence of various factors and errors associated with the multiple operational stages considered for oil spill preparedness and response (e.g., oil spill occurrence, spill monitoring, decision making/contingency planning, and spill response); coupled with quantitative data analysis by Fuzzy Set Theory and the Technique for Order Preference by Similarity to Ideal Solution (Fuzzy-TOPSIS) to enhance decision making during response operations. The efficiency of the integrated human factor analysis and decision support system is tested with data from a case study to generate a comprehensive priority rank, a robust sensitivity analysis, and other theoretical/practical insights. The proposed approach improves our knowledge on the significance of human factors/errors on oil spill accidents and response operations; and provides an improved support tool for decision making.

Latent error detection: A golden two hours for detection

Undetected error in safety critical contexts generates a latent condition that can contribute to a future safety failure. The detection of latent errors post-task completion is observed in naval air engineers using a diary to record work-related latent error detection (LED) events. A systems view is combined with multi-process theories to explore sociotechnical factors associated with LED. Perception of cues in different environments facilitates successful LED, for which the deliberate review of past tasks within two hours of the error occurring and whilst remaining in the same or similar sociotechnical environment to that which the error occurred appears most effective. Identified ergonomic interventions offer potential mitigation for latent errors; particularly in simple everyday habitual tasks. It is thought safety critical organisations should look to engineer further resilience through the application of LED techniques that engage with system cues across the entire sociotechnical environment, rather than relying on consistent human performance.