Accident Causation Model Research Articles

Towards a unified model of accident causation: refining and validating the systems thinking safety tenets

The systems thinking tenets were developed based on a synthesis of contemporary accident causation theory, models and approaches and encapsulate 15 features of complex systems that interact to create both safety and adverse events. Whilst initial testing provided supportive evidence, the tenets have not yet been subject to formal validation. This article presents the findings from a three-round Delphi study undertaken to refine and validate the tenets and assess their suitability for inclusion in a unified model of accident causation. Participants with expertise in accident causation and systems thinking provided feedback on the tenets and associated definitions until an acceptable level of consensus was achieved. The results reduced the original 15 tenets to 14 and 10 were identified as important to include in unified model of accident causation. The refined systems thinking tenets are presented along with future research directions designed to facilitate their use in safety practice. Practitioner summary: This article presents a refined and validated set of systems thinking tenets which describe features of complex systems that interact to create adverse events. The tenets can be used by practitioners to proactively identify safety leading indicators and contributory factors during adverse event analysis.

Fatal fall incidents in the Indian construction industry: a case study analysis

The fall from height fatal accident rate is higher than those of other accidents in the construction sector because of work-related causes. The purpose of this study was to investigate the causal factors of fatal fall incidents in the Indian construction industry. This study adopted a three-level accident causation model developed by Loughborough University researchers, aiming to identify immediate circumstances, shaping factors and originating influences in selected incidents. The accident cases were retrieved from police records and government documents. Accident data from 2019 to 2020 were studied, and specific emphasis was placed on fatal fall events. These events were subjected to content review to determine causal factors. In total, ten fatal fall cases were analysed in which immediate circumstances were established for all the cases that involved the use of unsafe methods of work. In some cases, shaping factors were identified as possible contributors to the events, such as the work process nature and team members’ communication. Originating influences could not be established in any of the cases. The study findings could give a more comprehensive qualitative insight into the causal factors of fatal fall accidents, which could alert stakeholders in developing safety programmes and providing effective fall preventive measures.

Hazard identification, risk assessment and management of industrial system: Process safety in mining industry

Hazard identification, risk assessment and management are of great significance for the safe and efficient production of industrial system. However, due to the lack of quantitative methods, the production of industrial systems still lacks safety guarantees. Firstly, we revise the accident causation model of mining industry based on the “Swiss-Cheese” model and construct a three-dimensional multi-granular structure model applied to the mining industry. To identify hazards of mining industry, a multi-layer hierarchical structure model and a system safety assessment model are established according to finite covering theorem. Then, the hazard identification is carried out based on the multi-layer hierarchical model and the risk matrix method, and a quantitative method is proposed to calculate the process indicators. Subsequently, the weighted grey relational analysis method is used for risk assessment on the driving system in mining industry. To improve the safety level of the driving system, the Hazard Identification-Assessment-Check-Action risk closed-loop management mode is used for risk management in the purpose of obtaining hazard rectification measures. Risk assessment is carried out again after risk rectification, and the safety level of the driving system can reach higher level. This research can provide guidance for the process safety improvement of industrial systems.

Stakeholder perspectives of system-related errors: Types, contributing factors, and consequences

BackgroundDespite growing evidence of the benefits of electronic medication management systems (EMMS), research has also identified a range of new safety risks linked with their use. There is limited qualitative research focusing on system-related errors that result from use of EMMS. The aim of this study was to explore in-depth stakeholders’ perceptions and experiences of system-related errors. MethodsSemi-structured interviews were conducted with EMMS users and other relevant staff (e.g. supporting roles in EMMS) across a local health district in Sydney, Australia. Analysis was conducted iteratively using a general inductive approach, and then mapped to Reason’s accident causation model, where codes were categorized as 1) unsafe acts (i.e. what error occurred), 2) latent conditions (i.e. what factors contributed to errors), and 3) consequences resulting from the error. ResultsTwenty-five participants were interviewed between September 2020 and May 2021. Participants most frequently described omission errors (e.g. failure to check for duplicate orders) as unsafe acts, although commission errors and workarounds were also reported. Poor EMMS design was reported to be a significant workplace factor contributing to system-related errors, however participants also described user factors, such as an overreliance on the system, and organizational factors, such as system downtime, as contributing to errors. Reported consequences of system-related errors included medication errors, but also impacts to the EMMS and on workers. ConclusionsEMMS design is a significant contributor to system-related errors, but this research showed that user and organizational factors are also at play. As these factors are not independent, minimizing system-related errors requires a multi-faceted approach, where mitigation strategies target not only the EMMS, but also the context in which the system has been implemented.

A Causation Analysis of Chinese Subway Construction Accidents Based on Fault Tree Analysis-Bayesian Network.

Clarifying the causes of subway construction accidents has an important impact on reducing the probability of accidents and protecting workers’ lives and public property to a greater extent. A total of 138 investigation records of subway construction accidents from 2000 to 2020 were collected in this study. Based on a systemic analysis of 29 well-known accident causation models and the formative process of the subway construction accidents, we extracted the causative factors of subway construction accidents from the collected records. Furthermore, a causation analysis index system of subway accidents was proposed based on fault tree analysis (FTA), where we considered subway construction accidents as the top event and the five dimensions, i.e., human, equipment, environment, management, and safety culture, as first-level intermediate events. Moreover, 17 causative factors were considered to be related to the severity of subway construction accidents. It is found that human factors are prone to be critical to high-risk accidents. Finally, a Bayesian network (BN) was formed to explore the causative factors of high-risk subway construction accidents. Based on the combined application of FTA and BN, this study discusses the complex influence factors and their action routes to unsafe accidents in subway construction sites, and makes efforts to correspond safety decision basis for the management of China subway construction.

Accident causation models: A comparison of SCM and 24Model

The Swiss Cheese Model (SCM) and 24Model have proved over the years to be lasting influences for many researchers and practitioners in various safety areas. However, as one practical tool for accident analysis, a gap still exists for whether these two models are consistent in current studies. A theoretical comparison of these two models to reveal constructive foundation, related concepts, correspondence to each level of cause-effect and characteristics of sub modules were presented. The basic structure of the two modular models is consistent and each sub module can match. The foundation of the two models is different, reflecting the differences between Eastern and Western cultures. 24Model overcomes the fuzziness of SCM model classification and divides organizational factors into two stages: safety management system and safety culture and refines the meaning of accident and hazard. Hazard identification based on SCM is presented at the design and commissioning of the system, while the identification of 24Model following PDCA cycle, which is an continuous improvement throughout the entire life cycle of the system. In conclusion, 24Model is a deepening and development of SCM, and explicit taxonomy for individual and organization is proposed by integrating factors on SCM. The comparisons will build a bridge of communication and exchange between East and West accident causation theories and will lead to more knowledge of the causes to the accident, placing focus on need for improved organizational behaviors, more efficient safety management systems and safety culture in companies.

Incident reporting in the outdoors: a systems-based analysis of injury, illness, and psychosocial incidents in led outdoor activities in Australia

Incident reporting systems are a fundamental component of safety management, however, most systems used in practice are not aligned with contemporary accident causation models. This article presents an analysis of a National Incident Dataset (NID) for adverse incidents occurring in the Australian Led Outdoor Activity (LOA) sector. The aim was to investigate the adverse Injury, Illness, and Psychosocial incidents reported to the NID. In total, 1657 injuries, 532 illnesses, and 146 psychosocial incidents were analysed from 357,691 program participation days. The findings show that the rate of incidents per 1000 program participant days in LOAs was 4.6 for injury, 1.5 for illness, and 0.04 for psychosocial incidents, and incident severity was predominately minor. The analysis of systemic contributory factors demonstrates that incidents in LOA are systemic in nature, with multiple levels of the LOA system identified as contributing to adverse incidents. For example, contributory factors were identified across local government (facilities), schools (communication), parents (communication), LOA management (policies and procedures), people involved in the incidents (mental and physical condition), and the environment (terrain) and equipment (clothing). This study presents an assessment of the current state of safety in the Australian LOA sector and demonstrates the utility of applying systems ergonomics methods in practice. Practitioner summary: This article presents an analysis of 1657 injury, 532 illness, and 146 psychosocial incidents occurring in the Australian Led Outdoor Activity (LOA) sector, using a systems ergonomics method. The findings demonstrate the incident charactersitics and how decisions and actions from across the system contribute to adverse incidents in LOAs.

A new accident causation theory based on systems thinking and its systemic accident analysis method of work systems

Major accidents such as the Space Shuttle Challenger disaster in the USA, the Bhopal Disaster in India, the Fukushima nuclear accident in Japan, and the Tianjin Port fire and explosion accident in China, have occurred all over the world. Safety scientists are always trying to understand why these accidents happened and how to prevent these accidents. Accident models and theories form the basis for many safety research fields and practices. However, there is no universally accepted model with useful elements relating to understanding accident causation, although many accident causation models exist. A new accident causation theory named the Interaction Theory of Hazard-Target System (ITHTS) is proposed based on Systems-Theoretic Accident Model and Processes (STAMP) and Risk Management Framework (RMF), which not only incorporates human, organisational and technological characteristics in the same framework, but also considers the sociological factors such as legislative, regulatory, and cultural factors. On the other hand, a new systemic accident analysis method of work systems (SAAMWS) is proposed based on ITHTS and STAMP because ITHTS cannot be applied directly in accident analysis. We choose Tianjin Port fire and explosion accident as a case study to demonstrate the explanatory power of Interaction Theory of Hazard-target System and the feasibility of the new accident analysis method. Further research needs to be done to assess the reliability and validity of this new systemic accident analysis method.

Uncertainty analysis of accident causality model using Credal Network with IDM method: A case study of hazardous material road transportation accidents

Bayesian network (BN) is an effective tool for causal inferences of accidents. However, it is often criticized for the difficulty in obtaining accurate/sufficient data needed to get precise probability numbers, and expert knowledge is necessary on this occasion. Such numbers provided by experts lead to great cognitive uncertainty in the model. Credal Network (CN), regarded as an extension of BN, uses imprecise probabilities to well express the cognitive uncertainty, but how to give the available interval probability is a key issue in its application. In this paper, a CN model based on Imprecise Dirichlet Model (IDM) is proposed to solve this problem, and a case study of hazardous material road transportation accidents (HMRTAs) is conducted. Firstly, based on the accident causation model, the CN topology is established by analyzing 30 investigation reports of HMRTAs in China. Secondly, the conditional probability table is calculated and then the CN model of HMRTAs is obtained by transforming the point probability into interval probability using IDM. Finally, causes and consequences of HMTRAs are analyzed. The results show that the method in this study can well represent the uncertainty propagation in the accident causal model and provide a new way for accident risk analysis.

Effects of an engaging maintenance task on fire evacuation delays and presence in virtual reality

The current study aims to investigate the capability of occupants of a powerhouse simulation to sense a fire and initiate evacuation while engaged with a task. For this reason, the study involved the maintenance task of replacing the air filter of a gas-powered engine through a series of instructions. The virtual reality-based accident causation model (VR-ACM) consisting of 3D modeling and simulation, accident causation, and safety training was adapted to address the study's aims. Two groups of participants were immersed in the virtual realm as occupants of the powerhouse to determine the pre-movement time and the evacuation duration under distinct scenarios. The first scenario constituted the experimental group (n = 26), who were assigned to replace the filters, while the second scenario (control n = 26) performed no task before the fire outbreak. An independent samples t-test revealed a significant difference in the pre-movement time of the groups, which suggested a decline in the perception of the experimental group due to the task. Further assessment revealed a consequential transfer of the delay at the pre-movement phase to the evacuation delay of the experimental group from the powerhouse. Secondly, the differences in interactivity implied that the experimental group exhibited a higher level of involvement and distraction in the Presence measurement than the control group. To this end, a virtual reality (VR) environment's performance and real-time functionality during a maintenance task simulation have been experimented with in an emergency fire evacuation scenario to ascertain safety concerns.

Analysis of accidents through combination of CAST and TRACEr techniques: A case study

This article presents a methodology for accident analysis developed from the combination of CAST - Causal Analysis based on System Theory, derived from the STAMP (Systems-Theoretic Accident Model and Process) accident causation model and the human error analysis/investigation tool TRACEr (Technique for the Retrospective and Predictive Analysis of Cognitive Errors). This combination was proposed from the perceived need to structure one of the stages of the application of the CAST technique where unsafe control actions, or human errors, that occurred in the course of accidental events are analyzed, for which the application of the TRACEr technique proved extremely useful. From the application of the proposed combination to an accident that occurred in an oil production unit in operation on the coast of southeastern Brazil, it was possible to obtain a deeper understanding of the psychological phenomena that preceded one of the unsafe control actions, as well as the identification of performance shaping factors that contributed to its occurrence. These results demonstrated the conceptual cohesion and mutual complementarity of the associated techniques, which allowed a comprehensive understanding of the accidental event and, consequently, the elaboration of safety recommendations more appropriate to the findings of the analysis, better specified to the aspects of human factors involved.

An integrated safety and security analysis for cyber-physical harm scenarios

Increasing digitalization and autonomous solutions in physical systems promise to enhance their performance, cost-efficiency and reliability. However, the integration of novel information technologies with safety-related systems also brings new vulnerabilities and risks that challenge the traditional field of safety analysis. Particularly, cyber security threats are becoming key factors in complex accident scenarios in cyber-physical systems (CPSs), where unintentional errors and design flaws overlap with cyber security vulnerabilities that could lead to harm to humans and assets. This overlap between safety and security analysis is still a loosely defined domain without established theories and methods, leading to complications during the risk analysis of CPSs. In this paper, we first describe how the domain of safety science increasingly overlaps with security analysis. Subsequently, based on this overlapping, we illustrate and complement an integrated method for the identification of harm scenarios in CPSs. This method, coined Uncontrolled Flows of Information and Energy (UFoI-E), offers a distinct theoretical foundation rooted in accident causation models and a framework to design diagrammatic representations of CPSs during the analysis. After summarizing these features of the UFoI-E method, we present our original contribution to the method, which is a new practical toolkit for risk identification composed of an ontology of harm scenarios and a database of checklists built from lessons learned analysis and expert knowledge. Finally, we demonstrate an application of the method in an illustrative case and show representative fields for future work.

DEEP SCOPE: A Framework for Safe Healthcare Design.

Thinking in patient safety has evolved over time from more simplistic accident causation models to more robust frameworks of work system design. Throughout this evolution, less consideration has been given to the role of the built environment in supporting safety. The aim of this paper is to theoretically explore how we think about harm as a systems problem by mitigating the risk of adverse events through proactive healthcare facility design. We review the evolution of thinking in safety as a safety science. Using falls as a case study topic, we use a previously published model (SCOPE: Safety as Complexity of the Organization, People, and Environment) to develop an expanded framework. The resulting theoretical model and matrix, DEEP SCOPE (DEsigning with Ergonomic Principles), provide a way to synthesize design interventions into a systems-based model for healthcare facility design using human factors/ergonomics (HF/E) design principles. The DEEP SCOPE matrix is proposed to highlight the design of safe healthcare facilities as an ergonomic problem of design that fits the environment to the user by understanding built environments that support the “human” factor.

Direct oral anticoagulant-related medication incidents and pharmacists\u2019 interventions in hospital in-patients: evaluation using reason\u2019s accident causation theory

Background Direct oral anticoagulants (DOACs) have revolutionised anticoagulant pharmacotherapy. However, DOAC-related medication incidents are known to be common. Objective To assess medication incidents associated with DOACs using an error theory and to analyse pharmacists’ contributions in minimising medication incidents in hospital in-patients. Setting A large University academic hospital in the West Midlands of England. Methods Medication incident data from the incident reporting system (48-months period) and pharmacists’ interventions data from the prescribing system (26-month period) relating to hospital in-patients were extracted. Reason’s Accident Causation Model was used to identify potential causality of the incidents. Pharmacists’ intervention data were thematically analysed. Main outcome measure (a) Frequency, type and potential causality of DOAC-related incidents; (b) nature of pharmacists’ interventions. Results A total of 812 reports were included in the study (124 medication incidents and 688 intervention reports). Missing drug/omission was the most common incident type (26.6%, n = 33) followed by wrong drug (16.1%, n = 20) and wrong dose/strength (11.3%, n = 14). A high majority (89.5%, n = 111) of medication incidents were caused by active failures. Patient discharge without anticoagulation supply and failure to restart DOACs post procedure/scan were commonly recurring themes. Pharmacists’ interventions most frequently related to changes in pharmacological strategy, including drug or dose changes (38.1%, n = 262). Impaired renal function was the most common reason for dose adjustments. Conclusion Prescribers’ active failure rather than system errors (i.e. latent failures) contributed to the majority of DOAC-related incidents. Reinforcement of guideline adherence, prescriber education, harnessing pharmacists’ roles and mandating renal function information in prescriptions are likely to improve patient safety.

문헌조사에 근거한 인적 처벌 중심 안전 접근의 학술적 배경, 한계점 및 개선 방안

Objective: This study aimed to investigate backgrounds and limitations of personal punishment-oriented safety approach from an academic point of view and to propose its improvement measures.BRBRBackground: The complexity of socio-technical systems which are comprised of interacting human, technological and environmental components has ever-increased, which resulted in change in accident causation mechanism. Consequently, the traditional blame-oriented safety approach should be changed.BRBRMethod: This study was based on the literature survey, via a search of the ScienceDirect and Scopus using the keywords: accident causation model, accident investigation technique, and system safety.BRBRResults: Backgrounds for blaming-oriented safety approach were summarized in viewpoint of the safety-I, domino theory and hindsight bias. The approach was necessary and helpful to learn from and prevent accidents or incidents in relatively simple systems of the past. Its limitations were revealed and presented from the perspective of the safety-II, domino theory, accident pyramids, characteristics of complex socio-technical systems, hindsight bias, and change of safety paradigm. This showed that the traditional approach would not prevent a recurrence of accidents in complex socio-technical systems, unless underlying causes across the systems were addressed.BRBRConclusion: Based on the results, it was suggested that to raise the level of safety, the safety approach should be shifted from traditional safety-I to safety-II.BRApplication: The results of this study will provide academic backgrounds for changing safety approach.

A state of the art of the accident causation models in the process industries

AbstractThe comprehensive review of research literature in accordance with the implementations of the accident causation models enables knowledge incomes for the contributing authors towards the advancement of the accident causation methodologies for administering the accidents' causal factors. For obtaining this objective, the systematic literature review meta‐analysis are developed by evaluating the parameter indicator linked to the most utilized causation methods in addressing the contributing factors in process industries. The methodological review process called preferred reporting items for systematic reviews and meta‐analyses (PRISMA) is implemented in this paper due to its capability to integrate both systematic reviews and meta‐analysis. This systematic literature review deeply investigates 149 papers by a thorough reading from the filtered 387 manuscripts published in the academic SCOPUS databases during 1980–2020. Additionally, the statistical analysis t test is performed to identify the homogeneity of literature papers resulting from research conclusions. The suggested future improvement in the domain of accident causation models is the advancement of administering the accident causal factors' values of correlations and interdependencies. While particularly for quantified accident causation models, the adoption of uncertainty analysis needs to further developed as a research suggestion in the future.

Knowledge discovery of correlations between unsafe behaviors within construction accidents

PurposeKnowledge discovery related to unsafe behaviors promotes the performance of accident prevention in construction. Although numerous studies on accident causation models have discussed the correlations of unsafe behaviors with various factors (e.g., unsafe conditions), limited research explores correlations between unsafe behaviors within accidents. The purpose of this paper is mining strong association rules of unsafe behaviors from historical accidents to clarify this kind of tacit knowledge.Design/methodology/approachA case study was adopted as the research approach, in which accident records from building and urban railway construction in China were selected as data resources. The groups of unsafe behaviors extracted from accident records were expressed by the definitions of unsafe behaviors from safety regulations and operating procedures. Frequent Pattern (FP)-Growth algorithm was used for association rule mining, and the critical correlations between unsafe behaviors were represented by the effective strong rules.FindingsThe findings identify and distinguish correlations between unsafe behaviors within construction accidents. In building construction, workers and managers should pay attention to preventing unsafe behaviors related to personal protective equipment and machines and equipment. In urban railway construction, workers should especially avoid unsafe behaviors of inadequately dealing with environmental factors.Practical implicationsTacit knowledge is transferred to explicit knowledge as the critical correlations between unsafe behaviors within accidents are determined by the effective strong rules. Additionally, the findings provide practice guidance for safety management, to collaboratively control unsafe behaviors with strong correlations.Originality/valueThis study contributes to the body of safety knowledge in construction and provides a further understanding of how construction accidents are caused by multiple unsafe behaviors.

Dynamic Inherently Safer Modifications: Metric development and its validation for fire and explosion prevention

Of the numerous inherent safety assessment tools, a dynamic metric capable of investigating and incorporating the temporal risk evolution when conducting Inherently Safer Modifications (ISMs) is yet to be established. To this end, this work developed a Dynamic Inherent Safety Metric (DISM) and validated its functionality and viability through a case study. Firstly, the Information-Flow-based Accident-causing Model (IFAM) was adapted to construct the topology of Bayesian Networks (BN). Then, Bayesian deductive reasoning was executed to do crucial risk identification by ranking posterior probabilities. Finally, risk-based ISMs were performed to address the relatively contributing risk factors. The case study results show that the fire and explosion risk decreased by approximately a third after implementing ISMs, thus demonstrating that the modified processing scenario could be inherently safer than the original processing scenario. The newly developed inherent safety metric (i.e., DISM) can assist in temporal risk identification and assessment, and it is expected to function as a novel assessment tool for measuring and comparing the inherent safeness before and after implementing ISMs with simultaneous considerations on the time-varying risk factors.

Understanding the "Swiss Cheese Model" and Its Application to Patient Safety.

This article reviews several key aspects of the Theory of Active and Latent Failures, typically referred to as the Swiss cheese model of human error and accident causation. Although the Swiss cheese model has become well known in most safety circles, there are several aspects of its underlying theory that are often misunderstood. Some authors have dismissed the Swiss cheese model as an oversimplification of how accidents occur, whereas others have attempted to modify the model to make it better equipped to deal with the complexity of human error in health care. This narrative review aims to provide readers with a better understanding and greater appreciation of the Theory of Active and Latent Failures upon which the Swiss cheese model is based. The goal is to help patient safety professionals fully leverage the model and its associated tools when performing a root cause analysis as well as other patient safety activities.

Simulation-based assessments of fire emergency preparedness and response in virtual reality

The current study aimed at evaluating the prospects of a three-dimensional gas power plant (GPP) simulation in an immersive virtual reality (IVR) environment for fire emergency preparedness and response (EPR). To achieve this aim, the study assessed the possibility of safety situational awareness, evacuation drills and hazard mitigation exercises during a fire emergency simulation scenario. The study likewise evaluated the safety and ergonomics of the environment while addressing this aim. We employed the virtual reality accident causation model (VR-ACM) for the assessment with 54 participants individually in IVR. Participants were grouped into two according to whether they had work experience in engineering or not. The obtained results suggested that IVR can be realistic and safe, with the potential for presenting hazardous scenarios necessary for fire EPR. Furthermore, the results indicated that there were no statistically significant differences in the perceptions of both groups regarding the prospects of IVR towards EPR.