A novel framework for human factors analysis and classification system for medical errors (HFACS-MES)-A Delphi study and causality analysis.

The healthcare system (HCS) is one of the most crucial and essential systems for humanity. Currently, supplying the patients' safety and preventing the medical adverse events (MAEs) in HCS is a global issue. Human and organizational factors (HOFs) are the primary causes of MAEs. However, there are limited analytical methods to investigate the role of these factors in medical errors (MEs). The aim of present study was to introduce a new and applicable framework for the causation of MAEs based on the original HFACS. In this descriptive-analytical study, HOFs related to MEs were initially extracted through a comprehensive literature review. Subsequently, a Delphi study was employed to develop a new human factors analysis and classification system for medical errors (HFACS-MEs) framework. To validate this framework in the causation and analysis of MEs, 180 MAEs were analyzed by using HFACS-MEs. The results showed that the new HFACS-MEs model comprised 5 causal levels and 25 causal categories. The most significant changes in HFACS-MEs compared to the original HFACS included adding a fifth causal level, named "extra-organizational issues", adding the causal categories "management of change" (MOC) and "patient safety culture" (PSC) to fourth causal level", adding "patient-related factors (PRF)" and "task elements" to second causal level and finally, appending "situational violations" to first causal level. Causality analyses among categories in the HFACS-MEs framework showed that the new added causal level (extra-organizational issues) have statistically significant relationships with causal factors of lower levels (Φc≤0.41, p-value≤0.038). Other new causal category including MOC, PSC, PRF and situational violations significantly influenced by the causal categories of higher levels and had an statistically significant effect on the lower-level causal categories (Φc>0.2, p-value<0.05). The framework developed in this study serves as a valuable tool in identifying the causes and causal pathways of MAEs, facilitating a comprehensive analysis of the human factors that significantly impact patient safety within HCS.

Evaluating Independent Double Checks in the Pediatric Intensive Care Unit: A Human Factors Engineering Approach.

OBJECTIVES: The goal of this human factors engineering-led improvement initiative was to examine whether the independent double check (IDC) during administration of high alert medications afforded improved patient safety when compared with a single check process. METHODS: The initiative was completed at a 24-bed pediatric intensive care unit and included all patients who were on the unit and received a medication historically requiring an IDC. The total review examined 37,968 high-risk medications administrations to 4417 pediatric intensive care unit patients over a 40-month period. The following 5 measures were reviewed: (1) rates of reported medication administration events involving IDC medications; (2) hospital length of stay; (3) patient mortality; (4) nurses' favorability toward single checking; and (5) nursing time spent on administration of IDC medications. RESULTS: The rate of reported medication administration events involving IDC medications was not significantly different across the groups (95% confidence interval, 0.02%-0.08%; P = 0.4939). The intervention also did not significantly alter mortality ( P = 0.8784) or length of stay ( P = 0.4763) even after controlling for the patient demographic variables. Nursing favorability for single checking increased from 59% of nurses in favor during the double check phase, to 94% by the end of the single check phase. Each double check took an average of 9.7 minutes, and a single check took an average of 1.94 minutes. CONCLUSIONS: Our results suggest that performing independent double checks on high-risk medications administered in a pediatric ICU setting afforded no impact on reported medication events compared with single checking.

Research on safety supervision and management system of China railway based on association rule and DEMATEL.

Safety management is a key issue in the railroad industry that needs to be continuously focused on. And it is essential to study causes of accidents for preventing accidents. However, there is a limited academic discussion on the systematic study of organizations and accidents, as well as their safety-related interactions and accidents, as opposed to human-caused disasters. Thus, the model of China's railway safety supervision and management system by sorting out the existing organizations involved in management in China is established in this paper. Firstly, social forces and auxiliary enterprises are specifically added to the model. And then, the relationship between organizations and accidents, as well as the relationship between safety interactions among organizations and accidents are explored by analyzing 224 accident reports, which led to 4 principles for accident prevention. Finally, based on these principles, measures to secure organizational nodes, as well as measures to promote safe interactions among organizations are proposed. The results showed that: (1) China Railway node is not only the most critical node in the safety supervision and management system but also the most vulnerable to the influence of other nodes. (2) The accident occurred due to the simultaneous occurrence of an accident at the China Railway node and the social force node. (3) When there are often safety risks in auxiliary enterprises and social forces simultaneously, the government's management is likely to be defective. The findings in this study can provide helpful references not only for improvement of safety management system structure and supervision and management mechanism but also for the formulation of safety supervision and management policies in China and other countries.

A Bibliometric Analysis of Neuroscience Tools Use in Construction Health and Safety Management.

Despite longstanding traditional construction health and safety management (CHSM) methods, the construction industry continues to face persistent challenges in this field. Neuroscience tools offer potential advantages in addressing these safety and health issues by providing objective data to indicate subjects' cognition and behavior. The application of neuroscience tools in the CHSM has received much attention in the construction research community, but comprehensive statistics on the application of neuroscience tools to CHSM is lacking to provide insights for the later scholars. Therefore, this study applied bibliometric analysis to examine the current state of neuroscience tools use in CHSM. The development phases; the most productive journals, regions, and institutions; influential scholars and articles; author collaboration; reference co-citation; and application domains of the tools were identified. It revealed four application domains: monitoring the safety status of construction workers, enhancing the construction hazard recognition ability, reducing work-related musculoskeletal disorders of construction workers, and integrating neuroscience tools with artificial intelligence techniques in enhancing occupational safety and health, where magnetoencephalography (EMG), electroencephalography (EEG), eye-tracking, and electrodermal activity (EDA) are four predominant neuroscience tools. It also shows a growing interest in integrating the neuroscience tools with artificial intelligence techniques to address the safety and health issues. In addition, future studies are suggested to facilitate the applications of these tools in construction workplaces by narrowing the gaps between experimental settings and real situations, enhancing the quality of data collected by neuroscience tools and performance of data processing algorithms, and overcoming user resistance in tools adoption.

Improvement of road safety management systems of local governments in Korea after evaluating related indicators.

This study analyzes what has changed in the road safety management systems (RSMS) of local governments after evaluating the related indicators continuously from 2015 to 2019. It has evaluated 24 indicators in four areas of RSMS such as institutional management, intervention, intermediate outcome, and the final outcome, according to Han and Lee (2020). It seems that continuous evaluation of indicators of RSMSs in local governments for five years has helped to improve road safety performance in local governments. The result shows that the average overall scores have increased from 77.92 to 83.89, a 7.7% increase. This improvement should have resulted from the competition between local governments, which do not want to be at the bottom in the score comparison. The most remarkable increase has been identified in the areas of institutional management and intervention. They have increased by 13.3% and 16.0%, respectively. In terms of types of local governments, it has been found that the increase in overall scores is higher in provinces which include most rural areas than in metropolitans. However, it has been found that the improvement of institutional management and interventions are not directly associated with the increase of the intermediate and final outcomes, at least during the five years. Further studies examining the relationship between the four areas of RSMS are needed.

Study on the Interaction Behaviors Identification of Construction Workers Based on ST-GCN and YOLO.

The construction industry is accident-prone, and unsafe behaviors of construction workers have been identified as a leading cause of accidents. One important countermeasure to prevent accidents is monitoring and managing those unsafe behaviors. The most popular way of detecting and identifying workers' unsafe behaviors is the computer vision-based intelligent monitoring system. However, most of the existing research or products focused only on the workers' behaviors (i.e., motions) recognition, limited studies considered the interaction between man-machine, man-material or man-environments. Those interactions are very important for judging whether the workers' behaviors are safe or not, from the standpoint of safety management. This study aims to develop a new method of identifying construction workers' unsafe behaviors, i.e., unsafe interaction between man-machine/material, based on ST-GCN (Spatial Temporal Graph Convolutional Networks) and YOLO (You Only Look Once), which could provide more direct and valuable information for safety management. In this study, two trained YOLO-based models were, respectively, used to detect safety signs in the workplace, and objects that interacted with workers. Then, an ST-GCN model was trained to detect and identify workers' behaviors. Lastly, a decision algorithm was developed considering interactions between man-machine/material, based on YOLO and ST-GCN results. Results show good performance of the developed method, compared to only using ST-GCN, the accuracy was significantly improved from 51.79% to 85.71%, 61.61% to 99.11%, and 58.04% to 100.00%, respectively, in the identification of the following three kinds of behaviors, throwing (throwing hammer, throwing bottle), operating (turning on switch, putting bottle), and crossing (crossing railing and crossing obstacle). The findings of the study have some practical implications for safety management, especially workers' behavior monitoring and management.

Multifaceted Intervention to Improve Patient Safety Incident Reporting in Intensive Care Units.

OBJECTIVES: Patient safety incident reporting in our institution's intensive care units (ICUs) had fallen 30% below national benchmarks during the COVID-19 pandemic. Underreporting diminishes awareness of risks and precludes organizational learning from near misses. We aimed to increase the ICU number of patient safety incident reports by 30% from 27 to 35 reports/1000 patient-days without negatively impacting culture of safety as measured by patient-care staff surveys. METHODS: Single-institution prospective interventional study with 9 ICUs receiving a multifaceted intervention developed using quality improvement methodology during February-April 2022. Study intervention involved creation of patient safety peer-leadership role, feedback process, interactive dashboards for patient safety data, and education resources accessible via quick response codes. Primary outcome was patient safety incident reports/1000 patient-days. Intensive care unit patient-care staff culture of safety was assessed with surveys. RESULTS: Intensive care unit patient safety incident reporting increased by 48% after intervention (40 versus 27 reports/1000 patient-days [ P = 0.136]). Near misses were the most common incident report. Intensive care unit patient-care staff ratings of patient safety did not change; 80% rated patient safety as good or better after intervention versus 78% at baseline ( P = 0.465). However, significant improvement was observed for subcomponents related to learning culture and support for staff involved in patient safety incidents. Most reports (>80%) were submitted by nurses. CONCLUSIONS: This multifaceted quality improvement intervention increased patient safety incident reporting in the ICUs. Increases in ratings of learning culture and support for staff underline the importance of a well-functioning patient safety incident reporting system in an institutional culture of safety.

Evaluating the effectiveness of strategies for implementation of health and safety programs on construction sites in Nigeria: A mixed-method study.

INTRODUCTION: Empirical and anecdotal evidence show that construction projects are delivered on work sites where unsafe acts and conditions abound. Researchers have investigated the strategies that can be adopted to effectively implement health and safety (H&S) in projects so as to reduce the high rates of accidents, injuries and fatalities. However, the effectiveness of these strategies have not been marginally established. Therefore, this study established the effectiveness of H&S implementation strategies on accidents, injuries, and fatalities reduction in Nigerian construction projects. METHOD: A mixed-method research design was adopted for data collection in the study. Physical observations, interviews, and a questionnaire were the instruments used for data collection in the mixed-method research design. RESULTS: The resultant data identified six appropriate strategies for enabling the desired levels of H&S program implementation on construction sites. Setting up statutory bodies such as the Health and Safety Executive to promote awareness, good practices, and standardization was adjudged pertinent as one of the effective H&S implementation programs that can be used to reduce accidents, incidents, and fatalities in projects. It is expected that the adoption of these strategies would culminate in effective H&S program implementation and subsequently a reduction in the prevalence of accidents, injuries, and fatalities in projects.

The Relationship Between Patient Safety Culture and the Intentions of the Nursing Staff to Report a Near-Miss Event During the COVID-19 Crisis.

BACKGROUND: Reporting a near-miss event has been associated with better patient safety culture. PURPOSE: To examine the relationship between patient safety culture and nurses' intention to report a near-miss event during COVID-19, and factors predicting that intention. METHODS: This mixed-methods study was conducted in a tertiary medical center during the fourth COVID-19 waves in 2020-2021 among 199 nurses working in COVID-19-dedicated departments. RESULTS: Mean perception of patient safety culture was low overall. Although 77.4% of nurses intended to report a near-miss event, only 20.1% actually did. Five factors predicted nurses' intention to report a near-miss event; the model explains 20% of the variance. Poor departmental organization can adversely affect the intention to report a near-miss event. CONCLUSIONS: Organizational learning, teamwork between hospital departments, transfers between departments, and departmental disorganization can affect intention to report a near-miss event and adversely affect patient safety culture during a health crisis.

Investigation of Unsafe Acts Influence Law Based on System Dynamics Simulation: Thoughts on Behavior Mechanism and Safety Control.

In modern safety management, it is very important to study the influence of the whole safety system on unsafe acts in order to prevent accidents. However, theoretical research in this area is sparse. In order to obtain the influence law of various factors in the safety system on unsafe acts, this paper used system dynamics simulation to carry out theoretical research. First, based on a summary of the causes of the coal and gas outburst accidents, a dynamic simulation model for unsafe acts was established. Second, the system dynamics model is applied to investigate the influence of various safety system factors on unsafe acts. Third, the mechanism and the control measures of unsafe acts in the enterprise safety system are studied. This study's main result and conclusions are as follows: (1) In the new coalmines, the influence of the safety culture, safety management system, and safety ability on the safety acts were similar. The order of influence on the safety acts in production coalmines is as follows: safety management system > safety ability > safety culture. The difference is most evident in months ten to eighteen. The higher the safety level and safety construction standard of the company, the greater the difference. (2) In the construction of the safety culture, the order of influence was as follows: safety measure elements > safety responsibility elements = safety discipline elements > safety concept elements. It shows the difference in influence from the 6th month and attains its maximum value from the 12th month to the 14th month. (3) In the construction of the safety management system, the degree of influence in new coalmines was as follows: safety policy > safety management organization structure > safety management procedures. Among them, especially in the first 18 months, the impact of the safety policy was most apparent. However, in the production mine, the degree of influence was as follows: safety management organization structure > safety management procedures > safety policy, but the difference is very small. (4) The degree of influence on the construct of safety ability was as follows: safety knowledge > safety psychology = safety habits > safety awareness, but the difference on the impact was small.

Analyzing Subway Operation Accidents Causations: Apriori Algorithm and Network Approaches.

Subway operation safety management has become increasingly important due to the severe consequences of accidents and interruptions. As the causative factors and accidents exhibit a complex and dynamic interrelationship, the proposed subway operation accident causation network (SOACN) could represent the actual scenario in a better way. This study used the SOACN to explore subway operation safety risks and provide suggestions for promoting safety management. The SOACN model was built under 13 accident types, 29 causations and their 84 relationships based on the literature review, grounded theory and association rule analysis, respectively. Based on the network theory, topological features were obtained to showcase different roles of an accident or causation in the SOACN, including degree distribution, betweenness centrality, clustering coefficient, network diameter, and average path length. The SOACN exhibits both small-world network and scale-free features, implying that propagation in the SOACN is fast. Vulnerability evaluation was conducted under network efficiency, and its results indicated that safety management should focus more on fire accident and passenger falling off the rail. This study is beneficial for capturing the complex accident safety-risk-causation relationship in subway operations. It offers suggestions regarding safety-related decision optimization and measures for causation reduction and accident control with high efficiency.

Framework for Integrating Productive, Contributory, and Noncontributory Work with Safe and Unsafe Acts and Conditions.

It is common for companies that are in the process of implementing the Last Planner System (LPS) journey to attempt an increase in productive work and a reduction in waste, such as contributory and noncontributory work. Even though the LPS has proven to have a synergy with the health and safety requirements, companies with deficient health and safety management systems tend to classify work involving substandard acts or conditions as standard, and then pretend to benchmark against other companies that are indeed performing safe work. The following work introduces a framework to simultaneously register and analyze productive, contributory, and noncontributory work, with the substandard acts and conditions in a construction site, allowing for the measurement of production and health & safety indicators simultaneously. In the absence of technology that automatically captures these indicators, it is proposed that simultaneous measurements be made through direct inspections and photo and video recording by means of a handheld camera. The proposed continuous improvement framework follows the steps indicated below: (1) defining the productive, contributory, and noncontributory work with surveys performed on the most representative stakeholders of the industry; (2) proposing a new classification of production and safety work; (3) assessing the level of application of the LPS in the company; (4) measuring the indicators; (5) improving the use of the LPS and performing new measurements; (6) statistically linking deadly, serious, and minor accidents, standard and substandard acts, standard and substandard conditions, and productive, contributory, and noncontributory work. This framework was applied to a case study of a building project in Lima and the results were improved simultaneous indicators, especially the health and safety indicators. Automated classification of productive and nonproductive work using technology still represents a challenge.

Mechanism Models of the Conventional and Advanced Methods of Construction Safety Training. Is the Traditional Method of Safety Training Sufficient?

Cognitive failures at the information acquiring (safety training), comprehension, or application stages led to near-miss or accidents on-site. The previous studies rarely considered the cognitive processes of two different kinds of construction safety training. Cognitive processes are a series of chemical and electrical brain impulses that allow you to perceive your surroundings and acquire knowledge. Additionally, their attention was more inclined toward the worker's behavior during hazard identification on-site while on duty. A study is proposed to fill the knowledge gap by developing the mechanism models of the two safety training approaches. The mechanism models were developed based on cognitive psychology and Bloom's taxonomy and six steps of cognitive learning theory. A worker's safety training is vital in acquiring, storing, retrieving, and utilizing the appropriate information for hazard identification on-site. It is assumed that those trained by advanced techniques may quickly identify and avoid hazards on construction sites because of the fundamental nature of the training, and when they come across threats, they may promptly use their working memory and prevent them, especially for more complex projects. The main benefit of making such a model, from a cognitive point of view, is that it can help us learn more about the mental processes of two different types of construction safety training, and it can also help us come up with specific management suggestions to make up for the approaches' flaws. Future research will concentrate on the organizational aspects and other cognitive failures that could lead to accidents.

Using systems thinking-based risk assessment methods to assess hazardous manual tasks: a comparison of Net-HARMS, EAST-BL, FRAM and STPA.

Formal risk assessment is a component of safety management relating to hazardous manual tasks (HMT). Systems thinking approaches are currently gaining interest for supporting safety management. Existing HMT risk assessment methods have been found to be limited in their ability to identify risks across the whole work system; however, systems thinking-based risk assessment (STBRA) methods were not designed for the HMT context and have not been tested in this area. The aim of this study was to compare the performance of four state-of-the-art STBRA methods: Net-HARMS, EAST-BL, FRAM and STPA to determine which would be most useful for identifying HMT risks. Each method was independently applied by one of four analysts to assess the risks associated with a hypothetical HMT system. The outcomes were assessed for alignment with a benchmark analysis. Using signal detection theory (SDT), overall STPA was found to be the best performing method having the highest hit rate, second lowest false alarm rate and highest Matthews Correlation Coefficient of the four methods.Practitioner summary: A comparison of four systems thinking risk assessment methods found that STPA had the highest level of agreement with the benchmark analysis and is the most suitable for practitioners to use to identify the risks associated with HMT systems.

Applying lessons from aviation safety culture in the hospitality industry: a review and road map.

It is widely accepted that positive safety culture improves organizations' safety performance and reduces the number of injuries and deaths. Safety culture has been well researched in high-risk industries; however, the hospitality industry until recently had no research of the concept unless related to food safety. This article explores theoretical grounds for research of safety culture in hospitality, based on the aviation safety culture body of knowledge. Using aviation as a foundation is motivated by the similarities in operations between aviation and hospitality, especially when hospitality is compared to other high-risk industries. The article proposes that aviation safety culture models and their dimensions could be valuable for hospitality industry's safety culture improvements. It's goal and aspiring contribution is to begin a discussion and build a theoretical base for future research about advancement of safety in hospitality operations and reduction of the industry's relatively high numbers of employee injuries.

Safety management implementation drivers for construction projects: a structural equation modelling approach.

The construction industry is one of the hazardous fields due to its exceptional environment. Therefore, this work aimed to assess the essential drivers needed for employing safety management in the Palestinian construction industry. The drivers for safety management were recognized from earlier literature, where the questionnaires were dispersed to professionals from construction projects. The exploratory factor analysis (EFA) technique was then performed to contextually adjust the identified drivers. The results showed that safety management drivers could be categorized into three constructs: management, awareness and policy. In addition, partial least squares structural equation modelling (PLS-SEM) was performed to generate the safety management driver's model. The results indicated that management drivers were vital drivers for adopting safety management. The study's findings would act as a reference for construction stakeholders to decrease danger and enhance the construction project's success via implementing safety management drivers.

Behavior-based safety program for process industries.

Objectives. This article describes the reduction of unsafe behaviors observed at a fertilizer complex by implementation of a behavior-based safety (BBS) program via a behavior observation form developed by a multidisciplinary team. Methods. Six observation categories, i.e., position of people, reaction of people, personal protective equipment (PPE), tools used, operating procedures and housekeeping, are used to monitor safe and unsafe behaviors for a period of 18 months. Results. Safe behaviors increased from 57 to 70% and unsafe behaviors reduced from 40 to 26%. Behaviors of employees working in various sections of fertilizer complex such as ammonia, urea, utility, bagging/shipping and workshop were also observed. Non-compliance with PPE, housekeeping and standard operating procedures was also monitored in individual sections. Non-operational areas including the administration block, housing colony, maintenance workshop, warehouse, fire station and electrical substation were also observed. Among these, the maximum unsafe behaviors are for the housing colony and minimum for the electrical substation. Conclusion. It has been concluded that working on the housing colony, administration block and fire station areas will address 74% unsafe behaviors of non-operational areas. For practical applications, worldwide industries can implement this BBS program to enhance BBS, thus reducing unsafe behaviors and increasing employee morale.

Interprofessional In Situ Simulation to Identify Latent Safety Threats for Quality Improvement: A Single-Center Protocol Report.

In situ simulation has frequently been used to improve team performance and provide an opportunity for the practice of critical skills and identify latent safety threats, which are undetected risks that may lead to adverse outcomes. However, the use of known quality improvement tools to prioritize and mitigate these safety threats is an area requiring further study. Over the course of 9 in situ simulations of a pediatric shock case, postcase debriefs were held to identify latent safety threats in an emergency department and a mixed pediatric and adult inpatient unit. Latent safety threats identified included structure-related threats such as inability to locate critical equipment, knowledge-based threats relating to rapid intravenous fluid administration, and communication-based threats such as lack of role designation. Identification of latent safety threats in the health care environment may assist clinician leaders in mitigating risk of patient harm. The protocol described may be adopted and applied to other critical event simulations, with structured debriefing used as a tool to identify and mitigate threats before they affect the patient.