Development and application of a human error identification tool for air traffic control

Behavioral Economics in Radiology Training: Overcoming Irrational Behavior

Behavioral economics studies how external influences subconsciously affect decision making. Everyone is subject to a range of cognitive biases, which can affect the radiology training environment and can impact resident selection, resident education, feedback, workflow, and report composition. Understanding the cognitive sources of error and patterns of deviation can help faculty and trainees better engage in an optimal learning environment. This review focuses on the role of cognitive biases as they impact multiple facets of radiology education and training environments.

The Binary-Based Model (BBM) for Improved Human Factors Method Selection

OBJECTIVE

This paper presents the Binary-Based Model (BBM), a new approach to Human Factors (HF) method selection. The BBM helps practitioners select the most appropriate HF methodology in relation to the complexity within the target system.

BACKGROUND

There are over 200 HF methods available to the practitioner and little guidance to help choose between them.

METHOD

The BBM defines a HF "problem space" comprising three complexity attributes. HF problems can be rated against these attributes and located in the "problem space." In addition, a similar HF "approach space" in which 66 predictive methods are rated according to their ability to confront those attributes is defined. These spaces are combined into a "utility space" in which problems and methods coexist. In the utility space, the match between HF problems and methods can be formally assessed.

RESULTS

The method space is split into octants to establish broad groupings of methods distributed throughout the space. About 77% of the methods reside in Octant 1 which corresponds to problems with low levels of complexity. This demonstrates that most HF methods are suited to problems in low-complexity systems.

CONCLUSION

The location of 77% of the rated methods in Octant 1 indicates that HF practitioners are underserved with methods for analysis of HF problems exhibiting high complexity.

APPLICATION

The BBM can be used by multidisciplinary teams to select the most appropriate HF methodology for the problem under analysis. All the materials and analysis are placed in the public domain for modification and consensus building by the wider HF community.

State of science: evolving perspectives on 'human error'

This paper reviews the key perspectives on human error and analyses the core theories and methods developed and applied over the last 60 years. These theories and methods have sought to improve our understanding of what human error is, and how and why it occurs, to facilitate the prediction of errors and use these insights to support safer work and societal systems. Yet, while this area of Ergonomics and Human Factors (EHF) has been influential and long-standing, the benefits of the 'human error approach' to understanding accidents and optimising system performance have been questioned. This state of science review analyses the construct of human error within EHF. It then discusses the key conceptual difficulties the construct faces in an era of systems EHF. Finally, a way forward is proposed to prompt further discussion within the EHF community. Practitioner statement This state-of-science review discusses the evolution of perspectives on human error as well as trends in the theories and methods applied to understand, prevent and mitigate error. It concludes that, although a useful contribution has been made, we must move beyond a focus on an individual error to systems failure to understand and optimise whole systems.

Classification and quantification of human error in air traffic control: a case study in an airport control tower

This study aims at exploring human error in an airport control tower through the technique for the retrospective and predictive analysis of cognitive error (TRACEr) and the controller action reliability assessment (CARA) method. Despite the presence of automated safety nets, air traffic control (ATC) is heavily dependent upon the capabilities of humans. A number of ATC-relevant accidents were characterized by human errors. The data related to error dimensions were collected through interview and direct observation. Then, human error probability and error-producing conditions were evaluated by the CARA method. The results showed that selection and quality, memory, distraction/preoccupation, and traffic and airspace have the highest percentage error rates. Furthermore, the results indicated that the highest probability of error was associated with emergency situation management. This study is the first research to classify and quantify human errors using the TRACEr and the CARA method to evaluate controller error in ATC.

Radical systems thinking and the future role of computational modelling in ergonomics: an exploration of agent-based modelling

We are teetering on the precipice of the imminent Fourth Industrial Revolution. In this new age, systems are set to become more densely intraconnected and interconnected, and massive sociotechnical systems exhibiting unprecedented levels of complexity will increasingly take hold. At the dawning of this new age, the Ergonomics discipline must reflect on its preparedness for tackling problems in these novel systems. This paper engages in this reflection by putting forth a critical commentary on the implication of these changes on the discipline and discusses the utility of our current methods in this new paradigm. A resulting Radical Systems Thinking in Ergonomics Manifesto is put forward - a set of mandates to guide practitioners and researchers in the development of new methods capable of coping with these imminent challenges. From the manifesto are derived a series of capability requirements for future computational modelling approaches in Ergonomics. Practitioner summary: The goal of this paper was to inspire the Ergonomics community to pursue further applications involving computational modelling approaches such as Agent-Based Modelling. It presents a manifesto for the future of the discipline, and from this the capabilities that future computational modelling approaches need to possess. Abbreviations: 1IR: first industrial revolution; 2IR: second industrial revolution; 3IR: third industrial revolution; 4IR: fourth industrial revolution; ABM: agent based model; AI: artificial intelligence; AoF: allocation of function; CPA: cyber physical attack; CPS: cyber-physical system; CWA: cognitive work analysis; DDoS: distributed denial of service; EAST: event analysis of systemic teamwork; FRAM; functional resonance analysis method; HCI: human-computer interaction; HERA: human error and recovery assessment; HET: human error template; HMC: human-machine cooperation; IoT: internet of things; RSTEM: radical systems thinking in ergonomics manifesto; SAI: situated artificial intelligence; STAMP: systems theoretic accident model and processes; TRACEr: technique for the retrospective and predictive analysis of cognitive errors in air traffic control.

What the eyes reveal: Investigating the detection of automation failures

In order to detect automation failures in a timely manner, operators are required to monitor automated systems efficiently. The present study analysed eye movements to predict whether or not participants could detect an automation failure. Eye movements were recorded whilst 101 participants were monitoring an automated system where automation failures occurred at irregular intervals. A main result is that about 75.6 per cent of automation failure detections were predicted successfully by the corresponding eye movements. In cases where failures were detected successfully, relevant information is monitored more often and more intensively, in particular shortly before an automation failure happens and while it is happening. The findings are discussed in the context of the personnel selection and training of aviation operatives, as well as incident reporting as used in air traffic control (ATC).

Human Factors Analysis of Air Traffic Safety Based on HFACS-BN Model

Air traffic control (ATC) performance is important to ensure flight safety and the sustainability of aviation growth. To better evaluate the performance of ATC, this paper introduces the HFACS-BN model (HFACS: Human factors analysis and classification system; BN: Bayesian network), which can be combined with the subjective information of relevant experts and the objective data of accident reports to obtain more accurate evaluation results. The human factors of ATC in this paper are derived from screening and analysis of 142 civil and general aviation accidents/incidents related to ATC human factors worldwide from 1980 to 2019, among which the most important 25 HFs are selected to construct the evaluation model. The authors designed and implemented a questionnaire survey based on the HFACS framework and collected valid data from 26 frontline air traffic controllers (ATCO) and experts related to ATC in 2019. Combining the responses with objective data, the noisy MAX model is used to calculate the conditional probability table. The results showed that, among the four levels of human factors, unsafe acts had the greatest influence on ATC Performance (79.4%), while preconditions for safe acts contributed the least (40.3%). The sensitivity analysis indicates the order of major human factors influencing the performance of ATC. Finally, this study contributes to the literature in terms of methodological development and expert empirical analysis, providing data support for human error management intervention of ATC in aviation safety.

Can Complexity-Thinking Methods Contribute to Improving Occupational Safety in Industry 4.0? A Review of Safety Analysis Methods and Their Concepts

With the introduction of Industry 4.0, occupational health and safety finds itself confronted with new types of hazards. Many Industry 4.0 innovations involve increased machine intelligence. These properties make socio-technical work in Industry 4.0 applications inherently more complex. At the same time, system failure can become more opaque to its users. This paper reviews and assesses safety analysis methods as the breakdown of interaction coupling in socio-technical systems on the one hand, and the degree of failure tractability on the other hand; the latter being used as a proxy for complexity. Previous literature confirms that traditional health and safety risk assessment methods are unable or are ‘ill-equipped’ to deal with these system properties. This paper studies the need to introduce new paradigms and safety methods related to complexity thinking with theories borrowed from the study of complex adaptive systems, all to assess the arena of abruptly changing hazards introduced by Industry 4.0. At the same time, this review makes clear that there is no one-solution-fits-all method. Occupational health and safety (OHS) covers many different hazard types and will need a combination of old, new and yet-to-be-developed safety assessment methods.

Systematic assessment of intrinsic factors influencing visual attention performances in air traffic control via clustering algorithm and statistical inference

The intrinsic factors (IF) influencing visual attention performance (VAP) might cause potential human errors, such as “error/mistake”, “forgetting” and “omission”. It is a key issue to develop a systematic assessment of IF in order to distinguish the levels of VAP. Motivated by the Stimulus-Response (S-R) model, we take an interactive cancellation test—Neuron Type Test (NTT)—to explore the IF and present the corresponding systematic assessment. The main contributions of this work include three elements: a) modeling the IF on account of attention span, attention stability, distribution-shift of attention with measurable parameters by combining the psychological and statistical concepts; b) proposing quantitative analysis methods for assessing the IF via its computational representation—intrinsic qualities (IQ)—in the sense of computational model; and c) clustering the IQ of air traffic control (ATC) students in the feature space of interest. The response sequences of participants collected with the NTT system are characterized by three parameters: Hurst exponent, normalized number of decisions (NNoD) and error rate of decisions (ERD). The K-means clustering is applied to partition the feature space constructed from practical data of VAP. For the distinguishable clusters, the statistical inference is utilized to refine the assessment of IF. Our comprehensive analysis shows that the IQ can be classified into four levels, i.e., excellent, good, moderate and unqualified, which has a potential application in selecting air traffic controllers subject to reducing the risk of the inadequacy of attention performances in aviation safety management.

Application of classification principles to improve the reliability of incident classification systems: A test case using HFACS-ADF

Accident classification systems are important tools for safety management. Unfortunately, many of the tools available have demonstrated poor reliability of coding, making their validity and usefulness questionable. This paper demonstrates the application of four strategies to improve the reliability of accident and incident classification systems. The strategies include creating a domain-specific system with limitations on system size and careful selection of codes, specifically the reduction of abstract concepts and bias-causing terminology. Using HFACS-ADF as a test case, the system was adapted using the strategies and validated using comprehension and comprehensiveness testing. The new system was then assessed for reliability. The reliability of the system increased by at least 20% at all levels of the classification system following the changes made. The results provide evidence that the application of theoretically and empirically-derived classification principles are effective for improving the reliability of accident and incident classification systems in high hazard industries.

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.

Fitting methods to paradigms: are ergonomics methods fit for systems thinking?

The issues being tackled within ergonomics problem spaces are shifting. Although existing paradigms appear relevant for modern day systems, it is worth questioning whether our methods are. This paper asks whether the complexities of systems thinking, a currently ubiquitous ergonomics paradigm, are outpacing the capabilities of our methodological toolkit. This is achieved through examining the contemporary ergonomics problem space and the extent to which ergonomics methods can meet the challenges posed. Specifically, five key areas within the ergonomics paradigm of systems thinking are focused on: normal performance as a cause of accidents, accident prediction, system migration, systems concepts and ergonomics in design. The methods available for pursuing each line of inquiry are discussed, along with their ability to respond to key requirements. In doing so, a series of new methodological requirements and capabilities are identified. It is argued that further methodological development is required to provide researchers and practitioners with appropriate tools to explore both contemporary and future problems. Practitioner Summary: Ergonomics methods are the cornerstone of our discipline. This paper examines whether our current methodological toolkit is fit for purpose given the changing nature of ergonomics problems. The findings provide key research and practice requirements for methodological development.

Beyond human error taxonomies in assessment of risk in sociotechnical systems: a new paradigm with the EAST 'broken-links' approach

Risk assessments in Sociotechnical Systems (STS) tend to be based on error taxonomies, yet the term 'human error' does not sit easily with STS theories and concepts. A new break-link approach was proposed as an alternative risk assessment paradigm to reveal the effect of information communication failures between agents and tasks on the entire STS. A case study of the training of a Royal Navy crew detecting a low flying Hawk (simulating a sea-skimming missile) is presented using EAST to model the Hawk-Frigate STS in terms of social, information and task networks. By breaking 19 social links and 12 task links, 137 potential risks were identified. Discoveries included revealing the effect of risk moving around the system; reducing the risks to the Hawk increased the risks to the Frigate. Future research should examine the effects of compounded information communication failures on STS performance. Practitioner Summary: The paper presents a step-by-step walk-through of EAST to show how it can be used for risk assessment in sociotechnical systems. The 'broken-links' method takes a systemic, rather than taxonomic, approach to identify information communication failures in social and task networks.

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

The purposes of this study were to develop a latent human error analysis process, to explore the factors of latent human error in aviation maintenance tasks, and to provide an efficient improvement strategy for addressing those errors. First, we used HFACS and RCA to define the error factors related to aviation maintenance tasks. Fuzzy TOPSIS with four criteria was applied to evaluate the error factors. Results show that 1) adverse physiological states, 2) physical/mental limitations, and 3) coordination, communication, and planning are the factors related to airline maintenance tasks that could be addressed easily and efficiently. This research establishes a new analytic process for investigating latent human error and provides a strategy for analyzing human error using fuzzy TOPSIS. Our analysis process complements shortages in existing methodologies by incorporating improvement efficiency, and it enhances the depth and broadness of human error analysis methodology.

Development of safety incident coding systems through improving coding reliability

This paper reviews classification theory sources to develop five research questions concerning factors associated with incident coding system development and use and how these factors affect coding reliability. Firstly, a method was developed to enable the comparison of reliability results obtained using different methods. Second, a statistical and qualitative review of reliability studies was conducted to investigate the influence of the identified factors on the reliability of incident coding systems. As a result several factors were found to have a statistically significant effect on reliability. Four recommendations for system development and use are provided to assist researchers in improving the reliability of incident coding systems in high hazard industries.

Human error identification for laparoscopic surgery: Development of a motion economy perspective

This study postulates that traditional human error identification techniques fail to consider motion economy principles and, accordingly, their applicability in operating theatres may be limited. This study addresses this gap in the literature with a dual aim. First, it identifies the principles of motion economy that suit the operative environment and second, it develops a new error mode taxonomy for human error identification techniques which recognises motion economy deficiencies affecting the performance of surgeons and predisposing them to errors. A total of 30 principles of motion economy were developed and categorised into five areas. A hierarchical task analysis was used to break down main tasks of a urological laparoscopic surgery (hand-assisted laparoscopic nephrectomy) to their elements and the new taxonomy was used to identify errors and their root causes resulting from violation of motion economy principles. The approach was prospectively tested in 12 observed laparoscopic surgeries performed by 5 experienced surgeons. A total of 86 errors were identified and linked to the motion economy deficiencies. Results indicate the developed methodology is promising. Our methodology allows error prevention in surgery and the developed set of motion economy principles could be useful for training surgeons on motion economy principles.

Applications of integrated human error identification techniques on the chemical cylinder change task

This paper outlines the human error identification (HEI) techniques that currently exist to assess latent human errors. Many formal error identification techniques have existed for years, but few have been validated to cover latent human error analysis in different domains. This study considers many possible error modes and influential factors, including external error modes, internal error modes, psychological error mechanisms, and performance shaping factors, and integrates several execution procedures and frameworks of HEI techniques. The case study in this research was the operational process of changing chemical cylinders in a factory. In addition, the integrated HEI method was used to assess the operational processes and the system's reliability. It was concluded that the integrated method is a valuable aid to develop much safer operational processes and can be used to predict human error rates on critical tasks in the plant.

Designing sociotechnical systems with cognitive work analysis: putting theory back into practice

Cognitive work analysis (CWA) is a framework of methods for analysing complex sociotechnical systems. However, the translation from the outputs of CWA to design is not straightforward. Sociotechnical systems theory provides values and principles for the design of sociotechnical systems which may offer a theoretically consistent basis for a design approach for use with CWA. This article explores the extent to which CWA and sociotechnical systems theory offer complementary perspectives and presents an abstraction hierarchy (AH), based on a review of literature, that describes an 'optimal' CWA and sociotechnical systems theory design system. The optimal AH is used to assess the extent to which current CWA-based design practices, uncovered through a survey of CWA practitioners, aligns with sociotechnical systems theory. Recommendations for a design approach that would support the integration of CWA and sociotechnical systems theory design values and principles are also derived.

The application of SHERPA (Systematic Human Error Reduction and Prediction Approach) in the development of compensatory cognitive rehabilitation strategies for stroke patients with left and right brain damage

Approximately 33% of stroke patients have difficulty performing activities of daily living, often committing errors during the planning and execution of such activities. The objective of this study was to evaluate the ability of the human error identification (HEI) technique SHERPA (Systematic Human Error Reduction and Prediction Approach) to predict errors during the performance of daily activities in stroke patients with left and right hemisphere lesions. Using SHERPA we successfully predicted 36 of the 38 observed errors, with analysis indicating that the proportion of predicted and observed errors was similar for all sub-tasks and severity levels. HEI results were used to develop compensatory cognitive strategies that clinicians could employ to reduce or prevent errors from occurring. This study provides evidence for the reliability and validity of SHERPA in the design of cognitive rehabilitation strategies in stroke populations.

Applying hierarchical task analysis to improving the patient positioning for direct lateral interbody fusion in spinal surgery

The present study brings together for the first time the techniques of hierarchical task analysis (HTA), human error identification (HEI), and business process management (BPM) to select practices that can eliminate or reduce potential errors in a surgical setting. We applied the above approaches to the improvement of the patient positioning process for lumbar spine surgery referred to as 'direct lateral interbody fusion' (DLIF). Observations were conducted to gain knowledge on current DLIF positioning practices, and an HTA was constructed. Potential errors associated with the practices specific to DLIF patient positioning were identified. Based on literature review and expert views alternative practices are proposed aimed at improving the DLIF patient positioning process. To our knowledge, this is the first attempt to use BPM in association with HEI/HTA for the purpose of improving the performance and safety of a surgical process - with promising results.

Reliability studies of incident coding systems in high hazard industries: A narrative review of study methodology

This paper reviews the current literature on incident coding system reliability and discusses the methods applied in the conduct and measurement of reliability. The search strategy targeted three electronic databases using a list of search terms and the results were examined for relevance, including any additional relevant articles from the bibliographies. Twenty five papers met the relevance criteria and their methods are discussed. Disagreements in the selection of methods between reliability researchers are highlighted as are the effects of method selection on the outcome of the trials. The review provides evidence that the meaningfulness of and confidence in results is directly affected by the methodologies employed by the researcher during the preparation, conduct and analysis of the reliability study. Furthermore, the review highlights the heterogeneity of methodologies employed by researchers measuring reliability of incident coding techniques, reducing the ability to critically compare and appraise techniques being considered for the adoption of report coding and trend analysis by client organisations. It is recommended that future research focuses on the standardisation of reliability research and measurement within the incident coding domain.

A reliability and usability study of TRACEr-RAV: the technique for the retrospective analysis of cognitive errors--for rail, Australian version

The aim of this study was to compare the usability and reliability of two human error identification tools: TRACEr-Rail (developed by the Rail Safety and Standards Board in the UK) and TRACEr-RAV (an Australian specific version of the tool). Following an attempt to modify TRACEr-Rail to more appropriately suit the Australian rail context, it was predicted that TRACEr-RAV would be rated as more usable and be applied more consistently by Australian users than TRACEr-Rail. In Experiment 1, twenty-five rail employees used either TRACEr-Rail or TRACEr-RAV1 to extract and classify errors from six Australian rail incident reports. In Experiment 2, eleven university students used both TRACEr-Rail and TRACEr-RAV2 to extract and classify errors from three incident summaries. The results revealed that although modification of TRACEr-Rail to become TRACEr-RAV1 and TRACEr-RAV2 did not result in improved inter-rater reliability, modification resulted in improved ratings of usability in Experiment 2. Most participants in Experiment 2 preferred TRACEr-RAV2 to TRACEr-Rail. The poor inter-rater reliability observed was most likely the result of inadequate training, limited practice in using the tools, and insufficient human factors knowledge.

Using Cognitive Work Analysis Techniques to Identify Human Factor Hazards

Accidents in the process industries can be attributed, at least in part, to human causes. Hazard studies are commonly used in industry to identify and manage risks. This paper describes a methodology, called HumHID, which potentially improves hazard identification associated with human factors. The approach is based on cognitive work analysis (CWA) techniques, human factors/error taxonomies and the blended hazard methodology (BLHAZID). A desktop case study is used to illustrate the application of the methodology. The results show that a combination of CWA, human factors/error taxonomies and BLHAZID techniques provides a structured means of identifying hazards associated with human activity as well as showing the causality behind the hazards which can be used to guide redesign work.

Evaluation of the HFACS-ADF safety classification system: inter-coder consensus and intra-coder consistency

This article evaluates an adaptation of the human factors analysis and classification system (HFACS) adopted by the Australian Defence Force (ADF) to classify factors that contribute to incidents. Three field studies were undertaken to assess the reliability of HFACS-ADF in the context of a particular ADF air traffic control (ATC) unit. Study one was designed to assess inter-coder consensus between many coders for two incident reports. Study two was designed to assess inter-coder consensus between one participant and the previous original analysts for a large set of incident reports. Study three was designed to test intra-coder consistency for four participants over many months. For all studies, agreement was low at the level of both fine-level HFACS-ADF descriptors and high-level HFACS-type categories. A survey of participants suggested that they were not confident that HFACS-ADF could be used consistently. The three field studies reported suggest that the ADF adaptation of HFACS is unreliable for incident analysis at the ATC unit level, and may therefore be invalid in this context. Several reasons for the results are proposed, associated with the underlying HFACS model and categories, the HFACS-ADF adaptations, the context of use, and the conduct of the studies.

Human performance interfaces in air traffic control

This paper examines how human performance factors in air traffic control (ATC) affect each other through their mutual interactions. The paper extends the conceptual SHEL model of ergonomics to describe the ATC system as human performance interfaces in which the air traffic controllers interact with other human performance factors including other controllers, software, hardware, environment, and organisation. New research hypotheses about the relationships between human performance interfaces of the system are developed and tested on data collected from air traffic controllers, using structural equation modelling. The research result suggests that organisation influences play a more significant role than individual differences or peer influences on how the controllers interact with the software, hardware, and environment of the ATC system. There are mutual influences between the controller-software, controller-hardware, controller-environment, and controller-organisation interfaces of the ATC system, with the exception of the controller-controller interface. Research findings of this study provide practical insights in managing human performance interfaces of the ATC system in the face of internal or external change, particularly in understanding its possible consequences in relation to the interactions between human performance factors.

Combining task analysis and fault tree analysis for accident and incident analysis: a case study from Bulgaria

Understanding the reasons for incident and accident occurrence is important for an organization's safety. Different methods have been developed to achieve this goal. To better understand the human behaviour in incident occurrence we propose an analysis concept that combines Fault Tree Analysis (FTA) and Task Analysis (TA). The former method identifies the root causes of an accident/incident, while the latter analyses the way people perform the tasks in their work environment and how they interact with machines or colleagues. These methods were complemented with the use of the Human Error Identification in System Tools (HEIST) methodology and the concept of Performance Shaping Factors (PSF) to deepen the insight into the error modes of an operator's behaviour. HEIST shows the external error modes that caused the human error and the factors that prompted the human to err. To show the validity of the approach, a case study at a Bulgarian Hydro power plant was carried out. An incident - the flooding of the plant's basement - was analysed by combining the afore-mentioned methods. The case study shows that Task Analysis in combination with other methods can be applied successfully to human error analysis, revealing details about erroneous actions in a realistic situation.

Human factors and safe patient care

AIMS

This paper aims to introduce the topic of human factors to nursing management and to identify areas where it can be applied to patient safety.

BACKGROUND

Human factors is a discipline established in most safety critical industries and uses knowledge about human behaviour in the analysis and design of complex systems, yet it is relatively new to many in healthcare.

EVALUATION

Most safety critical industries have developed tools and techniques to apply human factors to system design, and these have been reviewed together with those resources already available for use in healthcare.

KEY ISSUES

Models of human behaviour such as the nature and patterns of human error, information processing, decision-making and team work have clear applications to healthcare. Human factors focus on a system view of safety, and propose that safety should, where possible, be 'designed in'. Other interventions such as building defences, mitigating hazards and education and training should only be used where design solutions cannot be found.

CONCLUSIONS

Simple human factors principles such as: designing for standardization; the involvement of users and staff in designing services and procuring equipment; understanding how errors occur; and the workarounds that staff will inevitably take are vital considerations in improving patient safety.

IMPLICATIONS FOR NURSING MANAGEMENT

Opportunities for the application of human factors to healthcare and improved patient safety are discussed. Some existing tools and techniques for applying human factors in nursing management are also presented.

Understanding safety and production risks in rail engineering planning and protection

Much of the published human factors work on risk is to do with safety and within this is concerned with prediction and analysis of human error and with human reliability assessment. Less has been published on human factors contributions to understanding and managing project, business, engineering and other forms of risk and still less jointly assessing risk to do with broad issues of 'safety' and broad issues of 'production' or 'performance'. This paper contains a general commentary on human factors and assessment of risk of various kinds, in the context of the aims of ergonomics and concerns about being too risk averse. The paper then describes a specific project, in rail engineering, where the notion of a human factors case has been employed to analyse engineering functions and related human factors issues. A human factors issues register for potential system disturbances has been developed, prior to a human factors risk assessment, which jointly covers safety and production (engineering delivery) concerns. The paper concludes with a commentary on the potential relevance of a resilience engineering perspective to understanding rail engineering systems risk. Design, planning and management of complex systems will increasingly have to address the issue of making trade-offs between safety and production, and ergonomics should be central to this. The paper addresses the relevant issues and does so in an under-published domain - rail systems engineering work.

Predicting pilot error: testing a new methodology and a multi-methods and analysts approach

The Human Error Template (HET) is a recently developed methodology for predicting design-induced pilot error. This article describes a validation study undertaken to compare the performance of HET against three contemporary Human Error Identification (HEI) approaches when used to predict pilot errors for an approach and landing task and also to compare analyst error predictions to an approach to enhancing error prediction sensitivity: the multiple analysts and methods approach, whereby multiple analyst predictions using a range of HEI techniques are pooled. The findings indicate that, of the four methodologies used in isolation, analysts using the HET methodology offered the most accurate error predictions, and also that the multiple analysts and methods approach was more successful overall in terms of error prediction sensitivity than the three other methods but not the HET approach. The results suggest that when predicting design-induced error, it is appropriate to use a toolkit of different HEI approaches and multiple analysts in order to heighten error prediction sensitivity.

Confidential reporting of patient safety events in primary care: results from a multilevel classification of cognitive and system factors

OBJECTIVE

To classify events of actual or potential harm to primary care patients using a multilevel taxonomy of cognitive and system factors.

METHODS

Observational study of patient safety events obtained via a confidential but not anonymous reporting system. Reports were followed up with interviews where necessary. Events were analysed for their causes and contributing factors using causal trees and were classified using the taxonomy. Five general medical practices in the West Midlands were selected to represent a range of sizes and types of patient population. All practice staff were invited to report patient safety events. Main outcome measures were frequencies of clinical types of events reported, cognitive types of error, types of detection and contributing factors; and relationship between types of error, practice size, patient consequences and detection.

RESULTS

78 reports were relevant to patient safety and analysable. They included 21 (27%) adverse events and 50 (64%) near misses. 16.7% (13/71) had serious patient consequences, including one death. 75.7% (59/78) had the potential for serious patient harm. Most reports referred to administrative errors (25.6%, 20/78). 60% (47/78) of the reports contained sufficient information to characterise cognition: "situation assessment and response selection" was involved in 45% (21/47) of these reports and was often linked to serious potential consequences. The most frequent contributing factor was work organisation, identified in 71 events. This included excessive task demands (47%, 37/71) and fragmentation (28%, 22/71).

CONCLUSIONS

Even though most reported events were near misses, events with serious patient consequences were also reported. Failures in situation assessment and response selection, a cognitive activity that occurs in both clinical and administrative tasks, was related to serious potential harm.

A framework for managing system disturbances and insights from air traffic management

System disturbances are likely to be a key factor affecting the acceptance and safety of future automation. Since hardware and software are rarely totally reliable, humans are always required in socio-technical command and control environments such as air traffic management (ATM). Unfortunately, human-automation interaction is known to be problematic, particularly when the human assumes a monitoring or back-up role. Hence an understanding of how humans manage system disturbances is required, together with a method of looking at the problem for new systems. In this paper we outline a contextual framework of the process by which people recover from system disturbances, together with literature data and findings from 31 interviews with ATM personnel. The framework describes the context and causes of a problem, the problem itself, the effect and exposure, the recovery process, and the outcome. The framework, together with the research findings and operational experience, is also the basis for a performance prediction tool called the Recovery from Automation Failure Tool (RAFT).

From cognition to the system: developing a multilevel taxonomy of patient safety in general practice

The paper describes the process of developing a taxonomy of patient safety in general practice. The methodologies employed included fieldwork, task analysis and confidential reporting of patient-safety events in five West Midlands practices. Reported events were traced back to their root causes and contributing factors. The resulting taxonomy is based on a theoretical model of human cognition, includes multiple levels of classification to reflect the chain of causation and considers affective and physiological influences on performance. Events are classified at three levels. At level one, the information-processing model of cognition is used to classify errors. At level two, immediate causes are identified, internal and external to the individual. At level three, more remote causal factors are classified as either 'work organization' or 'technical' with subcategories. The properties of the taxonomy (validity, reliability, comprehensiveness) as well as its usability and acceptability remain to be tested with potential users.