Human Factors Taxonomy Research Articles

Beyond blame: A systemic accident analysis through a neutralized human factors taxonomy

AbstractThis paper investigates the usage of a systemic neutralized taxonomy for understanding human factors to foster a restorative culture when studying adverse events. The available studies supporting accident analysis from a system‐theoretic perspective with human factors‐based methods are grounded on error taxonomies and do not reinforce the non‐judgemental dimension that is encouraged by modern safety science. We propose a methodology to integrate the system‐theoretic accident analysis technique, Causal Analysis based on System Theory, with a neutralized taxonomy of human explanatory factors. The proposed methodology has been applied to an aviation accident involving a military aircraft and a glider. This case revealed various critical interactions among system components, which require dedicated safety recommendations that go beyond the identification of single points of failures and root causes, leading to a deeper understanding of socio‐technical orchestrations. Despite the use case in aviation, the proposed methodology remains suitable for various types of safety occurrences in diverse domains and industrial settings. It also represents the basis for supporting future proactive safety‐related decision‐making processes.

Application of broken windows theory to identify flow disruptions in neurosurgery procedure.

Addressing flow disruptions (FDs) in neurosurgery requires a multifaceted approach. Strategies like improved communication protocols, minimizing interruptions, improving coordination among team, optimizing operating room layout, and promoting user-centered design can help mitigate the challenges and enhance the overall flow and safety of neurosurgical procedures. Thirty neurosurgery cases were observed at two tertiary care facilities. The data collected were from wheels into the operating room to wheels out from the operating room. Data points were categorized using a human factors taxonomy known as RIPCHORD-TWA (Realizing Improved Patient Care Through Human-Centered Operating Room Design for Threat Window Analysis). Of the 541 total disruptions observed, coordination issues were the most prevalent (26.25%), followed by layout issues (26.06%), issues related to interruption (22.55%), communication (22.37%), equipment issues (2.40%) and usability issues (0.37%) comprised the remainder of the observations. This translated into one disruption every 2.7 min. Instead of focusing exclusively on errors and adverse events, we propose conceptualizing the accumulation of disruptions as "threat windows" to analyze potential threats to the integrity of the care system. This perspective allows for the improved identification of system weaknesses or threats, affording us the ability to address these inefficiencies and intervene before errors and adverse events may occur.

SHIELD Human Factors Taxonomy and Database for Learning from Aviation and Maritime Safety Occurrences

Human factors (HF) in aviation and maritime safety occurrences are not always systematically analysed and reported in a way that makes the extraction of trends and comparisons possible in support of effective safety management and feedback for design. As a way forward, a taxonomy and data repository were designed for the systematic collection and assessment of human factors in aviation and maritime incidents and accidents, called SHIELD (Safety Human Incident and Error Learning Database). The HF taxonomy uses four layers: The top layer addresses the sharp end where acts of human operators contribute to a safety occurrence; the next layer concerns preconditions that affect human performance; the third layer describes decisions or policies of operations leaders that affect the practices or conditions of operations; and the bottom layer concerns influences from decisions, policies or methods adopted at an organisational level. The paper presents the full details, guidance and examples for the effective use of the HF taxonomy. The taxonomy has been effectively used by maritime and aviation stakeholders, as follows from questionnaire evaluation scores and feedback. It was found to offer an intuitive and well-documented framework to classify HF in safety occurrences.

The Effects of Flow Disruptions on RN Circulators.

The RN circulator role includes maintaining situational awareness and mitigating risks to patient safety in the OR. Flow disruptions-deviations that threaten the safe and efficient flow of surgery-may contribute to the occurrence of errors and negatively affect safety for patients and health care providers. We used an existing data set to explore the effects of flow disruptions on the RN circulator. To create the data set, doctoral-level human factors students observed 24 cardiac surgery procedures and recorded the types and durations of disruptions. We used a human factors taxonomy to classify the flow disruptions. Of the 1,470 events observed, interruptions were most prevalent (66.67%), followed by coordination issues (15.37%) and communication breakdowns (8.37%). Layout (7.21%), equipment (1.77%), and usability (0.61%) issues accounted for the remainder of the disruptions. Perioperative leaders should work with staff members to minimize workflow disruptions and provide support for identifying and documenting flow disruptions.

Using the WHO International Classification of patient safety framework to identify incident characteristics and contributing factors for medical or surgical complication deaths

This study aimed to operationalise and use the World Health Organisation's International Classification for Patient Safety (ICPS) to identify incident characteristics and contributing factors of deaths involving complications of medical or surgical care in Australia. A sample of 500 coronial findings related to patient deaths following complications of surgical or medical care in Australia were reviewed using a modified-ICPS (mICPS). Over two-thirds (69.0%) of incidents occurred during treatment and 27.4% occurred in the operating theatre. Clinical process and procedures (55.9%), medication/IV fluids (11.2%) and healthcare-associated infection/complications (10.4%) were the most common incident types. Coroners made recommendations in 44.0% of deaths and organisations undertook preventive actions in 40.0% of deaths. This study demonstrated that the ICPS was able to be modified for practical use as a human factors taxonomy to identify sequences of incident types and contributing factors for patient deaths. Further testing of the mICPS is warranted.

The human factor and maritime safety

Abstract Studies of maritime accidents identify human error as the primary contributing cause for up to 70% of the accidents. By investigating incidents, safety problems can be identified, and preventive measures may be taken. This paper deals with incorporate human factors into an accident investigation program. In order to provide an examples of a human factors taxonomy for the purpose of investigation, the Human Factor Analysis and Classification System (HFACS), was used. The fundamental issue of the HFACS system is the proper categorisation of the causal factors in one of nineteen sections, known as “coding process”. In this paper, the recommendations for the proper classification of causal factors, focused on marine transport, will be provided.

Modeling workers’ behavior: A human factors taxonomy and a fuzzy analysis in the case of industrial accidents

While ‘Industry 4.0’ drives for greater automation, human factors are still essential in certain domains, especially in industrial disaster management. Despite human factors are frequently cause of individual biases and errors, a systematic quantitative analysis of the correlation between them and the workers' response performance in case of an industrial disaster has never been conducted.The aim of the present study is twofold: to design an original human factors taxonomy, which encompasses all the industrial worker's cognitive capabilities, physical skills, and psychological attitudes; to establish a correlation between each factor and the workers' response performance in case of an industrial emergency. A Fuzzy Analytic Hierarchy Process (FAHP) analysis has been conducted in collaboration with 44 subject matter experts by using an ad-hoc developed tool to investigate, in particular, two types of workers, the role of emergency manager and the emergency team member. Results reveal that the factors have not the same weight in determining the human response performance: cognitive and psychological aspects have a substantial influence on the emergency manager's response performance, while the emergency team member's response performance is more influenced by psychological and physical aspects. Relevance to industryGiven the crucial role of cognitive, physical and psychological factors in modern human-centred industrial systems and especially in the field of industrial safety & security, this study represents a meticulous guide for safety specialists in the design of disaster management strategies, for recruiters and practitioners in the development of competency-based job descriptions and for new research works for the development of personality-gifted intelligent agents in industrial applications.

A Theoretical Model of Flow Disruptions for the Anesthesia Team During Cardiovascular Surgery.

This investigation explores flow disruptions observed during cardiothoracic surgery and how they serve to disconnect anesthesia providers from their primary task. We can improve our understanding of this disengagement by exploring what we call the error space or the accumulated time required to resolve disruptions. Trained human factors students observed 10 cardiac procedures for disruptions impacting the anesthesia team and recorded the time required to resolve these events. Observations were classified using a human factors taxonomy. Of 301 disruptions observed, interruptions (e.g., those events related to alerts, distractions, searching activity, spilling/dropping, teaching moment, and task deviations) accounted for the greatest frequency of events (39.20%). The average amount of time needed for each disruption to be resolved was 48 seconds. Across 49.87 hours of observation, more than 4 hours were spent resolving disruptions to the anesthesia team's work flow. By defining a calculable error space associated with these disruptions, this research provides a conceptual metric that can serve in the identification and design of targeted interventions. This method serves as a proactive approach for recognizing systemic threats, affording healthcare workers the opportunity to mitigate the development and incidence of preventable errors precedently.

Flow disruptions impacting the surgeon during cardiac surgery: Defining the boundaries of the error space

BackgroundThe aim of this investigation is to place surgical disruptions in a different light. Rather than viewing these disruptions as isolated events which may affect the surgical team, we represent them as an aggregated space which serves to disconnect the team from the task at hand. Furthermore, we make the case that by understanding this error space, one can begin to target interventions that reduce the boundaries of this space and as a consequence reduce the opportunity for errors to develop. MethodsTrained doctoral-level human factors students observed 24 cardiac procedures for flow disruptions impacting the surgical team and recorded the frequency as well as time needed to resolve these events. Observations were later coded using a human factors taxonomy and descriptive statistics were applied. ResultsA total of 693 workflow disruptions were experienced by the surgical team where interruption issues accounted for the greatest frequency of events (32.61%). Of 139.06h of total observation time, 10.14h was needed to resolve the 693 disruptions identified. On average, each disruption took 61.99s to resolve. ConclusionWhile there is value in identifying the frequency of flow disruptions, this only addresses part of the problem. What is missing from analyses of this sort is the time that the healthcare professional is separated from their central task; in this case the surgeon performing thoracic surgery. This paper provides a conceptual and quantitative metric that allows for the practical application of proactive methods for identifying systemic threats.

Using Broken Windows Theory as the Backdrop for a Proactive Approach to Threat Identification in Health Care.

Historically, health care has relied on error management techniques to measure and reduce the occurrence of adverse events. This study proposes an alternative approach for identifying and analyzing hazardous events. Whereas previous research has concentrated on investigating individual flow disruptions, we maintain the industry should focus on threat windows, or the accumulation of these disruptions. This methodology, driven by the broken windows theory, allows us to identify process inefficiencies before they manifest and open the door for the occurrence of errors and adverse events. Medical human factors researchers observed disruptions during 34 trauma cases at a Level II trauma center. Data were collected during resuscitation and imaging and were classified using a human factors taxonomy: Realizing Improved Patient Care Through Human-Centered Operating Room Design for Threat Window Analysis (RIPCHORD-TWA). Of the 576 total disruptions observed, communication issues were the most prevalent (28%), followed by interruptions and coordination issues (24% each). Issues related to layout (16%), usability (5%), and equipment (2%) comprised the remainder of the observations. Disruptions involving communication issues were more prevalent during resuscitation, whereas coordination problems were observed more frequently during imaging. Rather than solely investigating errors and adverse events, we propose conceptualizing the accumulation of disruptions in terms of threat windows as a means to analyze potential threats to the integrity of the trauma care system. This approach allows for the improved identification of system weaknesses or threats, affording us the ability to address these inefficiencies and intervene before errors and adverse events may occur.

Identifying workflow disruptions in the cardiovascular operating room

The objectives of this study were to identify the frequency and nature of flow disruptions in the operating room with respect to three cardiac surgical team members: anaesthetists; circulating nurses; and perfusionists. Data collected from 15 cases and coded using a human factors taxonomy identified 878 disruptions. Significant differences wereidentified in frequency relative to discipline type. Circulating nurses experienced more coordination disruptions (χ(2) (2, N=110)=7.136, p<0.028) and interruptions (χ(2) (2, N=427)=29.743, p=0.001) than anaesthetists andperfusionists, whereas anaesthetists and perfusionists experienced more layout issues than circulating nurses (χ(2) (2, N=153)=48.558, p=0.001). Time to resolve disruptions also varied among disciplines (λ (12, 878)=5.186, p=0.000). Although most investigations take a one-size fits all approach in addressing disruptions to flow, this study demonstrates that targeted interventions must focus on differences with respect to individual role.

Human Factors in Financial Trading: An Analysis of Trading Incidents.

ObjectiveThis study tests the reliability of a system (FINANS) to collect and analyze incident reports in the financial trading domain and is guided by a human factors taxonomy used to describe error in the trading domain.BackgroundResearch indicates the utility of applying human factors theory to understand error in finance, yet empirical research is lacking. We report on the development of the first system for capturing and analyzing human factors–related issues in operational trading incidents.MethodIn the first study, 20 incidents are analyzed by an expert user group against a referent standard to establish the reliability of FINANS. In the second study, 750 incidents are analyzed using distribution, mean, pathway, and associative analysis to describe the data.ResultsKappa scores indicate that categories within FINANS can be reliably used to identify and extract data on human factors–related problems underlying trading incidents. Approximately 1% of trades (n = 750) lead to an incident. Slip/lapse (61%), situation awareness (51%), and teamwork (40%) were found to be the most common problems underlying incidents. For the most serious incidents, problems in situation awareness and teamwork were most common.ConclusionWe show that (a) experts in the trading domain can reliably and accurately code human factors in incidents, (b) 1% of trades incur error, and (c) poor teamwork skills and situation awareness underpin the most critical incidents.ApplicationThis research provides data crucial for ameliorating risk within financial trading organizations, with implications for regulation and policy.

Development of a bespoke human factors taxonomy for gliding accident analysis and its revelations about highly inexperienced UK glider pilots

Low-hours solo glider pilots have a high risk of accidents compared to more experienced pilots. Numerous taxonomies for causal accident analysis have been produced for powered aviation but none of these is suitable for gliding, so a new taxonomy was required. A human factors taxonomy specifically for glider operations was developed and used to analyse all UK gliding accidents from 2002 to 2006 for their overall causes as well as factors specific to low hours pilots. Fifty-nine categories of pilot-related accident causation emerged, which were formed into progressively larger categories until four overall human factors groups were arrived at: ‘judgement’; ‘handling’; ‘strategy’; ‘attention’. ‘Handling’ accounted for a significantly higher proportion of injuries than other categories. Inexperienced pilots had considerably more accidents in all categories except ‘strategy’. Approach control (path judgement, airbrake and speed handling) as well as landing flare misjudgement were chiefly responsible for the high accident rate in early solo glider pilots. Statement of Relevance: This paper uses extant accident data to produce a taxonomy of underlying human factors causes to analyse gliding accidents and identify the specific causes associated with low hours pilots. From this specific, well-targeted remedial measures can be identified.

Statement of Retraction

This article refers to:Development of a bespoke human factors taxonomy for gliding accident analysis and its revelations about highly inexperienced UK glider pilotsThe effect of overwing hatch placement on evacuation from smaller transport aircraft

Development of a bespoke human factors taxonomy for gliding accident analysis and its revelations about highly inexperienced UK glider pilots

Low-hours solo glider pilots have a high risk of accidents compared to more experienced pilots. Numerous taxonomies for causal accident analysis have been produced for powered aviation but none of these is suitable for gliding, so a new taxonomy was required. A human factors taxonomy specifically for glider operations was developed and used to analyse all UK gliding accidents from 2002 to 2006 for their overall causes as well as factors specific to low hours pilots. Fifty-nine categories of pilot-related accident causation emerged, which were formed into progressively larger categories until four overall human factors groups were arrived at: ‘judgement’; ‘handling’; ‘strategy’; ‘attention’. ‘Handling’ accounted for a significantly higher proportion of injuries than other categories. Inexperienced pilots had considerably more accidents in all categories except ‘strategy’. Approach control (path judgement, airbrake and speed handling) as well as landing flare misjudgement were chiefly responsible for the high accident rate in early solo glider pilots.

Human Factors Taxonomy

This paper: 1) describes the need for a human-factors taxonomy; 2) identifies existing taxonomies from the scientific, training, test and evaluation, and mission modeling disciplines; 3) lists the rules used in combining these taxonomies into a single, coherent taxonomy; 4) presents the taxonomy at its top levels; and 5) provides a source for obtaining a copy of the AIAA Human-Factors Taxonomy standard.