Lack of appropriate and sufficient human performance data has been identified as a key factor affecting human reliability analysis (HRA) quality especially in the estimation of human error ...probability (HEP). The Scenario Authoring, Characterization, and Debriefing Application (SACADA) database was developed by the U.S. Nuclear Regulatory Commission (NRC) to address this data need. An agreement between NRC and the South Texas Project Nuclear Operating Company (STPNOC) was established to support the SACADA development with aims to make the SACADA tool suitable for implementation in the nuclear power plants' operator training program to collect operator performance information. The collected data would support the STPNOC's operator training program and be shared with the NRC for improving HRA quality. This paper discusses the SACADA data taxonomy, the theoretical foundation, the prospective data to be generated from the SACADA raw data to inform human reliability and human performance, and the considerations on the use of simulator data for HRA. Each SACADA data point consists of two information segments: context and performance results. Context is a characterization of the performance challenges to task success. The performance results are the results of performing the task. The data taxonomy uses a macrocognitive functions model for the framework. At a high level, information is classified according to the macrocognitive functions of detecting the plant abnormality, understanding the abnormality, deciding the response plan, executing the response plan, and team related aspects (i.e., communication, teamwork, and supervision). The data are expected to be useful for analyzing the relations between context, error modes and error causes in human performance.
Background The importance of leadership is recognized in surgery, but the specific impact of leadership style on team behavior is not well understood. In other industries, leadership is a ...well-characterized construct. One dominant theory proposes that transactional (task-focused) leaders achieve minimum standards and transformational (team-oriented) leaders inspire performance beyond expectations. Study Design We videorecorded 5 surgeons performing complex operations. Each surgeon was scored on the Multifactor Leadership Questionnaire, a validated method for scoring transformational and transactional leadership style, by an organizational psychologist and a surgeon researcher. Independent coders assessed surgeons' leadership behaviors according to the Surgical Leadership Inventory and team behaviors (information sharing, cooperative, and voice behaviors). All coders were blinded. Leadership style (Multifactor Leadership Questionnaire) was correlated with surgeon behavior (Surgical Leadership Inventory) and team behavior using Poisson regression, controlling for time and the total number of behaviors, respectively. Results All surgeons scored similarly on transactional leadership (range 2.38 to 2.69), but varied more widely on transformational leadership (range 1.98 to 3.60). Each 1-point increase in transformational score corresponded to 3 times more information-sharing behaviors (p < 0.0001) and 5.4 times more voice behaviors (p = 0.0005) among the team. With each 1-point increase in transformational score, leaders displayed 10 times more supportive behaviors (p < 0.0001) and displayed poor behaviors 12.5 times less frequently (p < 0.0001). Excerpts of representative dialogue are included for illustration. Conclusions We provide a framework for evaluating surgeons' leadership and its impact on team performance in the operating room. As in other fields, our data suggest that transformational leadership is associated with improved team behavior. Surgeon leadership development, therefore, has the potential to improve the efficiency and safety of operative care.
The Oxford Handbook of Expertise Ward, Paul; Schraagen, Jan Maarten; Gore, Julie ...
Oxford University Press eBooks,
11/2019
eBook, Book
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The purpose of this Handbook is to provide a comprehensive picture of the field of Expertise Studies. We offer both traditional and contemporary perspectives, and importantly, a ...multidiscipline-multimethod view of the science and engineering research on expertise. We present different perspectives, theories, and methods of conducting expertise research, all of which have had an impact in helping us better understanding expertise across a broad range of domains. The Handbook also describes how researchers and practitioners have addressed practical problems and societal challenges. We have sought to demonstrate the heterogeneity of approaches and conceptions of expertise, to place current views of expertise in context, to show how these views can be used to address current issues, and to examine ways to advance the study of expertise.
To better understand the operating room as a system and to identify system features that influence patient safety, we performed an analysis of operating room patient care using a prospective ...observational technique.
A multidisciplinary team comprised of human factors experts and surgeons conducted prospective observations of 10 complex general surgery cases in an academic hospital. Minute-to-minute observations were recorded in the field, and later coded and analyzed. A qualitative analysis first identified major system features that influenced team performance and patient safety. A quantitative analysis of factors related to these systems features followed. In addition, safety-compromising events were identified and analyzed for contributing and compensatory factors.
Problems in communication and information flow, and workload and competing tasks were found to have measurable negative impact on team performance and patient safety in all 10 cases. In particular, the counting protocol was found to significantly compromise case progression and patient safety. We identified 11 events that potentially compromised patient safety, allowing us to identify recurring factors that contributed to or mitigated the overall effect on the patient's outcome.
This study demonstrates the role of prospective observational methods in exposing critical system features that influence patient safety and that can be the targets for patient safety initiatives. Communication breakdown and information loss, as well as increased workload and competing tasks, pose the greatest threats to patient safety in the operating room.
Deconstructing intraoperative communication failures Hu, Yue-Yung, MD, MPH; Arriaga, Alexander F., MD, MPH; Peyre, Sarah E., EdD ...
The Journal of surgical research,
09/2012, Letnik:
177, Številka:
1
Journal Article
Recenzirano
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Abstract Background Communication failure is a common contributor to adverse events. We sought to characterize communication failures during complex operations. Methods We video recorded and ...transcribed six complex operations, representing 22 h of patient care. For each communication event, we determined the participants and the content discussed. Failures were classified into four types: audience (key individuals missing), purpose (issue nonresolution), content (insufficient/inaccurate information), and/or occasion (futile timing). We added a systems category to reflect communication occurring at the organizational level. The impact of each identified failure was described. Results We observed communication failures in every case (mean 29, median 28, range 13–48), at a rate of one every 8 min. Cross-disciplinary exchanges resulted in failure nearly twice as often as intradisciplinary ones. Discussions about or mandated by hospital policy (20%), personnel (18%), or other patient care (17%) were most error prone. Audience and purpose each accounted for >40% of failures. A substantial proportion (26%) reflected flawed systems for communication, particularly those for disseminating policy (29% of system failures), coordinating personnel (27%), and conveying the procedure planned (27%) or the equipment needed (24%). In 81% of failures, inefficiency (extraneous discussion and/or work) resulted. Resource waste (19%) and work-arounds (13%) also were frequently seen. Conclusions During complex operations, communication failures occur frequently and lead to inefficiency. Prevention may be achieved by improving synchronous, cross-disciplinary communication. The rate of failure during discussions about/mandated by policy highlights the need for carefully designed standardized interventions. System-level support for asynchronous perioperative communication may streamline operating room coordination and preparation efforts.
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•Cognitive engineering (CE) has roots in cognitive science and engineering.•It provides structured, analytic methods for data collection and analysis.•CE intersect with and ...complements methods of cognitive informatics.•Health information technology systems can benefit from CE informed design.
Cognitive engineering is an applied field with roots in both cognitive science and engineering that has been used to support design of information displays, decision support, human-automation interaction, and training in numerous high risk domains ranging from nuclear power plant control to transportation and defense systems. Cognitive engineering provides a set of structured, analytic methods for data collection and analysis that intersect with and complement methods of Cognitive Informatics. These methods support discovery of aspects of the work that make performance challenging, as well as the knowledge, skills, and strategies that experts use to meet those challenges. Importantly, cognitive engineering methods provide novel representations that highlight the inherent complexities of the work domain and traceable links between the results of cognitive analyses and actionable design requirements. This article provides an overview of relevant cognitive engineering methods, and illustrates how they have been applied to the design of health information technology (HIT) systems. Additionally, although cognitive engineering methods have been applied in the design of user-centered informatics systems, methods drawn from informatics are not typically incorporated into a cognitive engineering analysis. This article presents a discussion regarding ways in which data-rich methods can inform cognitive engineering.
•Efforts has been made on improving patient assignment at triage to improve clinician workload management.•Data contained within the EHR have the potential to support automatic patient-related ...workload prediction.•One can predict patient-related workload at the early stage of patient visit and update the prediction as the visit proceeds.•The predicted workload can be used to in assigning new patients to clinicians in a way that better balanced workload, or to identify clinicians that are overloaded.
Understanding and managing clinician workload is important for clinician (nurses, physicians and advanced practice providers) occupational health as well as patient safety. Efforts have been made to develop strategies for managing clinician workload by improving patient assignment. The goal of the current study is to use electronic health record (EHR) data to predict the amount of work that individual patients contribute to clinician workload (patient-related workload).
One month of EHR data was retrieved from an emergency department (ED). A list of workload indicators and five potential workload proxies were extracted from the data. Linear regression and four machine learning classification algorithms were utilized to model the relationship between the indicators and the proxies.
Linear regression proved that the indicators explained a substantial amount of variance of the proxies (four out of five proxies were modeled with R2 > 0.80). Classification algorithms also showed success in classifying a patient as having high or low task demand based on data from early in the ED visit (e.g. 80 % accurate binary classification with data from the first hour).
The main contribution of this study is demonstrating the potential of using EHR data to predict patient-related workload automatically in the ED. The predicted workload can potentially help in managing clinician workload by supporting decisions around the assignment of new patients to providers. Future work should focus on identifying the relationship between workload proxies and actual workload, as well as improving prediction performance of regression and multi-class classification.
Nurses working in the hospital setting increasingly have become overburdened by managing alarms that, in many cases, provide low information value regarding patient health. The current trend, aided ...by disposable, wearable technologies, is to promote patient monitoring that does not require entering a patient's room. The development of telemetry alarms and middleware escalation devices adds to the continued growth of auditory, visual, and haptic alarms to the hospital environment but can fail to provide a more complete understanding of patient health. As we begin to innovate to both address alarm overload and improve patient management, perhaps using fundamentally different integration architectures, lessons from the aviation flight deck are worth considering. Commercial jet transport systems and their alarms have evolved slowly over many decades and have developed integration methods that account for operational context, provide multiple response protocol levels, and present a more integrated view of the airplane system state. We articulate three alarm system objectives: (1) supporting hazard management, (2) establishing context, and (3) supporting alarm prioritization. More generally, we present the case that alarm design in aviation can spur directions for innovation for telemetry monitoring systems in hospitals.
To understand the etiology and resolution of unanticipated events in the operating room (OR).
The majority of surgical adverse events occur intraoperatively. The OR represents a complex, high-risk ...system. The influence of different human, team, and organizational/environmental factors on safety and performance is unknown.
We video-recorded and transcribed 10 high-acuity operations, representing 43.7 hours of patient care. Deviations, defined as delays and/or episodes of decreased patient safety, were identified by majority consensus of a multidisciplinary team. Factors that contributed to each event and/or mitigated its impact were determined and attributed to the patient, providers, or environment/organization.
Thirty-three deviations (10 delays, 17 safety compromises, 6 both) occurred--with a mean of 1 every 79.4 minutes. These deviations were multifactorial (mean 3.1 factors). Problems with communication and organizational structure appeared repeatedly at the root of both types of deviations. Delays tended to be resolved with vigilance, communication, coordination, and cooperation, while mediation of safety compromises was most frequently accomplished with vigilance, leadership, communication, and/or coordination. The organization/environment was not found to play a direct role in compensation.
Unanticipated events are common in the OR. Deviations result from poor organizational/environmental design and suboptimal team dynamics, with caregivers compensating to avoid patient harm. Although recognized in other high-risk domains, such human resilience has not yet been described in surgery and has major implications for the design of safety interventions.
Objective: In this article, the author provides an overview of cognitive analysis methods and how they can be used to inform system analysis and design. Background: Human factors has seen a shift ...toward modeling and support of cognitively intensive work (e.g., military command and control, medical planning and decision making, supervisory control of automated systems). Cognitive task analysis and cognitive work analysis methods extend traditional task analysis techniques to uncover the knowledge and thought processes that underlie performance in cognitively complex settings. Methods: The author reviews the multidisciplinary roots of cognitive analysis and the variety of cognitive task analysis and cognitive work analysis methods that have emerged. Results: Cognitive analysis methods have been used successfully to guide system design, as well as development of function allocation, team structure, and training, so as to enhance performance and reduce the potential for error. Conclusions: A comprehensive characterization of cognitive work requires two mutually informing analyses: (a) examination of domain characteristics and constraints that define cognitive requirements and challenges and (b) examination of practitioner knowledge and strategies that underlie both expert and error-vulnerable performance. A variety of specific methods can be adapted to achieve these aims within the pragmatic constraints of particular projects. Application: Cognitive analysis methods can be used effectively to anticipate cognitive performance problems and specify ways to improve individual and team cognitive performance (be it through new forms of training, user interfaces, or decision aids).
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