Macroergonomics and patient safety: The impact of levels on theory, measurement, analysis and intervention in patient safety research

The study and practice of patient safety has seen a surge over the last 10 years. New resident training and staffing policies, health information technologies, error reporting systems, team models of care, training methods, patient involvement, information handoff strategies, just cultures, and many other interventions have been mandated or attempted to improve the safety of patient care. While some of these interventions focus on individual providers and others focus on organization-level changes, little, if any, patient safety research has purposefully sought to understand how variables at different levels, such as the provider level or organization level, interact to impact patient safety outcomes such as errors, adverse drug events, or patient harm. Looking at relationships across levels is important because adverse events might be related to variables at different levels; consider that adverse events may be nested within patients, patients nested within nurses and physicians, nurses and physicians nested within shifts, shifts nested within hospital units, and so forth. Because these nested levels exist, they may exert as yet untested influence on the levels below. In this paper the impact of levels on theory, measurement, analysis and intervention in patient safety research is discussed.     

Macroergonomics: analysis and design of work systems

Attending to the larger system components such as organizational design and management is not novel for ergonomists. In Europe, there has been a strong tradition to investigate ergonomic problems within a holistic, systems context. "Macroergonomics" builds upon this tradition by providing specific methods and tools that yield large-scale results. It is believed that meaningful and large-scale results are needed in today's competitive and turbulent work environments. Macroergonomics is defined, its history is uncovered and focus is given to a key methodology, macroergonomic analysis and design. Case studies are used to validate the method and illustrate that performance results in the 60-90% range can be expected.     

Applying ergonomics to systems: some documented "lessons learned"

Based on evidence accumulated during the author's 45 years of professional experience, the author presents 23 important “lessons learned” regarding applying ergonomics to systems. Documented results from reported cases or other evidence are presented to validate each of these practical learning points.     

Patient safety, systems design and ergonomics

The complexity of the health care environments necessitates an holistic and systematic ergonomics approach to understand the potential for accidents and errors to occur. The health service is also a socio-technical system, and design needs must be met within this context. This paper aims to present the design challenges and emphasises the specialised needs of the health care sector, when dealing with patient safety. It also provides examples of approaches and methods that ergonomists can bring to help inform our knowledge of these systems and the potential towards improving their safety. Mapping workshops provide an example of such methods. Results from these are used to illustrate how the knowledge base required for better design requirements can be generated. The workshops were developed specifically to help improve the design of medication packaging and thereby reduce the probability of medication error. The issues raised are now the subject of further research, design requirements guidance and new design concepts. The paper illustrates the need to engage with the design community and, through the use of robust scientific methods, to generate appropriate design requirements.     

Human factors systems approach to healthcare quality and patient safety

Human factors systems approaches are critical for improving healthcare quality and patient safety. The SEIPS (Systems Engineering Initiative for Patient Safety) model of work system and patient safety is a human factors systems approach that has been successfully applied in healthcare research and practice. Several research and practical applications of the SEIPS model are described. Important implications of the SEIPS model for healthcare system and process redesign are highlighted. Principles for redesigning healthcare systems using the SEIPS model are described. Balancing the work system and encouraging the active and adaptive role of workers are key principles for improving healthcare quality and patient safety.     

面向安全关键系统的实时数据处理软件设计

介绍了一种针对单片机、PSD,12C接口存储芯片为主要组件设计的一类针对安全关键系统的测量与控制装置的实时软件设计、数据传输、存储及处理方法。通过各项实验考核表明,这种设计方法可靠灵活、高效,而且有较好的开放性及通用性。     

Using an ethnographic process to conduct requirements analysis for agile systems development

Since the late 1990s, agile or lightweight software development methodologies have experienced a meteoric rise of interest among systems developers who consider traditional systems development methodologies (such as Structured Systems Development, Information Engineering, and Rational Unified Process) too inflexible for building systems having unpredictable and changing requirements. Agile methodologies try to adapt to rapid requirement changes by having short, iterative development cycles and by encouraging frequent, open communication with customers. However, agile methodologies are still in the process of devising systematic approaches on how to be adaptive to unpredictable and changing requirements and how to incorporate customers into the systems development process. In this study, we show how an ethnographic research process called Strip Resolution can be applied as a systematic complement to projects applying agile development principles. We illustrate, in detail, how the Strip Resolution Process (SRP) enabled us, in the role of systems developers, to adapt to changing and unpredictable user requirements and to incorporate customers into the systems development process.     

Computer vision techniques for construction safety and health monitoring

For construction safety and health, continuous monitoring of unsafe conditions and action is essential in order to eliminate potential hazards in a timely manner. As a robust and automated means of field observation, computer vision techniques have been applied for the extraction of safety related information from site images and videos, and regarded as effective solutions complementary to current time-consuming and unreliable manual observational practices. Although some research efforts have been directed toward computer vision-based safety and health monitoring, its application in real practice remains premature due to a number of technical issues and research challenges in terms of reliability, accuracy, and applicability. This paper thus reviews previous attempts in construction applications from both technical and practical perspectives in order to understand the current status of computer vision techniques, which in turn suggests the direction of future research in the field of computer vision-based safety and health monitoring. Specifically, this paper categorizes previous studies into three groups—object detection, object tracking, and action recognition—based on types of information required to evaluate unsafe conditions and acts. The results demonstrate that major research challenges include comprehensive scene understanding, varying tracking accuracy by camera position, and action recognition of multiple equipment and workers. In addition, we identified several practical issues including a lack of task-specific and quantifiable metrics to evaluate the extracted information in safety context, technical obstacles due to dynamic conditions at construction sites and privacy issues. These challenges indicate a need for further research in these areas. Accordingly, this paper provides researchers insights into advancing knowledge and techniques for computer vision-based safety and health monitoring, and offers fresh opportunities and considerations to practitioners in understanding and adopting the techniques.     

A component-based simulation environment for statistical process control systems analysis

This paper describes a simulation environment, called Prosim, which permits a user to define components, subsystems, and their interconnections to analyse a statistical process control (SPC) system. The components and systems are defined and analysed interactively. A library of standard SPC objects containing models for the Xbar, range, exponential weighted moving average, p-chart and other SPC techniques have been created which help define the control application. The PC-based tool is tested on theoretical, and real data, and is useful for the design and trouble shooting of a manufacturing system. It is also an effective teaching and research tool.     

Analytic hierarchy process: It can work for group decision support systems

Most group problems are complex and unstructured and are difficult to find solutions, GDSS, systems for group decision making support, have more concentrated on the development of technological factor such as communication support, electronic meeting support, etc. And there have been relatively few researches about group problem modeling and group decision-aid. We cannot guarantee the value of GDSS just with the support in technological basis. The AHP has been suggested as an group problem modeling tool. In this paper authors applied AHP in real world group problems, investigated its value. and suggested the elements of GDSS software.     

Micro- and macroergonomic changes in mental workload and medication safety following the implementation of new health IT

Health information technology (IT) is a promising way to achieve safer medication management in the delivery of healthcare. However, human factors/ergonomics dictates that in order to make the complex, cognitive work of healthcare delivery safer, health IT must properly support human cognition. This means, for example, that new health IT must reduce, not increase, workload during safety-critical tasks. The present study was the first to quantitatively assess the short- and long-term impact of bar coded medication administration (BCMA) IT on nurses' mental workload as well as on perceived medication safety. One-hundred seventy registered nurses across 3 dissimilar clinical units at an academic, freestanding pediatric hospital in the Midwest US participated in surveys administered before, 3 months after, and 12 months after the hospital implemented BCMA. Nurses rated their external mental workload (interruptions, divided attention, being rushed) and internal mental workload (concentration, mental effort) during medication administration tasks as well as the likelihood of each of three medication safety events: medication administration errors, medication errors on the clinical unit, and clinical unit-level adverse drug events. Clinical unit differences were assessed. Findings generally confirmed the hypothesis that external but not internal mental workload was associated with the perceived likelihood of a medication safety event. Comparisons of mental workload from pre- to post-BCMA revealed statistically significant changes in the critical care unit only. Medication safety appeared to improve over the long term in the hematology/oncology unit only. In the critical care and medical/surgical units, medication safety exhibited short-term improvements that were eliminated over time. Changes in mental workload and medication safety, two classically microergonomic constructs, were deeply embedded in macroergonomic phenomena. These included the fit between the BCMA system and the nature of nursing work, the process of BCMA implementation, and BCMA interactions with concurrent changes occurring in the hospital. Findings raise questions about achieving sustainable performance improvement with health IT as well as the balance between micro- and macroergonomic approaches to studying technology change.Relevance to industryDesigners must consider how technology changes cognitive work, including mental workload. Hospitals and other implementers of technology must ensure that new technology fits its users, their tasks, and the context of use, which may entail tailoring implementation, for example, to specific clinical units. Evaluators must look over time to assess both changes in cognitive work and implementation issues. Healthcare practitioners must also recognize that new technology means a complex transformation to an already complex sociotechnical system, which calls for a macroergonomic approach to design and analysis.     

化工过程本质安全评价指标的研究进展

介绍了本质安全指标方法的研究现状,对各类方法的基本原理及特点进行了阐述,通过系统地分析比较所有本质安全指标方法的适用阶段、评价范围和特点,总结了本质安全指标方法的演变脉络,综合评述了本质安全指标方法未来的发展前景,提出了本质安全指标方法的4个研究方向:建立综合的本质SHE指标;克服指标区间划分和权重设置的主观性;强化指标分析的逻辑性;本质安全指标与过程设计方法、工具的紧密集成.     

A new class of intelligent knowledge-based systems with an optimisation-based inference engine

In this paper we describe a new class of intelligent knowledge-based system (IKBS) which can be used principally for managerial decision making applications. This class of applications often requires a framework for knowledge acquisition which allows the system to use the knowledge of several experts. In addition, since in most business decision making the objective is maximise profits, there is a need for an inference engine which allows optimisation to be carried out. The new class of IKBS which is described in this paper has both these properties, i.e., the ability to use the knowledge of multiple experts in a convenient way and an inference engine which by performing optimisations is able to pick out the profit maximising decisions. As an illustration of these concepts, a system for allocation decision making is described. The system ‘Retail-opt’ allows the user to solve problems like allocation of space in retail outlets, allocation of space in mail order catalogues, pricing policy decisions for discounted airline tickets, etc. In the paper, the basic concepts behind ‘Retail-opt’ are described and an application of ‘Retail-opt’ to the problem of retail space allocation in a Scandinavian Department Store is given. A number of other systems which use these concepts for more complicated competitive decision making situations are also described.     

Brain signal-based safety measure activation for robotic systems

In this paper, we present our approach for using EEG signals to activate safety measures of a robot when an error or unexpected event is perceived by the human operator. In particular, we consider brain-based error perception while the operator passively observes the robot performing an action. Our approach consists of monitoring EEG signals and detecting a brain potential called error related negativity (ERN) that spontaneously occurs when the operator perceives an error made by the robot or when an unexpected event occurs. We detect ERN by pre-training two linear classifiers using data collected from a preliminary experiment based on a visual reaction task. We derive the probability of failure in demand (PFD), commonly used to assess functional safety for a two-channel verification system based on the combination of linear classifiers. Functional safety analysis was then performed on a BMI-based robotic framework in which a signal was sent to the robot to active its safety measures in when an ERN was detected. Using brain-based signals, we demonstrate that it is possible to send an emergency stop action during mobile navigation task when unexpected events occur with an accuracy of 75%.     

Human factors in patient safety as an innovation

The use of Human Factors and Ergonomics (HFE) tools, methods, concepts and theories has been advocated by many experts and organizations to improve patient safety. To facilitate and support the spread of HFE knowledge and skills in healthcare and patient safety, we propose to conceptualize HFE as innovations whose diffusion, dissemination, implementation and sustainability need to be understood and specified. Using Greenhalgh et al. (2004) model of innovation, we identified various factors that can either hinder or facilitate the spread of HFE innovations in healthcare organizations. Barriers include lack of systems thinking, complexity of HFE innovations and lack of understanding about the benefits of HFE innovations. Positive impact of HFE interventions on task performance and the presence of local champions can facilitate the adoption, implementation and sustainability of HFE innovations. This analysis concludes with a series of recommendations for HFE professionals, researchers and educators.     

面向安全关键系统的CAN总线应用研究综述*

控制器局域网适合小型安全关键系统的现场总线控制要求,能够以最大1Mbps速率发送和接收实时短消息。分析了CAN总线的结构、特点、协议仲裁机制、接口设计方法、实时特性和错误处理机制。为了支持任务关键网络,比较了事件触发协议与时间触发协议的特性,讨论了时间触发CAN协议的研究进展。     

化工过程安全智能技术系统集成

研究基于PID的化工过程安全智能技术,内容包括:(1)开发基于智能PID的计算机辅助HAZOP分析技术;(2)提出把HAZOP分析结果自动转换成故障树的新方法;(3)开发操作规程信息化管理技术;(4)开发可视化设备管理技术。最后,集成上述这些技术,开发实用性的新一代化工过程安全保障综合支撑系统,以乙炔加氢反应装置失控反应的安全评价为例进行应用验证。     

Human factors of complex sociotechnical systems

Increasingly products and services result from interactions among people who work across organizational, geographical, cultural and temporal boundaries. This has major implications for human factors and ergonomics (HFE), in particular, challenging the limits of the systems to be designed, and widening the range of system elements and dimensions that we need to consider. The design of sociotechnical systems that involve work across multiple boundaries requires better integration of the various sub-disciplines or components of HFE, as well as increased collaboration with other disciplines that provide either expertise regarding the domain of application or expertise in concepts that can enrich the system design. In addition, 'customers' contribute significantly to the 'co-production' of products/services, as well as to their quality/safety. The design of sociotechnical systems in collaboration with both the workers in the systems and the customers requires increasing attention not only to the design and implementation of systems, but also to the continuous adaptation and improvement of systems in collaboration with customers. This paper draws from research on human factors in the domains of health care and patient safety and of computer security.