An approach to safety analysis of clinical workflows

A clinical workflow considers the information and processes that are involved in providing a clinical service. They are safety critical since even minor faults have the potential to propagate and consequently cause harm to a patient, or even for a patient's life to be lost. Experiencing these kinds of failures has a destructive impact on all the involved parties. Due to the large number of processes and tasks included in the delivery of a clinical service, it can be difficult to determine the individuals or the processes that are responsible for adverse events, since such an analysis is typically complex and slow to do manually. Using automated tools to carry out an analysis can help in determining the root causes of potential adverse events and consequently help in avoiding preventable errors through either the alteration of existing workflows, or the design of a new workflow. This paper describes a technical approach to safety analysis of clinical workflows, utilising a safety analysis tool (Hierarchically-Performed Hazard Origin and Propagation Studies (HiP-HOPS)) that is already in use in the field of mechanical systems. The paper then demonstrates the applicability of the approach to clinical workflows by applying it to analyse the workflow in a radiology department. We conclude that the approach is applicable to this area of healthcare and provides a mechanism both for the systematic identification of adverse events and for the introduction of possible safeguards in clinical workflows

A safety analysis approach to clinical workflows : application and evaluation

Clinical workflows are safety critical workflows as they have the potential to cause harm or death to patients. Their safety needs to be considered as early as possible in the development process. Effective safety analysis methods are required to ensure the safety of these high-risk workflows, because errors that may happen through routine workflow could propagate within the workflow to result in harmful failures of the system’s output. This paper shows how to apply an approach for safety analysis of clinic al workflows to analyse the safety of the workflow within a radiology department and evaluates the approach in terms of usability and benefits. The outcomes of using this approach include identification of the root causes of hazardous workflow failures that may put patients’ lives at risk. We show that the approach is applicable to this area of healthcare and is able to present added value through the detailed information on possible failures, of both their causes and effects; therefore, it has the potential to improve the safety of radiology and other clinical workflows

Against the Grain: The Natural History of an Inter-disciplinary Faculty Development Program

Invited presentation about University Studies at the 1999 meeting of the Association for Higher Education: The union of the mathematician with the poet, fervor with measure, passion with correctness, this surely is the ideal. (William James) . . . . The twenty-five year history of the University of Tennessee\u27s University Studies Program illustrates . .

Energy managed reporting for wireless sensor networks

In this paper, we propose a technique to extend the network lifetime of a wireless sensor network, whereby each sensor node decides its individual network involvement based on its own energy resources and the information contained in each packet. The information content is ascertained through a system of rules describing prospective events in the sensed environment, and how important such events are. While the packets deemed most important are propagated by all sensor nodes, low importance packets are handled by only the nodes with high energy reserves. Results obtained from simulations depicting a wireless sensor network used to monitor pump temperature in an industrial environment have shown that a considerable increase in the network lifetime and network connectivity can be obtained. The results also show that when coupled with a form of energy harvesting, our technique can enable perpetual network operatio

Resource Aware Sensor Nodes in Wireless Sensor Networks

Wireless sensor networks are continuing to receive considerable research interest due, in part, to the range of possible applications. One of the greatest challenges facing researchers is in overcoming the limited network lifetime inherent in the small locally powered sensor nodes. In this paper, we propose IDEALS, a system to manage a wireless sensor network using a combination of information management, energy harvesting and energy monitoring, which we label resource awareness. Through this, IDEALS is able to extend the network lifetime for important messages, by controlling the degradation of the network to maximise information throughput

Heuristic Evaluation of Microsoft Teams as an Online Teaching Platform: An Educators’ Perspective

The way that education is delivered changed significantly during the COVID-19 pandemic to be completely online in many countries for many institutions. Despite the fact that they are not online teaching platforms, virtual meeting platforms were utilized to deal with this transformation. One of the platforms Philadelphia University utilized for the unplanned shift to online teaching was Microsoft Teams. This paper examines how heuristic evaluation may be used to guide the evaluation of online meeting platforms for teaching and focuses on the use of heuristic evaluation to assess the level of usability of Microsoft Teams. The level of Zoom’s usability is also evaluated using heuristic evaluation in order to compare it to that of Microsoft Teams and to assess Microsoft Teams’ overall usability in comparison to other platforms being used for the same purpose. Microsoft Teams was identified as having a few issues that need to be addressed. Additionally, strengths, weaknesses, opportunities, and threats to Microsoft Teams’ usability were assessed

A Structured Hardware/Software Architecture for Embedded Sensor Nodes

Owing to the limited requirement for sensor processing in early networked sensor nodes, embedded software was generally built around the communication stack. Modern sensor nodes have evolved to contain significant on-board functionality in addition to communications, including sensor processing, energy management, actuation and locationing. The embedded software for this functionality, however, is often implemented in the application layer of the communications stack, resulting in an unstructured, top-heavy and complex stack. In this paper, we propose an embedded system architecture to formally specify multiple interfaces on a sensor node. This architecture differs from existing solutions by providing a sensor node with multiple stacks (each stack implements a separate node function), all linked by a shared application layer. This establishes a structured platform for the formal design, specification and implementation of modern sensor and wireless sensor nodes. We describe a practical prototype of an intelligent sensing, energy-aware, sensor node that has been developed using this architecture, implementing stacks for communications, sensing and energy management. The structure and operation of the intelligent sensing and energy management stacks are described in detail. The proposed architecture promotes structured and modular design, allowing for efficient code reuse and being suitable for future generations of sensor nodes featuring interchangeable components

Application of Artificial Intelligence and Data Science in Detecting the Impact of Usability from Evaluation of Mobile Health Applications

Mobile health (mHealth) applications have demonstrated immense potential for facilitating preventative care and disease management through intuitive platforms. However, realizing transformational health objectives relies on creating accessible tools optimized for different users. This research analyses mHealth app usability data sourced from online repositories to reveal the impact of usability (ease of use) from evaluating mobile health applications. Thoroughly examining interfaces with a utilization of statistical tests of significance, platform, integra-tions, and various application features shows complex relationships between usability and users experience. This work shows that applying random forest models can accurately classify the ease-of-use of mHealth applications. This work sheds light on the connections between design choices and their effects, guiding intentional improvements to expand the reach of mHealth. It does so by providing insights into the subtle ways that people interact with mHealth applications. The methodologies and findings provide actionable insights for developers and practitioners passionate about advancing digital healthcare