What Happened, and Why: Toward an Understanding of Human Error Based on Automated Analyses of Incident Reports

The objective of the Aviation System Monitoring and Modeling project of NASA's Aviation Safety and Security Program was to develop technologies to enable proactive management of safety risk, which entails identifying the precursor events and conditions that foreshadow most accidents. Information about what happened can be extracted from quantitative data sources, but the experiential account of the incident reporter is the best available source of information about why an incident happened. In Volume I, the concept of the Scenario was introduced as a pragmatic guide for identifying similarities of what happened based on the objective parameters that define the Context and the Outcome of a Scenario. In this Volume II, that study continues into the analyses of the free narratives to gain understanding as to why the incident occurred from the reporter s perspective. While this is just the first experiment, the results of our approach are encouraging and indicate that it will be possible to design an automated analysis process guided by the structure of the Scenario that can achieve the level of consistency and reliability of human analysis of narrative reports

Recommendations for the quantitative analysis of landslide risk

This paper presents recommended methodologies for the quantitative analysis of landslide hazard, vulnerability and risk at different spatial scales (site-specific, local, regional and national), as well as for the verification and validation of the results. The methodologies described focus on the evaluation of the probabilities of occurrence of different landslide types with certain characteristics. Methods used to determine the spatial distribution of landslide intensity, the characterisation of the elements at risk, the assessment of the potential degree of damage and the quantification of the vulnerability of the elements at risk, and those used to perform the quantitative risk analysis are also described. The paper is intended for use by scientists and practising engineers, geologists and other landslide experts.JRC.H.5-Land Resources Managemen

Rehabilitation Therapy Services For Older Long–Stay Clients in the Ontario Home Care System

BACKGROUND Rehabilitation therapies are effective for older persons in home-based settings, and have the potential to save money for the health system, while also improving the quality of life for older adults who may otherwise be hospitalized or institutionalized. Although there is evidence that home-based rehabilitation can improve functional outcomes in older adults, research has shown that many older home care clients do not receive the rehabilitation services they need. Despite the home care sector’s increasing importance within Ontario’s health care system, we have a limited understanding of the population that currently utilizes these services and how these services are allocated in the province. This dissertation project aims to enhance the understanding of this domain using a large provincial data repository of home care client information (RAI-HC information system). METHODS Using the Andersen-Newman Framework to guide this research from a conceptual standpoint, and combining it with the CRoss Industry Standard Process for Data Mining (CRISP-DM) as an organizational framework, this dissertation focuses on examining data collected on older long-stay home care clients. Prior to the data mining modeling procedures, knowledge of the rehabilitation services in home care was developed through a series of semi-structured interviews with key informants. The results of this qualitative study were then used to inform quantitative analyses that included creating rehabilitation service user profiles using the K-means clustering algorithm, and the development of predictive models of rehabilitation service provision using a Random forest algorithm and multilevel models. RESULTS Older home care clients who receive occupational therapy and physiotherapy in the Ontario Home Care System form a complex and heterogeneous client population. These services are often provided to clients following an acute event, yet many older adults who could benefit from therapy services for functional improvement and maintenance are not provided services due to limited resources. K-means clustering analyses resulted in the creation of seven profiles of rehab service users illustrating the multidimensional diversity of the service user population. Predictive models were able to identify client characteristics that are commonly associated with service provision. These models confirmed the large amount of regional variation found across the province and highlighted the differences between factors that lead to occupational therapy and physiotherapy service provision. CONCLUSIONS Using multiple methods to systematically examine rehabilitation services for long-stay clients, new insights into the current user population and the client characteristics related to service provision were obtained. Future research activities should focus on ways to use the regularly collected standardized data to identify older long-stay home care clients who would benefit most from the rehabilitation therapy services provided by the provincial home care system

Novel Approaches in Landslide Monitoring and Data Analysis

Significant progress has been made in the last few years that has expanded the knowledge of landslide processes. It is, therefore, necessary to summarize, share and disseminate the latest knowledge and expertise. This Special Issue brings together novel research focused on landslide monitoring, modelling and data analysis

A Hybrid Modelling Framework for Real-time Decision-support for Urgent and Emergency Healthcare

In healthcare, opportunities to use real-time data to support quick and effective decision-making are expanding rapidly, as data increases in volume, velocity and variety. In parallel, the need for short-term decision-support to improve system resilience is increasingly relevant, with the recent COVID-19 crisis underlining the pressure that our healthcare services are under to deliver safe, effective, quality care in the face of rapidly-shifting parameters. A real-time hybrid model (HM) which combines real-time data, predictions, and simulation, has the potential to support short-term decision-making in healthcare. Considering decision-making as a consequence of situation awareness focuses the HM on what information is needed where, when, how, and by whom with a view toward sustained implementation. However the articulation between real-time decision-support tools and a sociotechnical approach to their development and implementation is currently lacking in the literature. Having identified the need for a conceptual framework to support the development of real-time HMs for short-term decision-support, this research proposed and tested the Integrated Hybrid Analytics Framework (IHAF) through an examination of the stages of a Design Science methodology and insights from the literature examining decision-making in dynamic, sociotechnical systems, data analytics, and simulation. Informed by IHAF, a HM was developed using real-time Emergency Department data, time-series forecasting, and discrete-event simulation. The application started with patient questionnaires to support problem definition and to act as a formative evaluation, and was subsequently evaluated using staff interviews. Evaluation of the application found multiple examples where the objectives of people or sub-systems are not aligned, resulting in inefficiencies and other quality problems, which are characteristic of complex adaptive sociotechnical systems. Synthesis of the literature, the formative evaluation, and the final evaluation found significant themes which can act as antecedents or evaluation criteria for future real-time HM studies in sociotechnical systems, in particular in healthcare. The generic utility of IHAF is emphasised for supporting future applications in similar domains

Risk Management for the Future

A large part of academic literature, business literature as well as practices in real life are resting on the assumption that uncertainty and risk does not exist. We all know that this is not true, yet, a whole variety of methods, tools and practices are not attuned to the fact that the future is uncertain and that risks are all around us. However, despite risk management entering the agenda some decades ago, it has introduced risks on its own as illustrated by the financial crisis. Here is a book that goes beyond risk management as it is today and tries to discuss what needs to be improved further. The book also offers some cases

Remote sensing applied to landslide risk management and governance

The main objective of this doctoral thesis is to analyze the use of remote sensors, the information that can be obtained to determine how these sensors and methodologies can be used to generate and update geospatial information for risk management and governance. To acquire this objective, after an extensive review, it is intended to develop from a purely practical and applied point of view, which are materialized in different case studies. And, applied to projects that are immersed in risk management focused on mass movements in Ecuador. This thesis is conformed of six chapters addressing mass movements from different perspectives objectives and, study areas

Recommendations for the quantitative analysis of landslide risk

This paper presents recommended methodologies for the quantitative analysis of landslide hazard, vulnerability and risk at different spatial scales (site-specific, local, regional and national), as well as for the verification and validation of the results. The methodologies described focus on the evaluation of the probabilities of occurrence of different landslide types with certain characteristics. Methods used to determine the spatial distribution of landslide intensity, the characterisation of the elements at risk, the assessment of the potential degree of damage and the quantification of the vulnerability of the elements at risk, and those used to perform the quantitative risk analysis are also described. The paper is intended for use by scientists and practising engineers, geologists and other landslide experts