Barriers and Facilitators of Suicide Risk Assessment in Emergency Departments: A Qualitative Study of Provider Perspectives

Objective To understand emergency department (ED) providers’ perspectives regarding the barriers and facilitators of suicide risk assessment and to use these perspectives to inform recommendations for best practices in ED suicide risk assessment. Methods Ninety-two ED providers from two hospital systems in a Midwestern state responded to open-ended questions via an online survey that assessed their perspectives on the barriers and facilitators to assess suicide risk as well as their preferred assessment methods. Responses were analyzed using an inductive thematic analysis approach. Results Qualitative analysis yielded six themes that impact suicide risk assessment. Time, privacy, collaboration and consultation with other professionals and integration of a standard screening protocol in routine care exemplified environmental and systemic themes. Patient engagement/participation in assessment and providers’ approach to communicating with patients and other providers also impacted the effectiveness of suicide risk assessment efforts. Conclusions The findings inform feasible suicide risk assessment practices in EDs. Appropriately utilizing a collaborative, multidisciplinary approach to assess suicide-related concerns appears to be a promising approach to ameliorate the burden placed on ED providers and facilitate optimal patient care. Recommendations for clinical care, education, quality improvement and research are offered

A Review of Algorithms for Credit Risk Analysis

The interest collected by the main borrowers is collected to pay back the principal borrowed from the depositary bank. In financial risk management, credit risk assessment is becoming a significant sector. For the credit risk assessment of client data sets, many credit risk analysis methods are used. The assessment of the credit risk datasets leads to the choice to cancel the customer\u27s loan or to dismiss the customer\u27s request is a challenging task involving a profound assessment of the information set or client information. In this paper, we survey diverse automatic credit risk analysis methods used for credit risk assessment. Data mining approach, as the most often used approach for credit risk analysis was described with the focus to various algorithms, such as neural networks. This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.</p

Разработка инструментария оперативной оценки вероятности возникновения рисков в IТ-проектах

As the title implies the article describes tools for assessing the impact and risks in the ITprojects. The purpose of the article is to give the reader some information on the basic procedures for management of risks, about the basic methods of probability and impact of risks. The article gives a detailed analysis of risk assessment methods, such as quantitative and qualitative. The author comes to the conclusion that qualitative methods are more optimal for risk assessment in the proof of this gives examples of a risk assessment based on the survey and mapping of risks

Cyber Supply Chain Risks in Cloud Computing - Bridging the Risk Assessment Gap

Cloud computing represents a significant paradigm shift in the delivery of information technology (IT) services. The rapid growth of the cloud and the increasing security concerns associated with the delivery of cloud services has led many researchers to study cloud risks and risk assessments. Some of these studies highlight the inability of current risk assessments to cope with the dynamic nature of the cloud, a gap we believe is as a result of the lack of consideration for the inherent risk of the supply chain. This paper, therefore, describes the cloud supply chain and investigates the effect of supply chain transparency in conducting a comprehensive risk assessment. We conducted an industry survey to gauge stakeholder awareness of supply chain risks, seeking to find out the risk assessment methods commonly used, factors that hindered a comprehensive evaluation and how the current state-of-the-art can be improved. The analysis of the survey dataset showed the lack of flexibility of the popular qualitative assessment methods in coping with the risks associated with the dynamic supply chain of cloud services, typically made up of an average of eight suppliers. To address these gaps, we propose a Cloud Supply Chain Cyber Risk Assessment (CSCCRA) model, a quantitative risk assessment model which is supported by decision support analysis and supply chain mapping in the identification, analysis and evaluation of cloud risks

Relative seismic and tsunami risk assessment for Stromboli Island (Italy)

An innovative method of estimating the relative risk of buildings exposed to seismic and tsunami hazards in volcanic islands is applied to Stromboli (Italy), a well-known stratovolcano affected by moderate earthquakes and mass-flow-induced tsunamis. The method uses a pre-existing quali-quantitative analysis to assess the relative risk indices of buildings, which provide comparative results useful for prioritisation purposes, in combination with a historical-geographical settlement analysis consistent with the ‘territorialist’ approach to the urban and regional planning and design. The quali-quantitative analysis is based on a new proposed survey-sheet model, useful to collect building information necessary for the relative risk estimation, whereas the historical-geographical investigation is based on the multi-temporal comparison of aerial and satellite images. The proposal to combine two consolidated methods represents an innovation in estimating relative risk. Considering that Stromboli Island had never been subjected to similar analyses, the results of the relative seismic risk assessment are novel and moreover identify buildings with a fairly-low and spatially-uniform relative risk. The results of the relative tsunami risk assessment are consistent with results of similar past studies, identifying buildings with a higher relative risk index on the northern coast of the island. The combined use of a building-by-building survey with a multi-temporal analysis of settlements allows obtaining a higher detail than previously available for the region. If adequately modified, the proposed combination of methods allows assessing relative risk also considering other geo-environmental hazards and their cascading effects, in a multi-hazard risk assessment perspective

Inter-vulnerability of financial institutions and households in the system of national financial security assessment

Purpose: The aim of this article is to study the concept of financial institutions and households' interrelation of vulnerabilities to the risk of money laundering and the integration of this concept into the methodology of a national ML/TF (Money Laundering and Terrorist Financing) risk assessment. Design/Methodology/Approach: At the theoretical and methodological levels, authors utilized a risk-based approach, which involves the separation of the object of study in risk levels and its impact on each risk level. At the methodological and analytical levels, authors utilized methods of grouping, descriptive analysis, comparison, synthesis, and graphic visualization of data. Findings: The most significant scientific results obtained in the course of the study include: proprietary algorithm for calculating the intensity coefficient of threats to national financial security, which practical approval on data of 27 countries allowed determining the structure of threats to financial security in the international landscape in the period 2013-2018; originally developed questionnaire on the assessment of the risks of deviations in the financial behavior of households and individuals. Originality/Value: The key findings are targeted at their widespread application in assessing money laundering risks at the national and international levels, in developing strategic documents on the development of systems to fight money laundering and terrorist financing. The methodology for identifying the propensity to deviations of financial behavior, based on a questionnaire survey, could serve as the basis for developing scoring systems.The research was supported by Russian Foundation for Basic Research # 18-010-00657.peer-reviewe

ANALISIS RISIKO KECELAKAAN KERJA METODE HIRA (HAZARD IDENTIFICATION AND RISK ASSESSMENT) DI PT. X

The HIRA (Hazard Identification, Risk Assessment) method is a process of identifying hazards that occur in all company activities, then conducting a risk assessment of the hazards that occur. Introduction: Based on the initial survey conducted at PT. X, it was found that there were work accidents such as pinched hands, cuts, entanglement in processing machines which caused the risk of accidents. This research was conducted at PT.X in February-August 2021. Methods: This study used a descriptive qualitative method. This study analyzes the risk of work accidents using the HIRA (Hazard Identification, Risk Assessment) method which aims to identify hazards and conduct a risk assessment of these hazards. The research informants were 6 people consisting of 2 key informants and 4 main informants. Results: The results showed that there were 44 types of hazards from 8 work stations at PT. X. Among them, 16% have a small risk of harm (trivial), 38.6% have a tolerable risk, 34.1% have a moderate risk of harm, 4.5% have a substantial risk of harm, 6, 8% have an intolerable risk of harm. Conclusion: Risk analysis is a process by which hazards are identified and risks are estimated to assess the damage caused with the likelihood of damage occurring

Machine learning methods for systemic risk analysis in financial sectors.

Financial systemic risk is an important issue in economics and financial systems. Trying to detect and respond to systemic risk with growing amounts of data produced in financial markets and systems, a lot of researchers have increasingly employed machine learning methods. Machine learning methods study the mechanisms of outbreak and contagion of systemic risk in the financial network and improve the current regulation of the financial market and industry. In this paper, we survey existing researches and methodologies on assessment and measurement of financial systemic risk combined with machine learning technologies, including big data analysis, network analysis and sentiment analysis, etc. In addition, we identify future challenges, and suggest further research topics. The main purpose of this paper is to introduce current researches on financial systemic risk with machine learning methods and to propose directions for future work.This research has been partially supported by grants from the National Natural Science Foundation of China (#U1811462, #71874023, #71771037, #71725001, and #71433001)

From flood science to flood policy: The Foresight Future Flooding Project, seven years on.

Purpose: The Foresight Future Flooding (FFF) project researched flood risk in the UK to the year 2100 for central government, using scenarios and a national risk assessment model backed by qualitative analysis from panels of some 45 senior scientists. The purpose of this paper is to assess the impact of the project, both nationally and internationally. Design/methodology/approach: This paper assesses the impact of the FFF project, both nationally and internationally, using web searches, document analysis, and a questionnaire survey of key actors in the flood risk management policy field. Findings: It was found that the penetration of the project into professionals' consciousness was high in relation to other comparable projects and publications, and its impact on policy - both immediately and continuing - was profound. The FFF initiative did not create policy change, however, but facilitated its legitimation, adding impetus to what was already there, as one element of a part-catalytic and part-incremental process of policy evolution. Research limitations/implications: Special circumstances, internal and external to the project, mean that this cannot be a simple model for matching research to policymakers' needs in the future. Practical implications: Important lessons may be learnt from this project about both the methods of forward-looking foresight-type research, and the way that its results are disseminated to its target audiences. Originality/value: This is an innovative attempt to assess the impact of a new type of foresight project. © Emerald Group Publishing Limited

Affective risk perception in automotive environments

Traversing the automotive environment exposes drivers to a risk of property damage, injury, and death. This risk varies across the road network. This research questions whether drivers are capable of accurately perceiving their own exposure to risk in this environment. Analysis begins with an assessment of risk exposure at roadway intersections (as measured in terms of crash frequency, severity, and mixed-weighting methods). This assessment provides risk indices for a cross-section of road intersections across an urban Iowa community. These indices are then used in the development of an experimental visual cognition survey used to record risk perceptions of roadway sites amongst survey respondents. Survey responses record the way in which drivers’ perception of risk varies within the automotive environment. Despite limitations in the experimental methods, survey results question the ability of drivers to predict their risk exposure, and therefore contributes to our understanding of risk homeostasis theory