726 research outputs found

    Climate Risk Management and Institutional Learning

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    Insurance companies are a prominent mechanism for risk transfers. Many initiatives are looking toward private–public partnerships and new risk-management instruments to provide a cushion for climate change-related effects. For this aspiration to be fulfilled, insurers and institutions within which they operate need to learn about emergent risks and develop workable strategies. We explore three factors shaping the evolution of insurance practices - quantitative models of catastrophic loss, experience of catastrophic loss, and outcomes of litigated cases. We use the available evidence to assess the importance of each of these factors in how the industry is evolving and, hence, what actual risk reductions and transfers are more likely in the future.climate change, insurance, risk management, climate change litigation, insurance modeling and learning

    Blind Minotaur Guided by Birds

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    Designing a Virtual Embedded Scenario-Based Military Simulation Training Program using Educational and Design Instructional Strategies

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    The purpose of this dissertation in practice was to develop and implement a new training program for designers of military intelligence simulation scenarios used to train soldiers. The use of education and design instructional strategies assisted in the ability for designers to gain mastery skills in creating realistic, high-fidelity scenarios that are applied in the training process. The use of simulation scenarios to train adult learners has increased significantly with improvements in technology and its fidelity to engage learners in a realistic way. Despite these advances, the lack of effective design, implementation and analysis of military simulation training programs in the military intelligence community has led to a decrease in simulation utilization, as in the case of the organization examined in this problem of practice. The current training program\u27s increasing difficulties with consistent use by military intelligence simulation scenario designers were discovered in the results of a gap analysis conducted in 2014, prompting this design. This simulation design aimed to examine: (1) a research-based design methodology to match training requirements for the designers, (2) formative assessment of performance and (3) a research-based evaluation framework to determine the effectiveness of the new training program. For the organization\u27s training program, a Simulation-Based Embedded Training (SBET) solution using scenarios was conceived based on research grounded in cognitive theory and instructional design considerations for simulations. As a structured framework for how to design and implement an effective and sustained training program, the educational instructional design model, ADDIE, was used. This model allowed for continual flexibility in each phase to evaluate and implement changes iteratively. The instructional model and its techniques were used with fidelity, specifically for training the designers of the simulation system. Industries will continue to increase the use of simulation as advances in technologies offer more realistic, safe, and complex training environments. A detailed strategy was provided specific to the organization using a research-based instructional approach integrated into program requirements set forth by the government. This proposed solution, supported by research in the application of instructional strategies, is specific to this organization; however, the training program design differs from other high-fidelity military simulator training programs through its use of dispersed training to the simulation scenario designers using realistic scenarios to mimic the tasks that the designers themselves must create. The difference in the solution in this dissertation in practice is: 1) that the simulation scenarios are designed without the help of subject matter experts by using the embedded instructional strategies and 2) the design is to the fidelity of realism required for military intelligence training exercises

    Analyzing the Clinical Outcomes of a Rapid Mass Conversion From Rosuvastatin to Atorvastatin in a VA Medical Center Outpatient Setting

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    Background: Medication conversions occur frequently within the Veterans Health Administration. This manual process involves several pharmacists over an extended period of time. Macros can automate the process of converting a list of patients from one medication to a therapeutic alternative. Objectives: To develop a macro that would convert active rosuvastatin prescriptions to atorvastatin and to create an electronic dashboard to evaluate clinical outcomes. Methods: A conversion protocol was approved by the Pharmacy & Therapeutics Committee. A macro was developed using Microsoft Visual Basic. Outpatients with active prescriptions for rosuvastatin were reviewed and excluded if they had a documented allergy to atorvastatin or a significant drug-drug interaction. An electronic dashboard was created to compare safety and efficacy endpoints pre- and postconversion. Primary endpoints included low-density lipoprotein (LDL), creatine phosphokinase (CPK), aspartate transaminase (AST), alanine transaminase (ALT), and alkaline phosphatase. Secondary endpoints evaluated cardiovascular events, including the incidences of myocardial infarction, stroke, and stent placement. Results: The macro was used to convert 1520 patients from rosuvastatin to atorvastatin over a period of 20 hours saving $5760 in pharmacist labor. There were no significant changes in LDL, AST, ALT, or secondary endpoints (P > .05). There was a significant increase in alkaline phosphatase (P = .0035). Conclusions: A rapid mass medication conversion from rosuvastatin to atorvastatin saved time and money and resulted in no clinically significant changes in safety or efficacy endpoints. Macros and clinical dashboards can be applied to any Veterans Health Administration facility
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