This series of books focuses on highly specialized Emergency Management arrangements for healthcare facilities and organizations. It is designed to assist any healthcare executive with a body of knowledge which permits a transition into the application of emergency management planning and procedures for healthcare facilities and organizations.This series is intended for both experienced practitioners of both healthcare management and emergency management, and also for students of these two disciplines.

Insurance Planning Models: Price Competition and Regulation of Financial Stability is an exciting new book that takes readers inside the secrets of internal organization of the modern general insurance business. Many people know that it is subject to intensive state regulation, whereby the purpose is to maintain long-term efficiency, honesty, security and stability in the interest and for the protection of policyholders. However, except for knowing that the insurance system is regulated by intensive calculations, that the insurance companies have different positions on the market, that they pursue different goals and even compete with each other, and that one of the tools of this competition is the policy price, not so many people know how to achieve these deserving goals.In developing quantitative recommendations and directives to competing insurers, regulators rely on certain models. In the 1900s, such models were proposed. They were useful for an insight into the probabilistic nature of the insurance process, but not for direct application to practically meaningful problems of insurance regulation. This book is your guide to the rigorously constructed long-term dynamic models with the aim to improve regulatory methods and develop quantitative recommendations using both analytical calculations and computer simulation. It is addressed to a wide range of readers, including interested policyholders, economists whose interest lies in insurance management and regulation, and mathematicians wishing to expand the scope of application for their knowledge.This book is devoted to certain issues that are either not sufficiently presented, or even absent in the literature. It is an attempt to penetrate from the standpoint of mathematical modeling into the goals which face insurance regulators and contending company managers for preventing insolvencies, or even crises pertinent to badly regulated complex reflexive systems.It offers rigorous probabilistic models of long-term insurance business based on the laws of mass phenomena. They mitigate deficiencies of oversimplified risk models. The book presents advances in probabilistic techniques designed to seek quantitative, rather than qualitative, directives and recommendations regarding safe control aiming to achieve different business goals.

Businesses exist to provide goods and services to customers, and in doing so, they take risks. Among these risks is the chance of losing money in lawsuits filed by customers, employees, and others negatively impacted by the business. Insurance provides some protection against these liabilities, but lawsuits still take their toll. This book covers the subject of economic damages and its role in insurance claims, lawsuits, and injunctions against businesses. This book will help the reader to identify economic damages as a component of business liability, describe the business risk posed by economic damages, explain some key determinants of economic damages, and estimate economic damages and business loss in a variety of cases.

When people need healthcare, few worry about being harmed by someone from the medical team making a mistake. Unfortunately, mistakes do happen, and many of the adverse events are not only serious but also preventable. Many countries struggle with top-heavy systems, in which decisions are made about how care is provided by those who are far from experienced in caring for patients. This must change. Professionals at the sharp end need support, structure, and help organizing necessary information to create a safe culture, a learning environment, and safe patient care-all at lower costs. This handbook provides tools for designing a structure for a management system, as well as the tools for documenting processes within it. The starting point is based on current safety research. The book is designed for medical professionals, managers, project members, politicians, public officials, and executives-all who work with patient safety matters. The content shows a new way to healthcare management, presenting an alternative approach together with concrete advice on how healthcare executives and practitioners can begin to think and act differently in order to provide safe healthcare.

Artificial Intelligence Design and Solutions for Risk and Security targets readers to understand, learn, define problems, and architect AI projects. Starting from current business architectures and business processes to futuristic architectures. Introduction to data analytics and life cycle includes data discovery, data preparation, data processing steps, model building, and operationalization are explained in detail. The authors examine the AI and ML algorithms in detail, which enables the readers to choose appropriate algorithms during designing solutions. Functional domains and industrial domains are also explained in detail. The takeaways are learning and applying designs and solutions to AI projects with risk and security implementation and knowledge about futuristic AI in five to ten years.

Artificial Intelligence for Security explores terminologies of security and how AI can be applied to automate security processes. Additionally, the text provides detailed explanations and recommendations for how implement procedures. Practical examples and real-time use cases are evaluated and suggest appropriate algorithms based on the author's experiences. Threat and associated securities from the data, process, people, things (e.g., Internet of things), systems, and actions were used to develop security knowledge base, which will help readers to build their own knowledge base. This book will help the readers to start their AI journey on security and how data can be applied to drive business actions to build secure environment.

Artificial Intelligence for Risk Management is about using AI to manage risk in the corporate environment. The content of this work focuses on concepts, principles, and practical applications that are relevant to the corporate and technology environments. The authors introduce AI and discuss the different types, capabilities, and purposes-including challenges. With AI also comes risk. This book defines risk, provides examples, and includes information on the risk-management process. Having a solid knowledge base for an AI project is key and this book will help readers define the knowledge base needed for an AI project by developing and identifying objectives of the risk-knowledge base and knowledge acquisition for risk. This book will help you become a contributor on an AI team and learn how to tell a compelling story with AI to drive business action on risk.

Artificial intelligence, machine learning, natural language processing, robotics, big data and other new technologies are ready to revolutionize the way we look at healthcare. But if we want them to achieve their full potential, we'll need leaders who understand these new tools and who have long-term strategies in place to take advantage of them. This book will help you to become one of those leaders. Predictive Medicine makes artificial intelligence more accessible for healthcare practitioners without shying away from complex topics and controversial subject matter. It's a call-to-action for a new generation of health leaders and a roadmap to help them usher in a brighter future.