Описание: If developing countries are to reach their development goals, their leaders must muster a firm understanding of the impact of infectious diseases on their people and take prompt action to fix socioeconomic arising from the problems associated with poor health practices. Similarly, international health organizations touted as helpers must make sound financial judgments and proper use of technical resources to improve the overall health and social wellbeing of the population. Developing countries must drastically reduce their dependence on foreign assistance and public officials as well as health experts, and local and international NGOs must enhance communication and their collaboration. Healthcare Management Strategy, Communication, and Development Challenges and Solutions in Developing Countries describes the ways in which health services, public health administration, and healthcare policies are managed in developing countries, and how intercultural, intergroup, and mass communication practices weaken development efforts in those countries. Drawing experiences from international health organizations such as the United Nations Fund for Population (UNFPA), commissioned in poor countries to assist national governments in improving the wellbeing of their citizens, this volume analyzes the spread of infectious diseases and offers communication strategies for the management of such diseases as malaria, HIV Aids, Polio, and others in Somalia, Madagascar, Nigeria, the Democratic Republic of Congo, and India.
Описание: Features statistical and operational research methods and tools being used to improve the healthcare industry With a focus on cutting–edge approaches to the quickly growing field of healthcare, Healthcare Analytics: From Data to Knowledge to Healthcare Improvement provides an integrated and comprehensive treatment on recent research advancements in data–driven healthcare analytics in an effort to provide more personalized and efficient healthcare services. Emphasizing data and healthcare analytics from an operational management and statistical perspective, the book details how analytical methods and tools can be utilized to enhance care quality and operational efficiency. Organized into two main sections, Part One features biomedical and health informatics and specifically addresses the analytics of genomic and proteomic data; physiological signals from patient monitoring systems; data uncertainty in clinical laboratory tests; predictive modeling; disease modeling for sepsis; and the design of cyber infrastructures for early prediction of epidemic events. Part Two focuses on healthcare delivery systems, including system advances for transforming clinic workflow and patient care; macro analysis of patient flow distribution; intensive care units; primary care; demand and resource allocation; mathematical models for predicting patient readmission and postoperative outcome; physician–patient interactions; insurance claims; and the role of social media in healthcare. Healthcare Analytics: From Data to Knowledge to Healthcare Improvement also features: Contributions from well–known international experts who shed light on new approaches in this growing area Discussions on contemporary methods and techniques to address the handling of rich and large–scale healthcare data as well as the overall optimization of healthcare system operations Numerous real–world examples and case studies that emphasize the vast potential of statistical and operational research tools and techniques to address the big data environment within the healthcare industry Plentiful applications that showcase the various analytical methods and tools that can be applied to successful predictive modeling The book is an ideal reference for academics and practitioners in operations research, management science, applied mathematics, statistics, business, industrial and systems engineering, healthcare systems, and economics. Healthcare Analytics: From Data to Knowledge to Healthcare Improvement is also appropriate for graduate–level courses typically offered within operations research, industrial engineering, business, and public health departments. Hui Yang, PhD, is Associate Professor in the Harold and Inge Marcus Department of Industrial and Manufacturing Engineering at The Pennsylvania State University. His research interests include sensor–based modeling and analysis of complex systems for process monitoring/control; system diagnostics/prognostics; quality improvement; and performance optimization with special focus on nonlinear stochastic dynamics and the resulting chaotic, recurrence, self–organizing behaviors. Eva K. Lee, PhD, is Professor in the H. Milton Stewart School of Industrial and Systems Engineering at the Georgia Institute of Technology, Director of the Center for Operations Research in Medicine and HealthCare, and Distinguished Scholar in Health System, Health Systems Institute at both Emory University School of Medicine and Georgia Institute of Technology. Her research interests include health risk prediction; early disease prediction and diagnosis; optimal treatment strategies and drug delivery; healthcare outcome analysis and treatment prediction; public health and medical preparedness; large–scale healthcare/medical decision analysis and quality improvement; clinical translational science; and business intelligence and organization transformation.
Автор: Bergeron, Bryan P. Название: Developing a data warehouse for the healthcare enterprise ISBN: 1138502952 ISBN-13(EAN): 9781138502956 Издательство: Taylor&Francis Рейтинг: Цена: 9033.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This third edition to the award-winning book is a straightforward view of a clinical data warehouse development project, from inception through implementation and follow-up. Through first-hand experiences from individuals charged with such an implementation, this book offers guidance and multiple perspectives on the data warehouse development process – from the initial vision to system-wide release. The book provides valuable lessons learned during a data warehouse implementation at King Faisal Specialist Hospital and Research Center (KFSH&RC) in Riyadh, Saudi Arabia – a large, modern, tertiary-care hospital with an IT environment that parallels a typical U.S. hospital. This book also examines the value of the data warehouse from the perspectives of a large healthcare system in the U.S. and a corporate health services business unit. Special features of the book include a sample RFP, data warehouse project plan, and information analysis template. A helpful glossary and acronyms list are included.
Автор: Sandra L. Furterer Название: Lean Six Sigma Case Studies in the Healthcare Enterprise ISBN: 1447170385 ISBN-13(EAN): 9781447170389 Издательство: Springer Рейтинг: Цена: 14365.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book shows in detail how to apply Lean Six Sigma in the health care industry, emphasizing process improvement and operations management in hospitals. Offers case studies on emergency room throughput, linen process improvement, sepsis protocols and more.
Автор: Sandra L. Furterer Название: Lean Six Sigma Case Studies in the Healthcare Enterprise ISBN: 1447155823 ISBN-13(EAN): 9781447155829 Издательство: Springer Рейтинг: Цена: 18284.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book shows in detail how to apply Lean Six Sigma in the health care industry, emphasizing process improvement and operations management in hospitals. Offers case studies on emergency room throughput, linen process improvement, sepsis protocols and more.
Автор: Reddy Chandan K. Название: Healthcare Data Analytics ISBN: 1482232111 ISBN-13(EAN): 9781482232110 Издательство: Taylor&Francis Рейтинг: Цена: 19140.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
At the intersection of computer science and healthcare, data analytics has emerged as a promising tool for solving problems across many healthcare-related disciplines. Supplying a comprehensive overview of recent healthcare analytics research, Healthcare Data Analytics provides a clear understanding of the analytical techniques currently available to solve healthcare problems.
The book details novel techniques for acquiring, handling, retrieving, and making best use of healthcare data. It analyzes recent developments in healthcare computing and discusses emerging technologies that can help improve the health and well-being of patients. Written by prominent researchers and experts working in the healthcare domain, the book sheds light on many of the computational challenges in the field of medical informatics. Each chapter in the book is structured as a "survey-style" article discussing the prominent research issues and the advances made on that research topic. The book is divided into three major categories:
Healthcare Data Sources and Basic Analytics - details the various healthcare data sources and analytical techniques used in the processing and analysis of such data
Advanced Data Analytics for Healthcare - covers advanced analytical methods, including clinical prediction models, temporal pattern mining methods, and visual analytics
Applications and Practical Systems for Healthcare - covers the applications of data analytics to pervasive healthcare, fraud detection, and drug discovery along with systems for medical imaging and decision support
Computer scientists are usually not trained in domain-specific medical concepts, whereas medical practitioners and researchers have limited exposure to the data analytics area. The contents of this book will help to bring together these diverse communities by carefully and comprehensively discussing the most relevant contributions from each domain.
Описание: Data science has always been an effective way of extracting knowledge and insights from information in various forms. One industry that can utilize the benefits from the advances in data science is the healthcare field. The Handbook of Research on Data Science for Effective Healthcare Practice and Administration is a critical reference source that overviews the state of data analysis as it relates to current practices in the health sciences field. Covering innovative topics such as linear programming, simulation modeling, network theory, and predictive analytics, this publication is recommended for all healthcare professionals, graduate students, engineers, and researchers that are seeking to expand their knowledge of efficient techniques for information analysis in the healthcare professions.
Автор: Trinckes, Jr. Название: How Healthcare Data Privacy Is Almo ISBN: 1498783953 ISBN-13(EAN): 9781498783958 Издательство: Taylor&Francis Рейтинг: Цена: 9492.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
The healthcare industry is under privacy attack. The book discusses the issues from the healthcare organization and individual perspectives. Someone hacking into a medical device and changing it is life-threatening. Personal information is available on the black market. And there are increased medical costs, erroneous medical record data that could lead to wrong diagnoses, insurance companies or the government data-mining healthcare information to formulate a medical 'FICO' score that could lead to increased insurance costs or restrictions of insurance. Experts discuss these issues and provide solutions and recommendations so that we can change course before a Healthcare Armageddon occurs.
Описание: Internet of Things Driven Connected Healthcare.-Internet of Things in HealthcareEnergy Efficient Network Design for IoT Healthcare Applications.-Exploring Formal Strategy Framework for the Security in IoT in e-health using Computational Intelligence.-Vitality of Robotics in Healthcare Industry: An Internet of Things (IoT) Perspective.-Internet of Things Meets Mobile Health Systems in Smart Spaces: An Overview.-Information and Communication Emerging Technology: Making Sense of Healthcare Innovation.-Health Informatics as a Service (HIaaS) for Developing Countries.- Analysis of Power Aware Protocols and Standards for Critical E-Health Applications.-Social Networking and Analytics.-A decision support system in brain tumor detection and localization in nominated areas in MR images.-Detecting Unusual Human Activities Using GPU-enabled Neural Network and Kinect Sensors.
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