Drawing on the work of the Roundtable on Evidence-Based Medicine, the 2007 IOM Annual Meeting assessed some of the rapidly occurring changes in health care related to new diagnostic and treatment tools, emerging genetic insights, the developments in information technology, and healthcare costs, and discussed the need for a stronger focus on evidence to ensure that the promise of scientific discovery and technological innovation is efficiently captured to provide the right care for the right patient at the right time. As new discoveries continue to expand the universe of medical interventions, treatments, and methods of care, the need for a more systematic approach to evidence development and application becomes increasingly critical. Without better information about the effectiveness of different treatment options, the resulting uncertainty can lead to the delivery of services that may be unnecessary, unproven, or even harmful. Improving the evidence-base for medicine holds great potential to increase the quality and efficiency of medical care. The Annual Meeting, held on October 8, 2007, brought together many of the nation's leading authorities on various aspects of the issues - both challenges and opportunities - to present their perspectives and engage in discussion with the IOM membership.

This unique text is a practical guide to managing and developing Healthcare Knowledge Management (KM) that is underpinned by theory and research. It provides readers with an understanding of approaches to the critical nature and use of knowledge by investigating healthcare-based KM systems. Designed to demystify the KM process and demonstrate its applicability, this text offers contemporary and clinically-relevant lessons for future organizational implementations.

Healthcare Data Analytics and Management help readers disseminate cutting-edge research that delivers insights into the analytic tools, opportunities, novel strategies, techniques and challenges for handling big data, data analytics and management in healthcare. As the rapidly expanding and heterogeneous nature of healthcare data poses challenges for big data analytics, this book targets researchers and bioengineers from areas of machine learning, data mining, data management, and healthcare providers, along with clinical researchers and physicians who are interested in the management and analysis of healthcare data. - Covers data analysis, management and security concepts and tools in the healthcare domain - Highlights electronic medical health records and patient information records - Discusses the different techniques to integrate Big data and Internet-of-Things in healthcare, including machine learning and data mining - Includes multidisciplinary contributions in relation to healthcare applications and challenges

“This is an outstanding book and I would highly recommend it for any professional or faculty in a current public health role, and absolutely for a student in the fields of public health, nursing, health administration, health education, medicine, and information technology (artificial intelligence)... This book provides the resources for professionals to learn and apply theory, analytics, quality, and services to understand populations with the ultimate goal of transforming U.S. health care." ---Doody's Review Service, 5 stars Population Health Management: Strategies, Tools, Applications, and Outcomes uniquely combines perspectives and concepts from community, public, and global health and aligns them with the essentials of health management. Written by leading experts in academia and industry, this text emphasizes the integration of management skills necessary to deliver quality care while producing successful outcomes sensitive to the needs of diverse populations. Designed to be both student-friendly and comprehensive, this text utilizes various models, frameworks, case examples, chapter podcasts, and more to illustrate foundational knowledge and impart the skills necessary for health care managers to succeed throughout the health care sector. The book spans core topics such as community needs assessments, social determinants of health, the role of data analytics, managerial epidemiology, value-based care payment models, and new population health delivery models. COVID-19 examples throughout chapters illustrate population health management strategies solving real-world challenges. Practical and outcomes-driven, Population Health Management prepares students in health administration and management, public health, social work, allied health, and other health professions for the challenges of an evolving health care ecosystem and the changing roles in the health management workforce. Key Features: Highlights up-to-date topics focusing on social marketing, design thinking for innovation, adopting virtual care and telehealth strategies, and social marketing ideas Introduces new population health management skills and tools such as the Social Vulnerability Index, Policy Map, PRAPARE, the PHM Framework, Design Thinking and Digital Messaging Incorporates "Did You Know?" callouts, chapter-based podcasts, and discussion questions to help explain real-world situations and examples that students and health professionals may encounter as administrators and managers Includes four full-length case studies focusing on the co-production of health, implementing a population health data analytics platform, health equity, and collaborative leadership Connects chapter objectives with the National Center for Healthcare Leadership (NCHL) and the Public Health Foundation (PHF) competencies Purchase includes digital access for use on most mobile devices or computers, as well as full suite of instructor resources with Instructor's Manual, PowerPoint slides, test bank, and sample syllabus

The Institute of Medicine study Crossing the Quality Chasm (2001) recommended that an interdisciplinary summit be held to further reform of health professions education in order to enhance quality and patient safety. Health Professions Education: A Bridge to Quality is the follow up to that summit, held in June 2002, where 150 participants across disciplines and occupations developed ideas about how to integrate a core set of competencies into health professions education. These core competencies include patient-centered care, interdisciplinary teams, evidence-based practice, quality improvement, and informatics. This book recommends a mix of approaches to health education improvement, including those related to oversight processes, the training environment, research, public reporting, and leadership. Educators, administrators, and health professionals can use this book to help achieve an approach to education that better prepares clinicians to meet both the needs of patients and the requirements of a changing health care system.

The production of healthcare services had been out of the business, organizational, and technological dynamic that continually revolutionized the production of all other goods and services for a long time. Nowadays, this marginality has ceased as the need for healthcare is rising. Healthcare is now at the center of attention influenced by the never-ending demand of medical technology and substantial resource scarcity that imposes substantial organizational and entrepreneurial innovations. One decisive challenge that has emerged from such a situation is the management of healthcare processes, in the broad sense: healthcare professionals are called upon to demonstrate their ability to cope with complex problems because they are characterized in an institutional, ethical, organizational, and economic sense. With its eight chapters in a single segment, this book makes it possible to realize the specific nature of the problem. Its multidimensionality and the original approach are contributed and harmonized by scholars belonging to different disciplines.

Artificial Intelligence (AI) in Healthcare is more than a comprehensive introduction to artificial intelligence as a tool in the generation and analysis of healthcare data. The book is split into two sections where the first section describes the current healthcare challenges and the rise of AI in this arena. The ten following chapters are written by specialists in each area, covering the whole healthcare ecosystem. First, the AI applications in drug design and drug development are presented followed by its applications in the field of cancer diagnostics, treatment and medical imaging. Subsequently, the application of AI in medical devices and surgery are covered as well as remote patient monitoring. Finally, the book dives into the topics of security, privacy, information sharing, health insurances and legal aspects of AI in healthcare. - Highlights different data techniques in healthcare data analysis, including machine learning and data mining - Illustrates different applications and challenges across the design, implementation and management of intelligent systems and healthcare data networks - Includes applications and case studies across all areas of AI in healthcare data

As developed economies enter a period of slower growth, emerging economies such as India have become prime examples of how more can be achieved with less. Bringing together experience and expertise from across the healthcare industry, this book examines innovations that can bring about real advances in the healthcare industry. Innovations in H

While hospitals can learn from other industries, they cannot be improved or run like factories. With work that is more individualized than standardized, and limited control over volume and arrivals, even the leanest-minded hospital must recognize that healthcare systems are more dynamic than nearly any work environment.Written with the creativity n

Strategic management of HR in health care is important in delivering high-quality patient care. This volume of Advances in Health Care Management which focuses on Human Resource Management aims to explore the strategic role that HRM can play in delivering high quality and affordable health care.