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As the focus of the health care delivery system continues to move toward a coordinated and accountable system, there is an increasing need for a single resource that focuses on analytics for population health. Population Health Analytics addresses that need by providing detailed information and a “how to” guide for achieving population health analytics. Comprehensive, current, and practical, this logically organized text builds from understanding data sources, to contextualizing data, modeling data, and gleaning insights from that data, which is a natural progression for organizations in progressing to higher levels of analytic capabilities. Furthermore, these frameworks for the population health process and analytics are grounded in an evidence base that is also aligned with theories and processes used in healthcare disciplines. This first of its kind text will prepare students to improve health outcomes, understand patterns of health behavior and more.
“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
Make healthcare analytics work: leverage its powerful opportunities for improving outcomes, cost, and efficiency.This book gives you thepractical frameworks, strategies, tactics, and case studies you need to go beyond talk to action. The contributing healthcare analytics innovators survey the field's current state, present start-to-finish guidance for planning and implementation, and help decision-makers prepare for tomorrow's advances. They present in-depth case studies revealing how leading organizations have organized and executed analytic strategies that work, and fully cover the primary applications of analytics in all three sectors of the healthcare ecosystem: Provider, Payer, and Life Sciences. Co-published with the International Institute for Analytics (IIA), this book features the combined expertise of IIA's team of leading health analytics practitioners and researchers. Each chapter is written by a member of the IIA faculty, and bridges the latest research findings with proven best practices. This book will be valuable to professionals and decision-makers throughout the healthcare ecosystem, including provider organization clinicians and managers; life sciences researchers and practitioners; and informaticists, actuaries, and managers at payer organizations. It will also be valuable in diverse analytics, operations, and IT courses in business, engineering, and healthcare certificate programs.
Population Health Informatics addresses the growing opportunity to utilize technology to put into practice evidence-based solutions to improve population health outcomes across diverse settings. The book focuses on how to operationalize population informatics solutions to address important public health challenges impacting individuals, families, communities, and the environment in which they live. The book uniquely uses a practical, step-by-step approach to implement evidence-based, data- driven population informatics solutions.
This User’s Guide is intended to support the design, implementation, analysis, interpretation, and quality evaluation of registries created to increase understanding of patient outcomes. For the purposes of this guide, a patient registry is an organized system that uses observational study methods to collect uniform data (clinical and other) to evaluate specified outcomes for a population defined by a particular disease, condition, or exposure, and that serves one or more predetermined scientific, clinical, or policy purposes. A registry database is a file (or files) derived from the registry. Although registries can serve many purposes, this guide focuses on registries created for one or more of the following purposes: to describe the natural history of disease, to determine clinical effectiveness or cost-effectiveness of health care products and services, to measure or monitor safety and harm, and/or to measure quality of care. Registries are classified according to how their populations are defined. For example, product registries include patients who have been exposed to biopharmaceutical products or medical devices. Health services registries consist of patients who have had a common procedure, clinical encounter, or hospitalization. Disease or condition registries are defined by patients having the same diagnosis, such as cystic fibrosis or heart failure. The User’s Guide was created by researchers affiliated with AHRQ’s Effective Health Care Program, particularly those who participated in AHRQ’s DEcIDE (Developing Evidence to Inform Decisions About Effectiveness) program. Chapters were subject to multiple internal and external independent reviews.
This book provides frameworks, use cases, and examples that illustrate the role of big data and analytics in modern health care, including how public health information can inform health delivery. Written for health care professionals and executives, this book presents the current thinking of academic and industry researchers and leaders from around the world. Using non-technical language, it includes case studies that illustrate the business processes that underlie the use of big data and health analytics to improve health care delivery.
As healthcare moves from volume to value, payment models and delivery systems will need to change their focus from the individual patient to a population orientation. This will move our economic model from that of a "sick system" to a system of care focused on prevention, boosting patient engagement, and reducing medical expenditures. This new focu
Why Nobody Believes the Numbers introduces a unique viewpoint to population health outcomes measurement: Results/ROIs should be presented as they are, not as we wish they would be. This viewpoint contrasts sharply with vendor/promoter/consultant claims along two very important dimensions: (1) Why Nobody Believes presents outcomes/ROIs achievable right here on this very planet... (2) ...calculated using actual data rather than controlled substances. Indeed, nowhere in healthcare is it possible to find such sharply contrasting worldviews, methodologies, and grips on reality. Why Nobody Believes the Numbers includes 12 case studies of vendors, carriers, and consultants who were apparently playing hooky the day their teacher covered fifth-grade math, as told by an author whose argument style can be so persuasive that he was once able to convince a resort to sell him a timeshare. The book's lesson: no need to believe what your vendor tells you -- instead you can estimate your own savings using “ingredients you already have in your kitchen.” Don't be intimidated just because you lack a PhD in biostatistics, or even a Masters, Bachelor's, high-school equivalency diploma or up-to-date inspection sticker. Why Nobody Believes the Numbers explains how to determine if the ROIs are real...and why they usually aren't. You'll learn how to: Figure out whether you are "moving the needle" or just crediting a program with changes that would have happened anyway Judge whether the ROIs your vendors report are plausible or even arithmetically possible Synthesize all these insights into RFPs and contracts that truly hold vendors accountable for results
Reductionism at the dawn of population health / Kristin Heitman -- Wrong answers : when simple interpretations create complex problems / David S. Fink, Katherine M. Keyes -- Complexity : the evolution towards 21st century science / Anton Palma, David W. Lounsbury -- Systems thinking in population health research and policy / Stephen Mooney -- Generation of systems maps: mapping complex systems of population health / Helen de Pinho -- Systems dynamics model / Eric Lofgren -- Agent-based modeling / Brandon Marshall -- Microsimulation / Sanjay Basu -- Social network analysis : the ubiquity of social networks and their importance for population health / Douglas A. Luke, Amar Dhand, Bobbi J. Carothers -- Machine learning / James H. Faghmous -- Systems science and the social determinants of population health / David S. Fink, Katherine M. Keyes, Magdalena Cerdá -- Systems approaches to understanding how the environment influences population health and population health interventions / Melissa Tracy -- Systems of behavior and population health / Mark Orr, Kathryn Ziemer, Daniel Chen -- Systems under your skin / Karina Standahl Olsen, Hege Bøvelstad, Eiliv Lund -- Frontiers in health modeling / Nathaniel Osgood -- Systems science and population health / Abdulrahman M. El-Sayed, Sandro Galea