Data-Guided Healthcare Decision Making PDF Download
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Author: Ramalingam Shanmugam
Publisher: Cambridge University Press
ISBN: 100921201X
Category : Medical
Languages : en
Pages : 529
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Book Description
This book effectively exposes and illustrates the ideas and tools for optimal healthcare decisions taken from evidence.
Author: Ramalingam Shanmugam
Publisher: Cambridge University Press
ISBN: 100921201X
Category : Medical
Languages : en
Pages : 529
Get Book Here
Book Description
This book effectively exposes and illustrates the ideas and tools for optimal healthcare decisions taken from evidence.
Author: Wang, John
Publisher: IGI Global
ISBN: 1466652039
Category : Business & Economics
Languages : en
Pages : 2862
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Book Description
As the age of Big Data emerges, it becomes necessary to take the five dimensions of Big Data- volume, variety, velocity, volatility, and veracity- and focus these dimensions towards one critical emphasis - value. The Encyclopedia of Business Analytics and Optimization confronts the challenges of information retrieval in the age of Big Data by exploring recent advances in the areas of knowledge management, data visualization, interdisciplinary communication, and others. Through its critical approach and practical application, this book will be a must-have reference for any professional, leader, analyst, or manager interested in making the most of the knowledge resources at their disposal.
Author: Harold C. Sox
Publisher: John Wiley & Sons
ISBN: 1118341562
Category : Medical
Languages : en
Pages : 330
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Book Description
Medical Decision Making provides clinicians with a powerful framework for helping patients make decisions that increase the likelihood that they will have the outcomes that are most consistent with their preferences. This new edition provides a thorough understanding of the key decision making infrastructure of clinical practice and explains the principles of medical decision making both for individual patients and the wider health care arena. It shows how to make the best clinical decisions based on the available evidence and how to use clinical guidelines and decision support systems in electronic medical records to shape practice guidelines and policies. Medical Decision Making is a valuable resource for all experienced and learning clinicians who wish to fully understand and apply decision modelling, enhance their practice and improve patient outcomes. “There is little doubt that in the future many clinical analyses will be based on the methods described in Medical Decision Making, and the book provides a basis for a critical appraisal of such policies.” - Jerome P. Kassirer M.D., Distinguished Professor, Tufts University School of Medicine, US and Visiting Professor, Stanford Medical School, US
Author: Jaganathan, Ramkumar
Publisher: IGI Global
ISBN:
Category : Business & Economics
Languages : en
Pages : 291
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Book Description
Academic scholars, entrenched in the complexities of various domains, face the daunting task of navigating intricate decision-making scenarios. The prevailing need for efficient and effective decision-making tools becomes increasingly apparent as traditional methodologies struggle to keep pace with the demands of modern research and industry. This pivotal issue necessitates a shift, urging scholars to explore unconventional approaches that can transcend disciplinary boundaries and unlock new dimensions of problem-solving. In response to these pressing challenges, Intelligent Decision Making Through Bio-Inspired Optimization emerges as a beacon of ingenuity. This groundbreaking book transcends usual disciplinary boundaries, seamlessly integrating computer science, artificial intelligence, optimization, and decision science. Its multidisciplinary approach addresses the inherent complexities faced by scholars, offering a comprehensive exploration of nature-inspired algorithms such as genetic algorithms, swarm intelligence, and evolutionary strategies. The book's core mission is to empower academic scholars with the tools to overcome contemporary decision-making hurdles, providing a holistic understanding of these bio-inspired approaches and their potential to revolutionize the scholarly landscape.
Author: Cybellium
Publisher: Cybellium Ltd
ISBN: 1836796951
Category : Business & Economics
Languages : en
Pages : 220
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Book Description
Designed for professionals, students, and enthusiasts alike, our comprehensive books empower you to stay ahead in a rapidly evolving digital world. * Expert Insights: Our books provide deep, actionable insights that bridge the gap between theory and practical application. * Up-to-Date Content: Stay current with the latest advancements, trends, and best practices in IT, Al, Cybersecurity, Business, Economics and Science. Each guide is regularly updated to reflect the newest developments and challenges. * Comprehensive Coverage: Whether you're a beginner or an advanced learner, Cybellium books cover a wide range of topics, from foundational principles to specialized knowledge, tailored to your level of expertise. Become part of a global network of learners and professionals who trust Cybellium to guide their educational journey. www.cybellium.com
Author: Parikshit N. Mahalle
Publisher: Springer Nature
ISBN: 9819963532
Category : Technology & Engineering
Languages : en
Pages : 137
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Book Description
This book discusses the best research roadmaps, strategies, and challenges in data-centric approach of artificial intelligence (AI) in various domains. It presents comparative studies of model-centric and data-centric AI. It also highlights different phases in data-centric approach and data-centric principles. The book presents prominent use cases of data-centric AI. It serves as a reference guide for researchers and practitioners in academia and industry.
Author: Alex Liu
Publisher: IAP
ISBN: 1641138998
Category : Computers
Languages : en
Pages : 184
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Book Description
Healthcare and technology are at a convergence point where significant changes are poised to take place. The vast and complex requirements of medical record keeping, coupled with stringent patient privacy laws, create an incredibly unwieldy maze of health data needs. While the past decade has seen giant leaps in AI, machine learning, wearable technologies, and data mining capacities that have enabled quantities of data to be accumulated, processed, and shared around the globe. Transforming Healthcare with Big Data and AI examines the crossroads of these two fields and looks to the future of leveraging advanced technologies and developing data ecosystems to the healthcare field. This book is the product of the Transforming Healthcare with Data conference, held at the University of Southern California. Many speakers and digital healthcare industry leaders contributed multidisciplinary expertise to chapters in this work. Authors’ backgrounds range from data scientists, healthcare experts, university professors, and digital healthcare entrepreneurs. If you have an understanding of data technologies and are interested in the future of Big Data and A.I. in healthcare, this book will provide a wealth of insights into the new landscape of healthcare.
Author: Patricia L. Thomas, PhD, RN, FAAN, FNAP, FACHE, NEA-BC, ACNS-BC, CNL
Publisher: Springer Publishing Company
ISBN: 0826139442
Category : Medical
Languages : en
Pages : 314
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Book Description
Data-Driven Quality Improvement and Sustainability in Health Care: An Interprofessional Approach provides nurse leaders and healthcare administrators of all disciplines with a solid understanding of data and how to leverage data to improve outcomes, fuel innovation, and achieve sustained results. It sets the stage by examining the current state of the healthcare landscape; new imperatives to meet policy, regulatory, and consumer demands; and the role of data in administrative and clinical decision-making. It helps the professional identify the methods and tools that support thoughtful and thorough data analysis and offers practical application of data-driven processes that determine performance in healthcare operations, value- and performance-based contracts, and risk contracts. Misuse or inconsistent use of data leads to ineffective and errant decision-making. This text highlights common barriers and pitfalls related to data use and provide strategies for how to avoid these pitfalls. In addition, chapters feature key points, reflection questions, and real-life interprofessional case exemplars to help the professional draw distinctions and apply principles to their own practice. Key Features: Provides nurse leaders and other healthcare administrators with an understanding of the role of data in the current healthcare landscape and how to leverage data to drive innovative and sustainable change Offers frameworks, methodology, and tools to support quality improvement measures Demonstrates the application of data and how it shapes quality and safety initiatives through real-life case exemplars Highlights common barriers and pitfalls related to data use and provide strategies for how to avoid these pitfalls
Author: Balasubramanian Thiagarajan
Publisher: Otolaryngology online
ISBN: 935913242X
Category : Computers
Languages : en
Pages : 345
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Book Description
Welcome to the world of data analysis! In today's data-driven era, the ability to effectively analyze and derive insights from data has become a vital skill for individuals and organizations across various domains. This book aims to serve as your comprehensive guide to understanding and performing data analysis, from the fundamental concepts to the practical applications. Chapter 1 introduces you to the fascinating realm of data analysis. We delve into the importance of data analysis in decision-making processes and highlight its role in gaining valuable insights and making informed choices. Understanding the power of data analysis sets the foundation for your journey ahead. Chapter 2 focuses on data entry, a crucial step in the data analysis process. We explore different methods and techniques for entering data accurately, ensuring the reliability and integrity of your dataset. Effective data entry practices are essential for obtaining meaningful results. In Chapter 3, we explore the different types of data analysis. Whether it's exploratory, descriptive, diagnostic, predictive, or prescriptive analysis, you will gain an understanding of each type and when to employ them in various scenarios. This chapter equips you with the knowledge to choose the appropriate analysis technique for your specific needs. To lay the groundwork for your data analysis journey, Chapter 4 familiarizes you with the basic terminology commonly used in the field. From variables and observations to measures of central tendency and variability, this chapter ensures you have a solid grasp of the foundational concepts necessary for effective data analysis. Chapter 5 focuses on setting up your data analysis environment. We guide you through the process of installing the necessary software and configuring your data workspace. Creating an optimal environment is crucial for seamless and efficient data analysis. Data preprocessing takes center stage in Chapter 6. We delve into the essential steps of data cleaning, transformation, and handling missing values. By mastering these techniques, you will be able to prepare your data for analysis, ensuring its quality and usability. In Chapter 7, we explore the exciting world of data exploration and visualization. Understanding the distribution of data and identifying relationships between variables are key aspects of uncovering meaningful insights. We delve into creating various charts and graphs to visually represent data, aiding in its interpretation and analysis. Chapter 8 introduces you to statistical analysis techniques. Descriptive statistics help us summarize and describe data, while inferential statistics enable us to make inferences and draw conclusions about populations based on sample data. Additionally, hypothesis testing allows us to validate our assumptions and test specific predictions. Predictive analytics takes the spotlight in Chapter 9. We explore techniques such as linear and logistic regression, decision trees, and clustering algorithms. These techniques empower you to make predictions and forecasts based on historical data, providing valuable insights for decision-making. Chapter 10 is dedicated to machine learning, an exciting field within data analysis. We introduce the fundamentals of machine learning, including supervised and unsupervised learning algorithms. Understanding these concepts opens doors to more advanced data analysis techniques and applications. Ethics in data analysis takes center stage in Chapter 11. We delve into the critical considerations of privacy concerns, data bias, and fairness in data analysis. Ethical data practices are crucial to ensure the responsible and ethical use of data in analysis. Chapter 12 explores the wide-ranging applications of data analysis. We delve into the domains of business analytics, healthcare analytics, sports analytics, and social media analytics, highlighting how data analysis drives insights and informs decision-making in these fields. Finally, Chapter 13 serves as a conclusion and sets you on the path for further learning and development. We recap the key concepts covered in the book, provide tips for advancing your data analysis skills, and discuss future trends and innovations in the field. We hope this book serves as a valuable resource in your data analysis journey. Whether you are a student, professional, or data enthusiast, we believe that understanding and applying data analysis.
Author: OECD
Publisher: OECD Publishing
ISBN: 9264805907
Category :
Languages : en
Pages : 447
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Book Description
This volume, developed by the Observatory together with OECD, provides an overall conceptual framework for understanding and applying strategies aimed at improving quality of care. Crucially, it summarizes available evidence on different quality strategies and provides recommendations for their implementation. This book is intended to help policy-makers to understand concepts of quality and to support them to evaluate single strategies and combinations of strategies.
