Required reading in many medical and healthcare institutions, How to Read a Paper is a clear and wide-ranging introduction to evidence-based medicine and healthcare, helping readers to understand its central principles, critically evaluate published data, and implement the results in practical settings. Author Trisha Greenhalgh guides readers through each fundamental step of inquiry, from searching the literature to assessing methodological quality and appraising statistics.
How to Read a Paper addresses the common criticisms of evidence-based healthcare, dispelling many of its myths and misconceptions, while providing a pragmatic framework for testing the validity of healthcare literature. Now in its sixth edition, this informative text includes new and expanded discussions of study bias, political interference in published reports, medical statistics, big data and more.
Offers user-friendly guidance on evidence-based healthcare that is applicable to both experienced and novice readers
Authored by an internationally recognised practitioner and researcher in evidence-based healthcare and primary care
Includes updated references, additional figures, improved checklists and more
How to Read a Paper is an ideal resource for healthcare students, practitioners and anyone seeking an accessible introduction to evidence-based healthcare.
Автор: Tinglong Dai; Sridhar Tayur Название: Handbook of Healthcare Analytics ISBN: 1119300940 ISBN-13(EAN): 9781119300946 Издательство: Wiley Рейтинг: Цена: 17733.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
How can analytics scholars and healthcare professionals access the most exciting and important healthcare topics and tools for the 21st century?
Editors Tinglong Dai (Johns Hopkins) and Sridhar Tayur (Carnegie Mellon), aided by a team of internationally acclaimed experts, have curated this timely volume to help newcomers and seasoned researchers alike to rapidly comprehend a diverse set of thrusts and tools in this rapidly growing cross-disciplinary field. The Handbook covers macro-, meso- and micro-level thrusts, spanning organizational structure, market design, access to (and quality of) care, competing interests, personalized medicine, global health, organ transplantation, healthcare supply chains, ambulatory care, inpatient care, residential care and concierge medicine. No other book in the field matches its scope. It is also the first book to synthesize what has been a highly fragmented research area--an uncoordinated accumulation of papers--and to structure it into a coherent scientific discipline. As Poincare remarked, an accumulation of facts is no more a science than a heap of stones is a house.
The handbook also provides an easy-to-comprehend introduction to five essential research tools--Markov decision process, game theory and information economics, queueing theory (with and without game theory), econometric methods, and data sciences (including machine learning)--by illustrating their uses and applicability on examples from diverse healthcare settings, thus connecting tools with thrusts.
The primary audience of the Handbook includes analytics scholars interested in healthcare and healthcare practitioners interested in analytics. This Handbook:
Instills analytics scholars with a way of thinking that incorporates behavioral, incentive, and policy considerations in various healthcare settings. This change in perspective--a shift in gaze away from narrow, local and one-off operational improvement efforts that do not replicate, scale or remain sustainable--can lead to new knowledge and innovative solutions that healthcare has been seeking so desperately.
Facilitates collaboration between healthcare experts and analytics scholars--to frame and tackle their pressing concerns through appropriate modern mathematical tools designed for this very purpose--ranging from queuing models imbedded with game theory ("queuing games") to game theory methods enhanced by operational considerations ("market design"), from tailored econometric methods to current day data-science methods that include algorithms from machine learning.
While the handbook is designed to be accessible to the independent reader, it may be used in a variety of settings, from a short lecture series on specific topics to a semester-long course covering the entire field.
Автор: Swan, Jacky; Newell, Sue; Nicolini, Davide Название: Mobilizing Knowledge in Healthcare ISBN: 0198738234 ISBN-13(EAN): 9780198738237 Издательство: Oxford Academ Рейтинг: Цена: 14890.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The divide between research and practice is one of the biggest challenges to healthcare improvement globally. This book aims to build a research-led, empirically-grounded, state of the art review of how knowledge is mobilized in healthcare settings and the critical challenges involved.
Автор: Sukhmeet Panesar,Andrew Carson-Stevens,Sarah Salvi Название: Patient Safety and Healthcare Improvement at a Glance ISBN: 1118361369 ISBN-13(EAN): 9781118361368 Издательство: Wiley Рейтинг: Цена: 5061.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Patient Safety and Healthcare Improvement at a Glance is a timely and thorough overview of healthcare quality written specifically for students and junior doctors and healthcare professionals. It bridges the gap between the practical and the theoretical to ensure the safety and wellbeing of patients.
Автор: Baesens Bart Название: Analytics in a big data world ISBN: 1118892704 ISBN-13(EAN): 9781118892701 Издательство: Wiley Рейтинг: Цена: 6178.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The guide to targeting and leveraging business opportunities using big data & analytics By leveraging big data & analytics, businesses create the potential to better understand, manage, and strategically exploiting the complex dynamics of customer behavior.
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: Dey, Nilanjan Название: Big Data Analytics for Intelligent Healthcare Management ISBN: 012818146X ISBN-13(EAN): 9780128181461 Издательство: Elsevier Science Рейтинг: Цена: 19875.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
Big Data Analytics for Intelligent Healthcare Management covers both the theory and application of hardware platforms and architectures, the development of software methods, techniques and tools, applications and governance, and adoption strategies for the use of big data in healthcare and clinical research. The book provides the latest research findings on the use of big data analytics with statistical and machine learning techniques that analyze huge amounts of real-time healthcare data.
Examines the methodology and requirements for development of big data architecture, big data modeling, big data as a service, big data analytics, and more
Discusses big data applications for intelligent healthcare management, such as revenue management and pricing, predictive analytics/forecasting, big data integration for medical data, algorithms and techniques, etc.
Covers the development of big data tools, such as data, web and text mining, data mining, optimization, machine learning, cloud in big data with Hadoop, big data in IoT, and more
Автор: Ashish Gupta; Vimla L. Patel; Robert A. Greenes Название: Advances in Healthcare Informatics and Analytics ISBN: 3319232932 ISBN-13(EAN): 9783319232935 Издательство: Springer Рейтинг: Цена: 13974.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This important new volume presents recent research in healthcare information technology and analytics. and failure in a dynamic decision environment, particularly in treating patients with a chronic disease.Other chapters look at such topics as the impact of information technology integration in integrated delivery systems;
Автор: Anand J. Kulkarni; Patrick Siarry; Pramod Kumar Si Название: Big Data Analytics in Healthcare ISBN: 3030316718 ISBN-13(EAN): 9783030316716 Издательство: Springer Рейтинг: Цена: 22359.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book includes state-of-the-art discussions on various issues and aspects of the implementation, testing, validation, and application of big data in the context of healthcare.
Hopes are high that stem cell (SC) research will lead to treatments and cures for some of the most serious diseases affecting humankind today. SC science has been used in a treatment setting in the replacement of patients' windpipes and in restoring sight to patients who were blind in one eye and in future it is hoped that when the body is injured it will be able to be stimulated to produce those types of SCs necessary to repair the particular damage caused. In the meantime, research into specific treatments for a wide range of serious conditions is being undertaken including Alzheimer's disease, cancer, and diabetes.
The book considers the regulatory governance of stem cell research, setting out a readily understandable account of the science and the challenges it poses for regulators as the research is increasingly being clinically applied. It provides a critical account of those elements of a regulatory system which will be required for any jurisdiction aiming to facilitate innovative and productive SC research while maintaining appropriate ethical and legal controls. The book addresses the specific failings in the current regulatory approach to SC research in the UK and goes on to look at the regulatory approaches in the US.
The book systematically analyses the roles and responsibilities of the three key participants who collaborate in this process: regulators, scientists and tissue providers, arguing that a regulatory system which fails to recognise and facilitate the vital role which each of these three groups plays runs the risk of impairing the chances of the hopes for SC research being realised. The book places a particular emphasis on ensuring that those who contribute their bodily tissues to this endeavour are treated fairly, involving a recognition that their tissues are their property.
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