Despite pressure from the private sector to market their own custom solutions, the healthcare industry is coming around to the idea of applying the strategies of collaboration, open solutions, and innovation to meet the ever-changing demands for healthcare information to support quality and safety. This book provides a roadmap for improving quality of care using Electronic Health Records (EHR) and interoperable, consumer-centric health information solutions. Through a series of case studies, the authors highlight collaborative and innovative initiatives that are already being used around the world, such as the acclaimed VistA system from Veterans' Health and a variety of other open source EHR systems.

Despite pressure from the private sector to market their own custom solutions, the healthcare industry is coming around to the idea of applying the strategies of collaboration, open solutions, and innovation to meet the ever-changing demands for healthcare information to support quality and safety. This book provides a roadmap for improving quality of care using Electronic Health Records (EHR) and interoperable, consumer-centric health information solutions. Important Notice: The digital edition of this book is missing some of the images or content found in the physical edition.

"This book is specific to the field of medical informatics and ubiquitous health care and highlights the use of new trends based on the new initiatives of Web 2.0"--Provided by publisher.

The digital age has presented an exponential growth in the amount of data available to individuals looking to draw conclusions based on given or collected information across industries. Challenges associated with the analysis, security, sharing, storage, and visualization of large and complex data sets continue to plague data scientists and analysts alike as traditional data processing applications struggle to adequately manage big data. Big Data: Concepts, Methodologies, Tools, and Applications is a multi-volume compendium of research-based perspectives and solutions within the realm of large-scale and complex data sets. Taking a multidisciplinary approach, this publication presents exhaustive coverage of crucial topics in the field of big data including diverse applications, storage solutions, analysis techniques, and methods for searching and transferring large data sets, in addition to security issues. Emphasizing essential research in the field of data science, this publication is an ideal reference source for data analysts, IT professionals, researchers, and academics.

Interdisciplinary Shared Governance is the foundational reference for interdisciplinary shared governance model design and implementation. This text provides a seminal information base for translating nursing shared governance across disciplinary boundaries in a way that creates systems and practice linkages across the organization. The Second Edition has been updated with new concepts and further research that extends thinking with regard to shared governance, Magnet recognition, and interdisciplinary relationships. This revised edition is essential in supporting the broad-based application of shared governance as a decision-making model for integrating clinical practice.

Comprehensive coverage of all the major health professions. The text outlines more than 75 careers and touches on every major facet of the field from the evolution of medicine to payment for services...add more!

R is quickly becoming the number one choice for users in the fields of biology, medicine, and bioinformatics as their main means of storing, processing, sharing, and analyzing biomedical data. R for Medicine and Biology is a step-by-step guide through the use of the statistical environment R, as used in a biomedical domain. Ideal for healthcare professionals, scientists, informaticists, and statistical experts, this resource will provide even the novice programmer with the tools necessary to process and analyze their data using the R environment. Introductory chapters guide readers in how to obtain, install, and become familiar with R and provide a clear introduction to the programming language using numerous worked examples. Later chapters outline how R can be used, not just for biomedical data analysis, but also as an environment for the processing, storing, reporting, and sharing of data and results. The remainder of the book explores areas of R application to common domains of biomedical informatics, including imaging, statistical analysis, data mining/modeling, pathology informatics, epidemiology, clinical trials, and metadata usage. R for Medicine and Biology will provide you with a single desk reference for the R environment and its many capabilities.

Thoroughly revised and updated, Exploring Bioinformatics: A Project-Based Approach, Second Edition is intended for an introductory course in bioinformatics at the undergraduate level. Through hands-on projects, students are introduced to current biological problems and then explore and develop bioinformatic solutions to these issues. Each chapter presents a key problem, provides basic biological concepts, introduces computational techniques to address the problem, and guides students through the use of existing web-based tools and software solutions. This progression prepares students to tackle the On-Your-Own Project, where they develop their own software solutions. Topics such as antibiotic resistance, genetic disease, and genome sequencing provide context and relevance to capture student interest.