Download or read book Data Management and Analytics for Medicine and Healthcare written by Edmon Begoli and published by Springer. This book was released on 2017-08-26 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the thoroughly refereed conference proceedings of the Third International Workshop on Data Management and Analytics for Medicine and Healthcare, DMAH 2017, in Munich, Germany, in September 2017, held in conjunction with the 43rd International Conference on Very Large Data Bases, VLDB 2017. The 9 revised full papers presented together with 2 keynote abstracts were carefully reviewed and selected from 16 initial submissions. The papers are organized in topical sections on data privacy and trustability for electronic health records; biomedical data management and Integration; online mining of Health related data; and clinical data analytics.
Download or read book Statistics Data Analytics for Health Data Management written by Nadinia A. Davis and published by Elsevier Health Sciences. This book was released on 2015-12-04 with total page 266 pages. Available in PDF, EPUB and Kindle. Book excerpt: Introducing Statistics & Data Analytics for Health Data Management by Nadinia Davis and Betsy Shiland, an engaging new text that emphasizes the easy-to-learn, practical use of statistics and manipulation of data in the health care setting. With its unique hands-on approach and friendly writing style, this vivid text uses real-world examples to show you how to identify the problem, find the right data, generate the statistics, and present the information to other users. Brief Case scenarios ask you to apply information to situations Health Information Management professionals encounter every day, and review questions are tied to learning objectives and Bloom’s taxonomy to reinforce core content. From planning budgets to explaining accounting methodologies, Statistics & Data Analytics addresses the key HIM Associate Degree-Entry Level competencies required by CAHIIM and covered in the RHIT exam. Meets key HIM Associate Degree-Entry Level competencies, as required by CAHIIM and covered on the RHIT registry exam, so you get the most accurate and timely content, plus in-depth knowledge of statistics as used on the job. Friendly, engaging writing style offers a student-centered approach to the often daunting subject of statistics. Four-color design with ample visuals makes this the only textbook of its kind to approach bland statistical concepts and unfamiliar health care settings with vivid illustrations and photos. Math review chapter brings you up-to-speed on the math skills you need to complete the text. Brief Case scenarios strengthen the text’s hands-on, practical approach by taking the information presented and asking you to apply it to situations HIM professionals encounter every day. Takeaway boxes highlight key points and important concepts. Math Review boxes remind you of basic arithmetic, often while providing additional practice. Stat Tip boxes explain trickier calculations, often with Excel formulas, and warn of pitfalls in tabulation. Review questions are tied to learning objectives and Bloom’s taxonomy to reinforce core content and let you check your understanding of all aspects of a topic. Integrated exercises give you time to pause, reflect, and retain what you have learned. Answers to integrated exercises, Brief Case scenarios, and review questions in the back of the book offer an opportunity for self-study. Appendix of commonly used formulas provides easy reference to every formula used in the textbook. A comprehensive glossary gives you one central location to look up the meaning of new terminology. Instructor resources include TEACH lesson plans, PowerPoint slides, classroom handouts, and a 500-question Test Bank in ExamView that help prepare instructors for classroom lectures.
Download or read book Big Data and Health Analytics written by Katherine Marconi and published by CRC Press. This book was released on 2014-12-20 with total page 374 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Data Analytics in Medicine Concepts Methodologies Tools and Applications written by Management Association, Information Resources and published by IGI Global. This book was released on 2019-12-06 with total page 2071 pages. Available in PDF, EPUB and Kindle. Book excerpt: Advancements in data science have created opportunities to sort, manage, and analyze large amounts of data more effectively and efficiently. Applying these new technologies to the healthcare industry, which has vast quantities of patient and medical data and is increasingly becoming more data-reliant, is crucial for refining medical practices and patient care. Data Analytics in Medicine: Concepts, Methodologies, Tools, and Applications is a vital reference source that examines practical applications of healthcare analytics for improved patient care, resource allocation, and medical performance, as well as for diagnosing, predicting, and identifying at-risk populations. Highlighting a range of topics such as data security and privacy, health informatics, and predictive analytics, this multi-volume book is ideally designed for doctors, hospital administrators, nurses, medical professionals, IT specialists, computer engineers, information technologists, biomedical engineers, data-processing specialists, healthcare practitioners, academicians, and researchers interested in current research on the connections between data analytics in the field of medicine.
Download or read book Healthcare Data Analytics and Management written by Nilanjan Dey and published by Academic Press. This book was released on 2018-11-15 with total page 340 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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
Download or read book Healthcare Analytics written by Hui Yang and published by John Wiley & Sons. This book was released on 2016-10-10 with total page 632 pages. Available in PDF, EPUB and Kindle. Book excerpt: Features of 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 smarter 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 healthcare quality and operational efficiency. Organized into two main sections, Part I 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 II 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 analytical methods and tools tailored for successful healthcare systems modeling and improvement 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.
Download or read book Clinical Analytics and Data Management for the DNP Second Edition written by Martha L. Sylvia, PhD, MBA, RN and published by Springer Publishing Company. This book was released on 2018-03-28 with total page 396 pages. Available in PDF, EPUB and Kindle. Book excerpt: Praise for the First Edition: “DNP students may struggle with data management, since their projects are not research, but quality improvement, and this book covers the subject well. I recommend it for DNP students for use during their capstone projects." Score: 98, 5 Stars --Doody's Medical Reviews This is the only text to deliver the strong data management knowledge and skills that are required competencies for all DNP students. It enables readers to design data tracking and clinical analytics in order to rigorously evaluate clinical innovations/programs for improving clinical outcomes, and to document and analyze change. The second edition is greatly expanded and updated to address major changes in our health care environment. Incorporating faculty and student input, it now includes modalities such as SPSS, Excel, and Tableau to address diverse data management tasks. Eleven new chapters cover the use of big data analytics, ongoing progress towards value-based payment, the ACA and its future, shifting of risk and accountability to hospitals and clinicians, advancement of nursing quality indicators, and new requirements for Magnet certification. The text takes the DNP student step by step through the complete process of data management from planning to presentation, and encompasses the scope of skills required for students to apply relevant analytics to systematically and confidently tackle the clinical interventions data obtained as part of the DNP student project. Of particular value is a progressive case study illustrating multiple techniques and methods throughout the chapters. Sample data sets and exercises, along with objectives, references, and examples in each chapter, reinforce information. Key Features: Provides extensive content for rigorously evaluating DNP innovations/projects Takes DNP students through the complete process of data management from planning through presentation Includes a progressive case study illustrating multiple techniques and methods Offers very specific examples of application and utility of techniques Delivers sample data sets, exercises, PowerPoint slides and more, compiled in Supplemental Materials and an Instructor Manual
Download or read book Data Management and Analytics for Medicine and Healthcare written by Edmon Begoli and published by Springer. This book was released on 2017-08-25 with total page 162 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the thoroughly refereed conference proceedings of the Third International Workshop on Data Management and Analytics for Medicine and Healthcare, DMAH 2017, in Munich, Germany, in September 2017, held in conjunction with the 43rd International Conference on Very Large Data Bases, VLDB 2017. The 9 revised full papers presented together with 2 keynote abstracts were carefully reviewed and selected from 16 initial submissions. The papers are organized in topical sections on data privacy and trustability for electronic health records; biomedical data management and Integration; online mining of Health related data; and clinical data analytics.
Download or read book Healthcare and Big Data Management written by Bairong Shen and published by Springer. This book was released on 2017-10-20 with total page 164 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book addresses the interplay of healthcare and big data management. Thanks to major advances in big data technologies and precision medicine, healthcare is now becoming the new frontier for both scientific research and economic development. This volume covers a range of aspects, including: big data management for healthcare; physiological and gut microbiota – data collection and analysis; big data standardization and ontology; and personal data privacy and systems level modeling in the healthcare context. The book offers a valuable resource for biomedical informaticians, clinicians, health practitioners and researchers alike.
Download or read book Data Management and Analytics for Medicine and Healthcare written by Fusheng Wang and published by Springer. This book was released on 2017-04-20 with total page 164 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the thoroughly refereed post-conference proceedings of the Second International Workshop on Data Management and Analytics for Medicine and Healthcare, DMAH 2016, in New Delhi, India, in September 2016, held in conjunction with the 42nd International Conference on Very Large Data Bases, VLDB 2016. The 7 revised full papers presented together with 2 invited papers and 3 keynote abstracts were carefully reviewed and selected from 11 initial submissions. The papers are organized in topical sections on knowledge discovery of biomedical data; managing, querying and processing of medical image data; information extraction and data integration for biomedical data; and health information systems.
Download or read book Analytics in Healthcare written by Christo El Morr and published by Springer. This book was released on 2019-01-21 with total page 105 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book offers a practical introduction to healthcare analytics that does not require a background in data science or statistics. It presents the basics of data, analytics and tools and includes multiple examples of their applications in the field. The book also identifies practical challenges that fuel the need for analytics in healthcare as well as the solutions to address these problems. In the healthcare field, professionals have access to vast amount of data in the form of staff records, electronic patient record, clinical findings, diagnosis, prescription drug, medical imaging procedure, mobile health, resources available, etc. Managing the data and analyzing it to properly understand it and use it to make well-informed decisions can be a challenge for managers and health care professionals. A new generation of applications, sometimes referred to as end-user analytics or self-serve analytics, are specifically designed for non-technical users such as managers and business professionals. The ability to use these increasingly accessible tools with the abundant data requires a basic understanding of the core concepts of data, analytics, and interpretation of outcomes. This book is a resource for such individuals to demystify and learn the basics of data management and analytics for healthcare, while also looking towards future directions in the field.
Download or read book Big Data Analytics for Intelligent Healthcare Management written by Nilanjan Dey and published by Academic Press. This book was released on 2019-04-15 with total page 312 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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
Download or read book Big Data Analytics for Healthcare written by Pantea Keikhosrokiani and published by Academic Press. This book was released on 2022-05-19 with total page 356 pages. Available in PDF, EPUB and Kindle. Book excerpt: Big Data Analytics and Medical Information Systems presents the valuable use of artificial intelligence and big data analytics in healthcare and medical sciences. It focuses on theories, methods and approaches in which data analytic techniques can be used to examine medical data to provide a meaningful pattern for classification, diagnosis, treatment, and prediction of diseases. The book discusses topics such as theories and concepts of the field, and how big medical data mining techniques and applications can be applied to classification, diagnosis, treatment, and prediction of diseases. In addition, it covers social, behavioral, and medical fake news analytics to prevent medical misinformation and myths. It is a valuable resource for graduate students, researchers and members of biomedical field who are interested in learning more about analytic tools to support their work. Presents theories, methods and approaches in which data analytic techniques are used for medical data Brings practical information on how to use big data for classification, diagnosis, treatment, and prediction of diseases Discusses social, behavioral, and medical fake news analytics for medical information systems
Download or read book Big Data Analytics in Bioinformatics and Healthcare written by Wang, Baoying and published by IGI Global. This book was released on 2014-10-31 with total page 552 pages. Available in PDF, EPUB and Kindle. Book excerpt: As technology evolves and electronic data becomes more complex, digital medical record management and analysis becomes a challenge. In order to discover patterns and make relevant predictions based on large data sets, researchers and medical professionals must find new methods to analyze and extract relevant health information. Big Data Analytics in Bioinformatics and Healthcare merges the fields of biology, technology, and medicine in order to present a comprehensive study on the emerging information processing applications necessary in the field of electronic medical record management. Complete with interdisciplinary research resources, this publication is an essential reference source for researchers, practitioners, and students interested in the fields of biological computation, database management, and health information technology, with a special focus on the methodologies and tools to manage massive and complex electronic information.
Download or read book Big Data Analytics in Healthcare written by Anand J. Kulkarni and published by Springer Nature. This book was released on 2019-10-01 with total page 187 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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. The concept of big data is revolutionary, both from a technological and societal well-being standpoint. This book provides a comprehensive reference guide for engineers, scientists, and students studying/involved in the development of big data tools in the areas of healthcare and medicine. It also features a multifaceted and state-of-the-art literature review on healthcare data, its modalities, complexities, and methodologies, along with mathematical formulations. The book is divided into two main sections, the first of which discusses the challenges and opportunities associated with the implementation of big data in the healthcare sector. In turn, the second addresses the mathematical modeling of healthcare problems, as well as current and potential future big data applications and platforms.
Download or read book Healthcare Analytics for Quality and Performance Improvement written by Trevor L. Strome and published by John Wiley & Sons. This book was released on 2013-10-02 with total page 246 pages. Available in PDF, EPUB and Kindle. Book excerpt: Improve patient outcomes, lower costs, reduce fraud—all with healthcare analytics Healthcare Analytics for Quality and Performance Improvement walks your healthcare organization from relying on generic reports and dashboards to developing powerful analytic applications that drive effective decision-making throughout your organization. Renowned healthcare analytics leader Trevor Strome reveals in this groundbreaking volume the true potential of analytics to harness the vast amounts of data being generated in order to improve the decision-making ability of healthcare managers and improvement teams. Examines how technology has impacted healthcare delivery Discusses the challenge facing healthcare organizations: to leverage advances in both clinical and information technology to improve quality and performance while containing costs Explores the tools and techniques to analyze and extract value from healthcare data Demonstrates how the clinical, business, and technology components of healthcare organizations (HCOs) must work together to leverage analytics Other industries are already taking advantage of big data. Healthcare Analytics for Quality and Performance Improvement helps the healthcare industry make the most of the precious data already at its fingertips for long-overdue quality and performance improvement.
Download or read book Efficient Data Handling for Massive Internet of Medical Things written by Chinmay Chakraborty and published by Springer Nature. This book was released on 2021-09-01 with total page 398 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book focuses on recent advances and different research areas in multi-modal data fusion under healthcare informatics and seeks out theoretical, methodological, well-established and validated empirical work dealing with these different topics. This book brings together the latest industrial and academic progress, research, and development efforts within the rapidly maturing health informatics ecosystem. Contributions highlight emerging data fusion topics that support prospective healthcare applications. The book also presents various technologies and concerns regarding energy aware and secure sensors and how they can reduce energy consumption in health care applications. It also discusses the life cycle of sensor devices and protocols with the help of energy-aware design, production, and utilization, as well as the Internet of Things technologies such as tags, sensors, sensing networks, and Internet technologies. In a nutshell, this book gives a comprehensive overview of the state-of-the-art theories and techniques for massive data handling and access in medical data and smart health in IoT, and provides useful guidelines for the design of massive Internet of Medical Things.
