Medical Data Management PDF Book

Author : Florian Leiner,Wilhelm Gaus,Reinhold Haux,Petra Knaup-Gregori
Publisher : Springer Science & Business Media
Release : 2006-04-18
Category : Medical
ISBN : 9780387217734
File Size : 17,9 Mb
Total Download : 132

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Book Summary: Medical Data Management is a systematic introduction to the basic methodology of professional clinical data management. It emphasizes generic methods of medical documentation applicable to such diverse tasks as the electronic patient record, maintaining a clinical trials database, and building a tumor registry. This book is for all students in medical informatics and health information management, and it is ideal for both the undergraduate and the graduate levels. The book also guides professionals in the design and use of clinical information systems in various health care settings. It is an invaluable resource for all health care professionals involved in designing, assessing, adapting, or using clinical data management systems in hospitals, outpatient clinics, study centers, health plans, etc. The book combines a consistent theoretical foundation of medical documentation methods outlining their practical applicability in real clinical data management systems. Two new chapters detail hospital information systems and clinical trials. There is a focus on the international classification of diseases (ICD-9 and -10) systems, as well as a discussion on the difference between the two codes. All chapters feature exercises, bullet points, and a summary to provide the reader with essential points to remember. New to the Third Edition is a comprehensive section comprised of a combined Thesaurus and Glossary which aims to clarify the unclear and sometimes inconsistent terminology surrounding the topic.

Author : Nilanjan Dey,Amira S. Ashour,Simon James Fong,Chintan Bhatt
Publisher : Academic Press
Release : 2018-11-15
Category : Science
ISBN : 9780128156360
File Size : 54,9 Mb
Total Download : 800

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Book Summary: 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

Author : Richard K. Rondel,Sheila A. Varley,Colin F. Webb
Publisher : John Wiley & Sons
Release : 2000-02-03
Category : Medical
ISBN : 0471983292
File Size : 17,9 Mb
Total Download : 703

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Book Summary: Extensively revised and updated, with the addition of new chapters and authors, this long-awaited second edition covers all aspects of clinical data management. Giving details of the efficient clinical data management procedures required to satisfy both corporate objectives and quality audits by regulatory authorities, this text is timely and an important contribution to the literature. The volume: * is written by well-known and experienced authors in this area * provides new approaches to major topics in clinical data management * contains new chapters on systems software validation, database design and performance measures. It will be invaluable to anyone in the field within the pharmaceutical industry, and to all biomedical professionals working in clinical research.

Author : Martha L. Sylvia, PhD, MBA, RN
Publisher : Springer Publishing Company
Release : 2018-03-28
Category : Medical
ISBN : 9780826142788
File Size : 47,8 Mb
Total Download : 485

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Book Summary: 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

Author : Wilhelm Kirch
Publisher : Springer Science & Business Media
Release : 2008-06-13
Category : Medical
ISBN : 9781402056130
File Size : 19,9 Mb
Total Download : 146

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Book Summary: The Encyclopedic Reference of Public Health presents the most important definitions, principles and general perspectives of public health, written by experts of the different fields. The work includes more than 2,500 alphabetical entries. Entries comprise review-style articles, detailed essays and short definitions. Numerous figures and tables enhance understanding of this little-understood topic. Solidly structured and inclusive, this two-volume reference is an invaluable tool for clinical scientists and practitioners in academia, health care and industry, as well as students, teachers and interested laypersons.

Author : Lisa Federer
Publisher : Rowman & Littlefield
Release : 2016-09-15
Category : Language Arts & Disciplines
ISBN : 9781442264281
File Size : 29,9 Mb
Total Download : 928

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Book Summary: Technological advances and the rise of collaborative, interdisciplinary approaches have changed the practice of research. The 21st century researcher not only faces the challenge of managing increasingly complex datasets, but also new data sharing requirements from funders and journals. Success in today’s research enterprise requires an understanding of how to work effectively with data, yet most researchers have never had any formal training in data management. Libraries have begun developing services and programs to help researchers meet the demands of the data-driven research enterprise, giving librarians exciting new opportunities to use their expertise and skills. The Medical Library Association Guide to Data Management for Librarians highlights the many ways that librarians are addressing researchers’ changing needs at a variety of institutions, including academic, hospital, and government libraries. Each chapter ends with “pearls of wisdom,” a bulleted list of 5-10 takeaway messages from the chapter that will help readers quickly put the ideas from the chapter into practice. From theoretical foundations to practical applications, this book provides a background for librarians who are new to data management as well as new ideas and approaches for experienced data librarians.

Author : Nadinia Davis,Betsy J. Shiland
Publisher : Elsevier Health Sciences
Release : 2015-12-04
Category : Medical
ISBN : 9780323292214
File Size : 37,8 Mb
Total Download : 783

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Book Summary: 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.

Author : Pieter Kubben,Michel Dumontier,Andre Dekker
Publisher : Springer
Release : 2018-12-21
Category : Medical
ISBN : 9783319997131
File Size : 25,9 Mb
Total Download : 701

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Book Summary: This open access book comprehensively covers the fundamentals of clinical data science, focusing on data collection, modelling and clinical applications. Topics covered in the first section on data collection include: data sources, data at scale (big data), data stewardship (FAIR data) and related privacy concerns. Aspects of predictive modelling using techniques such as classification, regression or clustering, and prediction model validation will be covered in the second section. The third section covers aspects of (mobile) clinical decision support systems, operational excellence and value-based healthcare. Fundamentals of Clinical Data Science is an essential resource for healthcare professionals and IT consultants intending to develop and refine their skills in personalized medicine, using solutions based on large datasets from electronic health records or telemonitoring programmes. The book’s promise is “no math, no code”and will explain the topics in a style that is optimized for a healthcare audience.