Statistics Data Analytics For Health Data Management

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Statistics Data Analytics For Health Data Management

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Author : Nadinia A. Davis
language : en
Publisher: Elsevier Health Sciences
Release Date : 2015-12-04

Statistics Data Analytics For Health Data Management written by Nadinia A. Davis and has been published by Elsevier Health Sciences this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-12-04 with Medical categories.

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.

Healthcare Data Analytics And Management

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Author : Nilanjan Dey
language : en
Publisher: Academic Press
Release Date : 2018-11-15

Healthcare Data Analytics And Management written by Nilanjan Dey and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-11-15 with Science categories.

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

Analytics In Healthcare

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Author : Christo El Morr
language : en
Publisher: Springer
Release Date : 2019-01-21

Analytics In Healthcare written by Christo El Morr and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-01-21 with Medical categories.

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.

Data Science For Healthcare

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Author : Sergio Consoli
language : en
Publisher: Springer
Release Date : 2019-02-23

Data Science For Healthcare written by Sergio Consoli and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-02-23 with Computers categories.

This book seeks to promote the exploitation of data science in healthcare systems. The focus is on advancing the automated analytical methods used to extract new knowledge from data for healthcare applications. To do so, the book draws on several interrelated disciplines, including machine learning, big data analytics, statistics, pattern recognition, computer vision, and Semantic Web technologies, and focuses on their direct application to healthcare. Building on three tutorial-like chapters on data science in healthcare, the following eleven chapters highlight success stories on the application of data science in healthcare, where data science and artificial intelligence technologies have proven to be very promising. This book is primarily intended for data scientists involved in the healthcare or medical sector. By reading this book, they will gain essential insights into the modern data science technologies needed to advance innovation for both healthcare businesses and patients. A basic grasp of data science is recommended in order to fully benefit from this book.

Big Data In Healthcare

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Author : Farrokh Alemi
language : en
Publisher:
Release Date : 2019

Big Data In Healthcare written by Farrokh Alemi and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019 with Data mining categories.

Big Data in Healthcare: Statistical Analysis of the Electronic Health Record provides the statistical tools that healthcare leaders need to organize and interpret their data. Designed for accessibility to those with a limited mathematics background, the book demonstrates how to leverage EHR data for applications as diverse as healthcare marketing, pay for performance, cost accounting, and strategic management. Topics include:* Using real-world data to compare hospitals' performance. * Measuring the prognosis of patients through massive data* Distinguishing between fake claims and true improvements* Comparing the effectiveness of different interventions using causal analysis* Benchmarking different clinicians on the same set of patients* Remove confounding in observational dataThis book can be used in introductory courses on hypothesis testing, intermediate courses on regression, and advanced courses on causal analysis. It can also be used to learn SQL language. Its extensive online instructor resources include course syllabi, PowerPoint and video lectures, Excel exercises, individual and team assignments, answers to assignments, and student-organized tutorials. Big Data in Healthcare applies the building blocks of statistical thinking to the basic challenges that healthcare leaders face every day. Prepare for those challenges with the clear understanding of your data that statistical analysis can bring--and make the best possible decisions for maximum performance in the competitive field of healthcare.

Big Data And Health Analytics

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Author : Katherine Marconi
language : en
Publisher: Auerbach Publications
Release Date : 2014-12-20

Big Data And Health Analytics written by Katherine Marconi and has been published by Auerbach Publications this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-12-20 with Business & Economics categories.

Data availability is surpassing existing paradigms for governing, managing, analyzing, and interpreting health data. Big Data and Health Analytics 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 is not a technical book on the use of statistics and machine-learning algorithms for extracting knowledge out of data, nor a book on the intricacies of database design. Instead, this book presents the current thinking of academic and industry researchers and leaders from around the world. Using non-technical language, this book is accessible to health care professionals who might not have an IT and analytics background. It includes case studies that illustrate the business processes underlying the use of big data and health analytics to improve health care delivery. Highlighting lessons learned from the case studies, the book supplies readers with the foundation required for further specialized study in health analytics and data management. Coverage includes community health information, information visualization which offers interactive environments and analytic processes that support exploration of EHR data, the governance structure required to enable data analytics and use, federal regulations and the constraints they place on analytics, and information security. Links to websites, videos, articles, and other online content that expand and support the primary learning objectives for each major section of the book are also included to help you develop the skills you will need to achieve quality improvements in health care delivery through the effective use of data and analytics.

Exploratory Data Analytics For Healthcare

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Author : R. Lakshmana Kumar
language : en
Publisher: CRC Press
Release Date : 2021-12-23

Exploratory Data Analytics For Healthcare written by R. Lakshmana Kumar and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-12-23 with Computers categories.

Exploratory data analysis helps to recognize natural patterns hidden in the data. This book describes the tools for hypothesis generation by visualizing data through graphical representation and provides insight into advanced analytics concepts in an easy way. The book addresses the complete data visualization technologies workflow, explores basic and high-level concepts of computer science and engineering in medical science, and provides an overview of the clinical scientific research areas that enables smart diagnosis equipment. It will discuss techniques and tools used to explore large volumes of medical data and offers case studies that focus on the innovative technological upgradation and challenges faced today. The primary audience for the book includes specialists, researchers, graduates, designers, experts, physicians, and engineers who are doing research in this domain.

Health Services Research And Analytics Using Excel

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Author : Nalin Johri, PhD, MPH
language : en
Publisher: Springer Publishing Company
Release Date : 2020-02-01

Health Services Research And Analytics Using Excel written by Nalin Johri, PhD, MPH and has been published by Springer Publishing Company this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-02-01 with Medical categories.

Your all-in-one resource for quantitative, qualitative, and spatial analyses in Excel® using current real-world healthcare datasets. Health Services Research and Analytics Using Excel® is a practical resource for graduate and advanced undergraduate students in programs studying healthcare administration, public health, and social work as well as public health workers and healthcare managers entering or working in the field. This book provides one integrated, application-oriented resource for common quantitative, qualitative, and spatial analyses using only Excel. With an easy-to-follow presentation of qualitative and quantitative data, students can foster a balanced decision-making approach to financial data, patient statistical data and utilization information, population health data, and quality metrics while cultivating analytical skills that are necessary in a data-driven healthcare world. Whereas Excel is typically considered limited to quantitative application, this book expands into other Excel applications based on spatial analysis and data visualization represented through 3D Maps as well as text analysis using the free add-in in Excel. Chapters cover the important methods and statistical analysis tools that a practitioner will face when navigating and analyzing data in the public domain or from internal data collection at their health services organization. Topics covered include importing and working with data in Excel; identifying, categorizing, and presenting data; setting bounds and hypothesis testing; testing the mean; checking for patterns; data visualization and spatial analysis; interpreting variance; text analysis; and much more. A concise overview of research design also provides helpful background on how to gather and measure useful data prior to analyzing in Excel. Because Excel is the most common data analysis software used in the workplace setting, all case examples, exercises, and tutorials are provided with the latest updates to the Excel software from Office365 ProPlus® and newer versions, including all important “Add-ins” such as 3D Maps, MeaningCloud, and Power Pivots, among others. With numerous practice problems and over 100 step-by-step videos, Health Services Research and Analytics Using Excel® is an extremely practical tool for students and health service professionals who must know how to work with data, how to analyze it, and how to use it to improve outcomes unique to healthcare settings. Key Features: Provides a competency-based analytical approach to health services research using Excel Includes applications of spatial analysis and data visualization tools based on 3D Maps in Excel Lists select sources of useful national healthcare data with descriptions and website information Chapters contain case examples and practice problems unique to health services All figures and videos are applicable to Office365 ProPlus Excel and newer versions Contains over 100 step-by-step videos of Excel applications covered in the chapters and provides concise video tutorials demonstrating solutions to all end-of-chapter practice problems Robust Instructor ancillary package that includes Instructor’s Manual, PowerPoints, and Test Bank

Big Data Analytics For Healthcare

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Author : Pantea Keikhosrokiani
language : en
Publisher: Academic Press
Release Date : 2022-05-19

Big Data Analytics For Healthcare written by Pantea Keikhosrokiani and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-05-19 with Medical categories.

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

Spss Statistics For Data Analysis And Visualization

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Author : Keith McCormick
language : en
Publisher: John Wiley & Sons
Release Date : 2017-05-01

Spss Statistics For Data Analysis And Visualization written by Keith McCormick and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-05-01 with Computers categories.

Dive deeper into SPSS Statistics for more efficient, accurate, and sophisticated data analysis and visualization SPSS Statistics for Data Analysis and Visualization goes beyond the basics of SPSS Statistics to show you advanced techniques that exploit the full capabilities of SPSS. The authors explain when and why to use each technique, and then walk you through the execution with a pragmatic, nuts and bolts example. Coverage includes extensive, in-depth discussion of advanced statistical techniques, data visualization, predictive analytics, and SPSS programming, including automation and integration with other languages like R and Python. You'll learn the best methods to power through an analysis, with more efficient, elegant, and accurate code. IBM SPSS Statistics is complex: true mastery requires a deep understanding of statistical theory, the user interface, and programming. Most users don't encounter all of the methods SPSS offers, leaving many little-known modules undiscovered. This book walks you through tools you may have never noticed, and shows you how they can be used to streamline your workflow and enable you to produce more accurate results. Conduct a more efficient and accurate analysis Display complex relationships and create better visualizations Model complex interactions and master predictive analytics Integrate R and Python with SPSS Statistics for more efficient, more powerful code These "hidden tools" can help you produce charts that simply wouldn't be possible any other way, and the support for other programming languages gives you better options for solving complex problems. If you're ready to take advantage of everything this powerful software package has to offer, SPSS Statistics for Data Analysis and Visualization is the expert-led training you need.