Statistics Data Analytics For Health Data Management
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| Author | : Nadinia Davis |
| Publisher | : Saunders |
| Total Pages | : 0 |
| Release | : 2016-01-26 |
| Genre | : Health services administration |
| ISBN | : 9781455753154 |
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 | : Martha L. Sylvia, PhD, MBA, RN |
| Publisher | : Springer Publishing Company |
| Total Pages | : 239 |
| Release | : 2014-05-05 |
| Genre | : Medical |
| ISBN | : 0826129749 |
"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 Strong data management knowledge and skills are a requirement for every DNP. This unique text focuses on fostering the rigorous, meticulous data management skills that can improve care experience, health outcomes, and cost savings worldwide. It provides a knowledge base, describes the regulatory and ethical context, outlines a process to guide evaluation, presents a compendium of resources, and includes examples of evaluation of translation. It takes the DNP student step by step through the complete process of data management, including planning, data collection, data governance and cleansing, analysis, and data presentation. Moreover, the text continues the process of establishing a sturdy clinical data management (CDM) skill base by presenting techniques for ongoing project monitoring after analysis and evaluation are concluded. A progressive case study illustrates multiple techniques throughout each chapter, enabling students to apply what they have learned to their own DNP projects. The book features information from professors who are highly experienced in teaching CDM as well as a renowned scholar of population health analytics. The text provides very specific examples of techniques using SPSSÆ software that is familiar to graduate nursing students. Chapters include objectives, references, and examples from translation projects to assist students to learn and apply chapter content. Appendices describe numerous tools and practical strategies compiled by the authors over several years of teaching CDM to DNP students. Key Features: Meets the specific data management needs of the DNP student from planning to presentation Presents a wide selection of data display options through frequent illustrations of SPSS data Uses a progressive case study to illustrate multiple techniques and methods throughout chapters Provides substantial content necessary for the DNP student to rigorously evaluate DNP innovations/projects Includes very specific examples of the application and utility of these techniques using software that is familiar to graduate nursing students
| Author | : Christo El Morr |
| Publisher | : Springer |
| Total Pages | : 105 |
| Release | : 2019-01-21 |
| Genre | : Medical |
| ISBN | : 3030045064 |
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.
| Author | : Ruth Etzioni |
| Publisher | : Springer Nature |
| Total Pages | : 238 |
| Release | : 2021-01-04 |
| Genre | : Medical |
| ISBN | : 3030598896 |
Students and researchers in the health sciences are faced with greater opportunity and challenge than ever before. The opportunity stems from the explosion in publicly available data that simultaneously informs and inspires new avenues of investigation. The challenge is that the analytic tools required go far beyond the standard methods and models of basic statistics. This textbook aims to equip health care researchers with the most important elements of a modern health analytics toolkit, drawing from the fields of statistics, health econometrics, and data science. This textbook is designed to overcome students’ anxiety about data and statistics and to help them to become confident users of appropriate analytic methods for health care research studies. Methods are presented organically, with new material building naturally on what has come before. Each technique is motivated by a topical research question, explained in non-technical terms, and accompanied by engaging explanations and examples. In this way, the authors cultivate a deep (“organic”) understanding of a range of analytic techniques, their assumptions and data requirements, and their advantages and limitations. They illustrate all lessons via analyses of real data from a variety of publicly available databases, addressing relevant research questions and comparing findings to those of published studies. Ultimately, this textbook is designed to cultivate health services researchers that are thoughtful and well informed about health data science, rather than data analysts. This textbook differs from the competition in its unique blend of methods and its determination to ensure that readers gain an understanding of how, when, and why to apply them. It provides the public health researcher with a way to think analytically about scientific questions, and it offers well-founded guidance for pairing data with methods for valid analysis. Readers should feel emboldened to tackle analysis of real public datasets using traditional statistical models, health econometrics methods, and even predictive algorithms. Accompanying code and data sets are provided in an author site: https://roman-gulati.github.io/statistics-for-health-data-science/
| Author | : John F. Kros |
| Publisher | : John Wiley & Sons |
| Total Pages | : 562 |
| Release | : 2015-12-15 |
| Genre | : Medical |
| ISBN | : 1118712641 |
The must-have statistics guide for students of health services Statistics for Health Care Management and Administration is a unique and invaluable resource for students of health care administration and public health. The book introduces students to statistics within the context of health care, focusing on the major data and analysis techniques used in the field. All hands-on instruction makes use of Excel, the most common spreadsheet software that is ubiquitous in the workplace. This new third edition has been completely retooled, with new content on proportions, ANOVA, linear regression, chi-squares, and more, Step-by-step instructions in the latest version of Excel and numerous annotated screen shots make examples easy to follow and understand. Familiarity with statistical methods is essential for health services professionals and researchers, who must understand how to acquire, handle, and analyze data. This book not only helps students develop the necessary data analysis skills, but it also boosts familiarity with important software that employers will be looking for. Learn the basics of statistics in the context of Excel Understand how to acquire data and display it for analysis Master various tests including probability, regression, and more Turn test results into usable information with proper analysis Statistics for Health Care Management and Administration gets students off to a great start by introducing statistics in the workplace context from the very beginning.
| Author | : Chandan K. Reddy |
| Publisher | : CRC Press |
| Total Pages | : 756 |
| Release | : 2015-06-23 |
| Genre | : Business & Economics |
| ISBN | : 148223212X |
At the intersection of computer science and healthcare, data analytics has emerged as a promising tool for solving problems across many healthcare-related disciplines. Supplying a comprehensive overview of recent healthcare analytics research, Healthcare Data Analytics provides a clear understanding of the analytical techniques currently available
| Author | : Nilanjan Dey |
| Publisher | : Academic Press |
| Total Pages | : 340 |
| Release | : 2018-11-15 |
| Genre | : Science |
| ISBN | : 0128156368 |
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 | : Jeffrey Wilson |
| Publisher | : CRC Press |
| Total Pages | : 280 |
| Release | : 2023-03-27 |
| Genre | : Business & Economics |
| ISBN | : 1000848825 |
This book aims to compile typical fundamental-to-advanced statistical methods to be used for health data sciences. Although the book promotes applications to health and health-related data, the models in the book can be used to analyze any kind of data. The data are analyzed with the commonly used statistical software of R/SAS (with online supplementary on SPSS/Stata). The data and computing programs will be available to facilitate readers’ learning experience. There has been considerable attention to making statistical methods and analytics available to health data science researchers and students. This book brings it all together to provide a concise point-of-reference for the most commonly used statistical methods from the fundamental level to the advanced level. We envisage this book will contribute to the rapid development in health data science. We provide straightforward explanations of the collected statistical theory and models, compilations of a variety of publicly available data, and illustrations of data analytics using commonly used statistical software of SAS/R. We will have the data and computer programs available for readers to replicate and implement the new methods. The primary readers would be applied data scientists and practitioners in any field of data science, applied statistical analysts and scientists in public health, academic researchers, and graduate students in statistics and biostatistics. The secondary readers would be R&D professionals/practitioners in industry and governmental agencies. This book can be used for both teaching and applied research.
| Author | : Katherine Marconi |
| Publisher | : CRC Press |
| Total Pages | : 374 |
| Release | : 2014-12-20 |
| Genre | : Business & Economics |
| ISBN | : 1482229250 |
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.
| Author | : Nadinia A. Davis |
| Publisher | : Elsevier Health Sciences |
| Total Pages | : 266 |
| Release | : 2015-12-04 |
| Genre | : Medical |
| ISBN | : 0323292216 |
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.
