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cover image - Statistics & Data Analytics for Health Data Management - Elsevier eBook on VitalSource,1st Edition
ISBN: 9781455773961
Copyright: 2017
Publication Date: 12-28-2015
Page Count: 264
Imprint: Saunders
List Price: $55.99

Statistics & Data Analytics for Health Data Management - Elsevier eBook on VitalSource, 1st Edition

by Nadinia A. Davis, MBA, RHIA, CHDA, CCS, FAHIMA and Betsy J. Shiland, MS, RHIA, CCS, CHDA, CPC, CPB, CPPM

Elsevier eBook on VitalSource

cover image - Statistics & Data Analytics for Health Data Management - Elsevier eBook on VitalSource,1st Edition
ISBN: 9781455773961
Copyright: 2017
Publication Date: 12-28-2015
Page Count: 264
Imprint: Saunders
List Price: $55.99
Was $55.99

Now $53.19

Or $0.00 with a valid access code

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.
  • Unit I: Understanding the Basics of Statistics and Data Analytics
    1. Introduction to Statistical Terms and Concepts in Health Data Management
    2. Basic Math Concepts, Central Tendency and Dispersion
    3. Data Presentation
    Unit II: Applications of Descriptive Statistics and Data Analysis in Health Care Settings
    4. Administrative Data
    5. Clinical Facility Data
    6. Public Health Data
    7. Departmental Data
    8. Financial Data
    Unit III: Advanced Data Analysis Techniques
    9. Scrubbing and Mapping Data
    10. Predicting Data
  • Nadinia A. Davis, MBA, RHIA, CHDA, CCS, FAHIMA, Program Coordinator, Health Information Management and Medical Coding Studies, Delaware Technical Community College, Wilmington, Delaware and Betsy J. Shiland, MS, RHIA, CCS, CHDA, CPC, CPB, CPPM, Former Assistant Professor, Allied Health Department, Community College of Philadelphia, Philadelphia, Pennsylvania
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