Statistics & Data Analytics for Health Data Management

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.

Nadinia Davis has over 18 years of full-time teaching experience, encompassing both the associate and baccalaureate HIM levels. She has held program director-level positions in two associate programs, both of which she successfully led to timely accreditation. Nadinia has worked in a variety of capacities, including consultant coding, HIM department management, and revenue cycle director. Nadinia has volunteered for the American Health Information Management Association (AHIMA), including a term on the board of directors.The first edition of FHIM published in 2001 and won the AHIMA Legacy award. She has also written a reimbursement text for AHIMA.Betsy Shiland has authored 2 very successful medical terminology texts, along with a statistics text for health information management students. She is a credentialed coder (CCS, CPC), an EMT, a cancer registrar, and a health data administrator. She taught at Central College in Philadelphia for over 20 years.

Unit I: Understanding the Basics of Statistics and Data Analytics1. Introduction to Statistical Terms and Concepts in Health Data Management2. Basic Math Concepts, Central Tendency and Dispersion3. Data PresentationUnit II: Applications of Descriptive Statistics and Data Analysis in Health Care Settings4. Administrative Data5. Clinical Facility Data6. Public Health Data7. Departmental Data8. Financial DataUnit III: Advanced Data Analysis Techniques9. Scrubbing and Mapping Data10. Predicting Data

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