Statistical Applications for Health Information Management / Edition 1

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Overview

"Statistical Applications for Health Information Management covers the basic biostatistics, descriptive statistics, and inferential statistics that are unique to health information management. The text provides the essential theory while emphasizing practical applications that health information management professionals use in the real world every day. For example, computer applications used in the real world are emphasized throughout the book, with only a minimal focus on manual applications. To further assist readers, spreadsheet exercises and other learning resources are provided on Aspen's Web site. An instructor's manual is also available for this textbook.".

The book contains black-and-white illustrations.

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Editorial Reviews

Doody's Review Service
Reviewer: LouAnn Schraffenberger, MBA, RHIA, CCS, CCS-P(Advocate Health Care)
Description: The focus of this book is on applying statistical techniques to problems in healthcare.
Purpose: The author's goal is to introduce students and professionals to how statistical techniques can be used to describe and make inferences from healthcare data. The book is written for the reader who has had coursework in probability theory and normal distribution. It is designed so that students can use the Aspen Publishers' Web site that supports the book or input the data for each problem using their own statistical software. The book includes examples using SPSS and Microsoft Excel.
Audience: The book is specifically written for students in bachelor degree programs for health information management. It should also be promoted to practitioners who may not have had a solid statistics course and now find they need to understand statistical techniques in their everyday work.
Features: The focus is on health information interests in the exercises presented. Frequency measures, graphic display of data, introduction to measurement, measures of central tendency, normal distribution and statistical inference, hypothesis testing, analysis of variance, correlation and linear regression, Chi square, and non-parametric methods are all covered. Two appendixes have an excellent glossary and statistical tables.
Assessment: There is no way to make this subject easy but the author has made it clear. This book is unique as he promotes the use of statistical techniques in problems in healthcare encountered in everyday work. Health information academic program leaders should consider this book for their statistical analysis or introductory evaluation or research courses. The book should not be limited to health information management courses. It should be a welcome addition to the textbooks for coursework in healthcare administration programs at both the bachelor and master levels. Students and practitioners interested in graduate study would benefit from the book as it will give them a knowledge advantage in graduate statistics courses.
LouAnn Schraffenberger
The focus of this book is on applying statistical techniques to problems in healthcare. The author's goal is to introduce students and professionals to how statistical techniques can be used to describe and make inferences from healthcare data. The book is written for the reader who has had coursework in probability theory and normal distribution. It is designed so that students can use the Aspen Publishers' Web site that supports the book or input the data for each problem using their own statistical software. The book includes examples using SPSS and Microsoft Excel. The book is specifically written for students in bachelor degree programs for health information management. It should also be promoted to practitioners who may not have had a solid statistics course and now find they need to understand statistical techniques in their everyday work. The focus is on health information interests in the exercises presented. Frequency measures, graphic display of data, introduction to measurement, measures of central tendency, normal distribution and statistical inference, hypothesis testing, analysis of variance, correlation and linear regression, Chi square, and non-parametric methods are all covered. Two appendixes have an excellent glossary and statistical tables. There is no way to make this subject easy but the author has made it clear. This book is unique as he promotes the use of statistical techniques in problems in healthcare encountered in everyday work. Health information academic program leaders should consider this book for their statistical analysis or introductory evaluation or research courses. The book should not be limited to health information management courses.It should be a welcome addition to the textbooks for coursework in healthcare administration programs at both the bachelor and master levels. Students and practitioners interested in graduate study would benefit from the book as it will give them a knowledge advantage in graduate statistics courses.
Booknews
A textbook for undergraduate health information management students. Osborne (health information management, Ohio U.) focuses on applying statistical techniques to problems in health care. Statistical techniques discussed include measures of central tendency and variability, normal distribution and statistical inference, hypothesis testing of the difference between two population means, analysis of variance, correlation and linear regression, chi-square tests, and nonparametric methods. Because the focus is on application, it is assumed that the student has had previous experience in probability theory and the normal distribution. Annotation c. Book News, Inc., Portland, OR (booknews.com)

5 Stars! from Doody
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Product Details

  • ISBN-13: 9780834212435
  • Publisher: Jones & Bartlett Learning, LLC
  • Publication date: 3/30/2000
  • Edition description: Older Edition
  • Edition number: 1
  • Pages: 334

Table of Contents

Contents: Commonly Used Frequency Measures in Health Care * Graphic Display of Data * Introduction to Measurement * Measures of Central Tendency and Variability * The Normal Distribution and Statistical Inference * Hypothesis Testing of the Difference Between Population Means *Analysis of Variance * Correlation and Linear Regression * Chi Square * Nonparametric Methods * Glossary * Appendixes * Frequency Distribution of Discharges by DRGs, Critical Care Hospital, 1997 * Index
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