Books.org participates in affiliate programs including Bookshop.org and the Amazon Services LLC Associates Program. We may earn a commission from qualifying purchases made through links on this page, at no additional cost to you.
Overview
From the author of Statistical Applications for Health Information Management, this text provides a solid foundation of the fundamentals of statistics in health information technology in an accessible and reader-friendly format.
A single case study is woven throughout the book to serve as an example for each statistical process covered. Attention is given to morbidity and mortality measures, graphical display of data, measurement, central tendency and variability, normal distribution and statistical inference, and inferential statistics.
Written specifically for health information technology students who need a basic understanding of the topic, this text is ideal for those with a modest background in mathematics and no prior training in statistics.
Features:
β’ Introduces students to how statistical techniques can be used to describe and make inferences from healthcare data.
β’ Includes traditional hospital statistics such as average length of stay and total inpatient service days.
β’ Uses examples in both SPSS and Microsoft Excel.
Editorials
From The Critics
Reviewer: LouAnn Schraffenberger, MBA, RHIA, CCS, CCS-P(Univ of Illinois at Chicago School of Biomed & Health Info Mgmt)Description: This book is intended to provide instruction on the fundamentals of healthcare statistics in health information technology. While written for health information technology students, anyone with a modest background in mathematics but no background in statistics can use this to get a basic understanding of the computation of healthcare statistics. The book is also a good reference for practicing health information professionals who need a refresher on healthcare related statistics.
Purpose: According to the author, the book was written specifically for health information technology (HIT) students enrolled in associate degree programs. It may also be used by practicing health information professionals who need a review of healthcare statistic definitions and computations. The author's goal was to introduce students and professionals to how statistical techniques can be used to describe and make inferences from healthcare data.
Audience: HIT students in an associate degree program of health information technology are the primary audience. Other potential readers include practicing health information professionals and others in healthcare who need a basic understanding of healthcare statistics. The author is a practicing health information manager with a PhD in research and evaluation that makes her uniquely qualified to teach statistics to members of her profession.
Features: The eight chapters include basic statistical data used in acute care facilities; population-based morbidity and mortality measures; graphic display of data; introduction to measurement; measures of central tendency and variability; the normal distribution and statistical inference; hypothesis testing and statistical inference; and measures of association. Three appendixes provide a glossary, statistical tables, and answers and solutions to chapter exercises. The book is organized to allow students to input the data for each problem using their own statistical software. It is not intended to teach students how to use SPSS, Excel or other types of statistical or spreadsheet software. Numerous tables, graphs, and other displays of data are used to explain a concept. Each chapter ends with exercises for problem solving.
Assessment: I was impressed with the clarity and simplicity with which the author explains healthcare statistics. The book is easy to read and the many tables and examples explain the concepts well. The exercises are reasonable yet challenging. Instructors in HIT programs would be smart to consider this book for teaching healthcare statistics. Practicing health information managers and quality/process improvement managers would also be smart to pick up this book for review or to finally understand what they didn't learn in school but need to know today for healthcare data analysis.
From The Critics
Reviewer: LouAnn Schraffenberger, MBA, RHIA, CCS, CCS-P(Univ of Illinois at Chicago School of Biomed & Health Info Mgmt)Description: This book is intended to provide instruction on the fundamentals of healthcare statistics in health information technology. While written for health information technology students, anyone with a modest background in mathematics but no background in statistics can use this to get a basic understanding of the computation of healthcare statistics. The book is also a good reference for practicing health information professionals who need a refresher on healthcare related statistics.
Purpose: According to the author, the book was written specifically for health information technology (HIT) students enrolled in associate degree programs. It may also be used by practicing health information professionals who need a review of healthcare statistic definitions and computations. The author's goal was to introduce students and professionals to how statistical techniques can be used to describe and make inferences from healthcare data.
Audience: HIT students in an associate degree program of health information technology are the primary audience. Other potential readers include practicing health information professionals and others in healthcare who need a basic understanding of healthcare statistics. The author is a practicing health information manager with a PhD in research and evaluation that makes her uniquely qualified to teach statistics to members of her profession.
Features: The eight chapters include basic statistical data used in acute care facilities; population-based morbidity and mortality measures; graphic display of data; introduction to measurement; measures of central tendency and variability; the normal distribution and statistical inference; hypothesis testing and statistical inference; and measures of association. Three appendixes provide a glossary, statistical tables, and answers and solutions to chapter exercises. The book is organized to allow students to input the data for each problem using their own statistical software. It is not intended to teach students how to use SPSS, Excel or other types of statistical or spreadsheet software. Numerous tables, graphs, and other displays of data are used to explain a concept. Each chapter ends with exercises for problem solving.
Assessment: I was impressed with the clarity and simplicity with which the author explains healthcare statistics. The book is easy to read and the many tables and examples explain the concepts well. The exercises are reasonable yet challenging. Instructors in HIT programs would be smart to consider this book for teaching healthcare statistics. Practicing health information managers and quality/process improvement managers would also be smart to pick up this book for review or to finally understand what they didn't learn in school but need to know today for healthcare data analysis.