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E-raamat: Health Services Research and Analytics Using Excel

  • Formaat: 550 pages
  • Ilmumisaeg: 01-Feb-2020
  • Kirjastus: Springer Publishing Co Inc
  • Keel: eng
  • ISBN-13: 9780826150288
  • Formaat - EPUB+DRM
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  • Formaat: 550 pages
  • Ilmumisaeg: 01-Feb-2020
  • Kirjastus: Springer Publishing Co Inc
  • Keel: eng
  • ISBN-13: 9780826150288

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Your all-in-one resource for quantitative, qualitative, and spatial analyses in Excel® using current real-world healthcare datasets.

Health Services Research and Analytics Using Excel® is a practical resource for graduate and advanced undergraduate students in programs studying healthcare administration, public health, and social work as well as public health workers and healthcare managers entering or working in the field. This book provides one integrated, application-oriented resource for common quantitative, qualitative, and spatial analyses using only Excel. With an easy-to-follow presentation of qualitative and quantitative data, students can foster a balanced decision-making approach to financial data, patient statistical data and utilization information, population health data, and quality metrics while cultivating analytical skills that are necessary in a data-driven healthcare world. Whereas Excel is typically considered limited to quantitative application, this book expands into other Excel applications based on spatial analysis and data visualization represented through 3D Maps as well as text analysis using the free add-in in Excel.

Chapters cover the important methods and statistical analysis tools that a practitioner will face when navigating and analyzing data in the public domain or from internal data collection at their health services organization. Topics covered include importing and working with data in Excel; identifying, categorizing, and presenting data; setting bounds and hypothesis testing; testing the mean; checking for patterns; data visualization and spatial analysis; interpreting variance; text analysis; and much more. A concise overview of research design also provides helpful background on how to gather and measure useful data prior to analyzing in Excel. Because Excel is the most common data analysis software used in the workplace setting, all case examples, exercises, and tutorials are provided with the latest updates to the Excel software from Office365 ProPlus® and newer versions, including all important Add-ins such as 3D Maps, MeaningCloud, and Power Pivots, among others. With numerous practice problems and over 100 step-by-step videos, Health Services Research and Analytics Using Excel® is an extremely practical tool for students and health service professionals who must know how to work with data, how to analyze it, and how to use it to improve outcomes unique to healthcare settings.





Key Features:Provides a competency-based analytical approach to health services research using Excel Includes applications of spatial analysis and data visualization tools based on 3D Maps in Excel Lists select sources of useful national healthcare data with descriptions and website information Chapters contain case examples and practice problems unique to health services All figures and videos are applicable to Office365 ProPlus Excel and newer versions Contains over 100 step-by-step videos of Excel applications covered in the chapters and provides concise video tutorials demonstrating solutions to all end-of-chapter practice problems Robust Instructor ancillary package that includes Instructors Manual, PowerPoints, and Test Bank
Preface xi
Acknowledgments xv
1 Introduction to Healthcare Data and the Role of Excel
1(10)
1.1 Context
1(2)
1.2 Approach Advocated
3(3)
1.3 Outline of the Book
6(1)
1.4 Competency Development
7(2)
1.5 Summary
9(1)
1.6 Discussion Questions
10(1)
2 Working in Excel* and Importing Healthcare Data
11(28)
2.1 Sources of Healthcare Data
14(2)
2.2 Data Used for Decision-Making
16(2)
2.3 Excel in Actionable Insights
18(1)
2.4 Importing Data Into Excel
19(2)
2.5 Editing Cells and Content
21(2)
2.6 Managing Data
23(8)
2.7 Managing Add-Ins in Excel
31(2)
2.8 Competency Development
33(1)
2.9 Summary
34(1)
2.10 Discussion Questions
34(1)
2.11 Practice Problems
35(4)
3 Identifying, Categorizing, and Presenting Healthcare Data Using Excel*
39(30)
3.1 Getting Started
39(3)
3.2 Identifying Your Data
42(6)
3.3 Using Pivot Tables
48(4)
3.4 Pivot Charts
52(3)
3.5 Using Chart Types in Excel
55(9)
3.6 Considerations in Using Different Chart Types
64(1)
3.7 Competency Development
65(1)
3.8 Summary
66(1)
3.9 Discussion Questions
66(1)
3.10 Practice Problems
67(2)
4 Setting Bounds for Healthcare Data and Hypothesis Testing Using Excel*
69(24)
4.1 Introduction
69(3)
4.2 Setting Bounds on Data
72(1)
4.3 Sample and Population
72(3)
4.4 Measure and Variation
75(1)
4.5 Confidence Interval
76(2)
4.6 Hypothesis Testing
78(1)
4.7 Z-Test
79(3)
4.8 Comparing Two Samples Using the Z-Test
82(5)
4.9 Competency Development
87(1)
4.10 Summary
88(1)
4.11 Discussion Questions
89(1)
4.12 Practice Problems
89(4)
5 Testing and Comparing Means of Healthcare Datasets Using Excel*
93(18)
5.1 t-Test
93(2)
5.2 Assumptions for the f-Test
95(1)
5.3 Example for f-Test
95(4)
5.4 t-Test Two-Sample Mean Assuming Equal Variance
99(1)
5.5 t-Test Two-Sample Mean Assuming Unequal Variance
100(3)
5.6 t-Test Paired Two-Sample Mean
103(2)
5.7 Competency Development
105(1)
5.8 Summary
106(1)
5.9 Discussion Questions
106(1)
5.10 Practice Problems
106(5)
6 Checking Patterns in Healthcare Data Using Scatterplots, Correlations, and Regressions in Excel*
111(24)
6.1 Exploring Relationships and Patterns
114(1)
6.2 Scatterplot and Correlation
115(4)
6.3 Regression
119(1)
6.4 Single Linear Regression
119(4)
6.5 Multiple Regression
123(4)
6.6 Revisiting Missing Values
127(2)
6.7 Competency Development
129(1)
6.8 Summary
130(1)
6.9 Discussion Questions
130(1)
6.10 Practice Problems
131(4)
7 Visualization and Spatial Analysis of Healthcare Data Using 3D Maps in Excel*
135(20)
7.1 Why and When to Map Data
135(3)
7.2 Converting Data to Tables
138(2)
7.3 Turn to 3D Maps
140(1)
7.4 Steps in Visualizing 3D Maps
141(3)
7.5 Working With Scenes
144(1)
7.6 Including Time Element
145(3)
7.7 Production of Tour
148(1)
7.8 Competency Development
149(1)
7.9 Summary
150(1)
7.10 Discussion Questions
151(1)
7.11 Practice Problems
151(4)
8 Using Analysis of Variance (ANOVA) in Healthcare Datasets to Compare Groups and Test Hypotheses in Excel*
155(12)
8.1 ANOVA
155(2)
8.2 Creating Categories
157(1)
8.3 Stating Hypotheses
158(1)
8.4 Getting Data Ready in Excel
158(3)
8.5 Interpreting ANOVA Output
161(1)
8.6 Competency Development
162(1)
8.7 Summary
163(1)
8.8 Discussion Questions
163(1)
8.9 Practice Problems
164(3)
9 Text Analysis of Healthcare Data Using MeaningCloud Add-In in Excel*
167(18)
9.1 Qualitative Data in Healthcare
169(1)
9.2 Qualitative Analysis and Excel
169(1)
9.3 MeaningCloud Add-In
170(1)
9.4 Text Classification
171(1)
9.5 Sentiment Analysis
172(4)
9.6 Topic Extraction
176(1)
9.7 Text Clustering
176(4)
9.8 Competency Development
180(1)
9.9 Summary
181(1)
9.10 Discussion Questions
181(1)
9.11 Practice Problems
181(4)
10 Sampling and Research Design Using Healthcare Data in Excel*
185(16)
10.1 Research Driven by Questions
185(3)
10.2 Sampling
188(1)
10.3 Probability Sampling
189(5)
10.4 Nonprobability Sampling
194(1)
10.5 Research Design
195(2)
10.6 Competency Development
197(1)
10.7 Summary
198(1)
10.8 Discussion Questions
198(1)
10.9 Practice Problems
198(3)
11 Video Tutorials and Answers to Practice Problems Using Healthcare Datasets in Excel*
201(6)
12 List of Select Sources of Healthcare Data
207(12)
13 Glossary
219(12)
Index 231
Nalin Johri, PhD, MPH, MA (Social Work) is an assistant professor and assessment coordinator in the Masters in Healthcare Administration (MHA) program/Department of Interprofessional Health Sciences and Healthcare Administration/School of Health and Medical Sciences at Seton Hall University.