Title Health Services Research and Analytics Using Excel®
Subtitle
Author Nalin Johri
ISBN 9780826150271
List price USD 80.00
Price outside India Available on Request
Original price
Binding Paperback
No of pages 252
Book size 178 x 254 mm
Publishing year 2021
Original publisher Springer Publishing Company
Published in India by .
Exclusive distributors .
Sales territory Bangladesh, India, Pakistan, Sri Lanka
Status New Arrival
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Description:

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. 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


Contents:

Preface

Acknowledgments

 

Chapter 1. Introduction to Healthcare Data and the Role of Excel® • Context • Approach Advocated • Outline of the Book • Competency Development • Summary • Discussion Questions

Chapter 2. Working in Excel® and Importing Healthcare Data • Sources of Healthcare Data • Data Used for Decision-Making • Excel in Actionable Insights • Importing Data Into Excel • Editing Cells and Content • Managing Data • Managing Add-Ins in Excel • Competency Development • Summary • Discussion Questions • Practice Problems

Chapter 3. Identifying, Categorizing, and Presenting Healthcare Data Using Excel® • Getting Started • Identifying Your Data • Using Pivot Tables • Pivot Charts • Using Chart Types in Excel • Considerations in Using Different Chart Types • Competency Development • Summary • Discussion Questions • Practice Problems

Chapter 4. Setting Bounds for Healthcare Data and Hypothesis Testing Using Excel® • Introduction • Setting Bounds on Data • Sample and Population • Measure and Variation • Confidence Interval • Hypothesis Testing • Z-Test • Comparing Two Samples Using the Z-Test • Competency Development • Summary • Discussion Questions • Practice Problems

Chapter 5. Testing and Comparing Means of Healthcare Datasets Using Excel®t-Test • Assumptions for the t-Test • Example for t-Test • t-Test Two-Sample Mean Assuming Equal Variance • t-Test Two-Sample Mean Assuming Unequal Variance • t-Test Paired Two-Sample Mean • Competency Development • Summary • Discussion Questions • Practice Problems

Chapter 6. Checking Patterns in Healthcare Data Using Scatterplots, Correlations, and Regressions in Excel® • Exploring Relationships and Patterns • Scatterplot and Correlation • Regression • Single Linear Regression • Multiple Regression • Revisiting Missing Values • Competency Development • Summary • Discussion Questions • Practice Problems

Chapter 7. Visualization and Spatial Analysis of Healthcare Data Using 3D Maps in Excel® • Why and When to Map Data • Converting Data to Tables • Turn to 3D Maps • Steps in Visualizing 3D Maps • Working With Scenes • Including Time Element • Production of Tour • Competency Development • Summary • Discussion Questions • Practice Problems

Chapter 8. Using Analysis of Variance (ANOVA) in Healthcare Datasets to Compare Groups and Test Hypotheses in Excel® • ANOVA • Creating Categories • Stating Hypotheses • Getting Data Ready in Excel • Interpreting ANOVA Output • Competency Development • Summary • Discussion Questions • Practice Problems

Chapter 9. Text Analysis of Healthcare Data Using MeaningCloud Add-In in Excel® • Qualitative Data in Healthcare • Qualitative Analysis and Excel • MeaningCloud Add-In • Text Classification • Sentiment Analysis • Topic Extraction • Text Clustering • Competency Development • Summary • Discussion Questions • Practice Problems

Chapter 10. Sampling and Research Design Using Healthcare Data in Excel® Research Driven by Questions • Sampling • Probability Sampling • Nonprobability Sampling • Research Design • Competency Development • Summary • Discussion Questions • Practice Problems

List of Select Sources of Healthcare Data

Glossary

 

Index


About the Author:

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 and teaches several courses, including research methods, healthcare data analytics, healthcare economics, healthcare policy, and financial management. His areas of interest include program evaluation, competency-based assessment, and training. Dr. Johri is a frequent presenter on competency-based assessment at the Association of University Programs in Healthcare Administration (AUPHA) Annual Meetings and was invited by the Commission on Accreditation of Healthcare Management Education (CAHME) for a national webinar. Dr. Johri’s work experience includes program development, monitoring, and evaluation experience on maternal and child health and nutrition and prevention of mother-to-child transmission of HIV. His experience spans over 10 years with nongovernmental organizations such as CARE and EngenderHealth, Francois-Xavier Bagnoud Center at the University of Medicine and Dentistry of New Jersey as well as consulting with UNICEF. Until April 2013 he was the Impact Evaluation Advisor for USAID’s Palestinian Health Sector Reform Project. He holds a master’s degree in social work from the Tata Institute of Social Sciences, Mumbai, India, a master’s degree in public health (MPH) from Emory University, and a PhD in health policy and administration from the University of North Carolina at Chapel Hill. 


Target Audience:

This textbook is positioned as an essential part of graduate and advanced undergraduate studies in healthcare research methods and statistical analysis or related courses in healthcare administration, public health, and allied health schools and departments.

 

 
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