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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 Instructor’s Manual, PowerPoints, and Test Bank
Your all-in-one resource for quantitative, qualitative, and spatial analyses in Excel(R) using current real-world healthcare datasets. Health Services Research and Analytics Using Excel(R) 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, quality metrics and cultivate analytical skills that are necessary in a data-driven healthcare world. Whereas Excel is typically thought of as 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(R) software from Office365 ProPlus and newer versions, including all important "Add-ins" such as 3D Maps, Meaning Cloud, and Power Pivots among others. With numerous practice problems and over 100 step-by-step videos, Health Services Research and Analytics Using Excel(R) 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(R) and newer versions Containing over 100 step-by-step videos of Excel applications covered in the chapters and providing concise video tutorials demonstrating solutions to all end-of-chapter practice problems
“This is an outstanding book and I would highly recommend it for any professional or faculty in a current public health role, and absolutely for a student in the fields of public health, nursing, health administration, health education, medicine, and information technology (artificial intelligence)... This book provides the resources for professionals to learn and apply theory, analytics, quality, and services to understand populations with the ultimate goal of transforming U.S. health care." ---Doody's Review Service, 5 stars Population Health Management: Strategies, Tools, Applications, and Outcomes uniquely combines perspectives and concepts from community, public, and global health and aligns them with the essentials of health management. Written by leading experts in academia and industry, this text emphasizes the integration of management skills necessary to deliver quality care while producing successful outcomes sensitive to the needs of diverse populations. Designed to be both student-friendly and comprehensive, this text utilizes various models, frameworks, case examples, chapter podcasts, and more to illustrate foundational knowledge and impart the skills necessary for health care managers to succeed throughout the health care sector. The book spans core topics such as community needs assessments, social determinants of health, the role of data analytics, managerial epidemiology, value-based care payment models, and new population health delivery models. COVID-19 examples throughout chapters illustrate population health management strategies solving real-world challenges. Practical and outcomes-driven, Population Health Management prepares students in health administration and management, public health, social work, allied health, and other health professions for the challenges of an evolving health care ecosystem and the changing roles in the health management workforce. Key Features: Highlights up-to-date topics focusing on social marketing, design thinking for innovation, adopting virtual care and telehealth strategies, and social marketing ideas Introduces new population health management skills and tools such as the Social Vulnerability Index, Policy Map, PRAPARE, the PHM Framework, Design Thinking and Digital Messaging Incorporates "Did You Know?" callouts, chapter-based podcasts, and discussion questions to help explain real-world situations and examples that students and health professionals may encounter as administrators and managers Includes four full-length case studies focusing on the co-production of health, implementing a population health data analytics platform, health equity, and collaborative leadership Connects chapter objectives with the National Center for Healthcare Leadership (NCHL) and the Public Health Foundation (PHF) competencies Purchase includes digital access for use on most mobile devices or computers, as well as full suite of instructor resources with Instructor's Manual, PowerPoint slides, test bank, and sample syllabus
Thoroughly revised and updated for Excel®, this second edition of Quantitative Methods in Health Care Management offers a comprehensive introduction to quantitative methods and techniques for the student or new administrator. Its broad range of practical methods and analysis spans operational, tactical, and strategic decisions. Users will find techniques for forecasting, decision-making, facility location, facility layout, reengineering, staffing, scheduling, productivity, resource allocation, supply chain and inventory management, quality control, project management, queuing models for capacity, and simulation. The book's step-by-step approach, use of Excel, and downloadable Excel templates make the text highly practical. Praise for the Second Edition "The second edition of Dr. Ozcan's textbook is comprehensive and well-written with useful illustrative examples that give students and health care professionals a perfect toolkit for quantitative decision making in health care on the road for the twenty-first century. The text helps to explain the complex health care management problems and offer support for decision makers in this field." Marion Rauner, associate professor, School of Business, Economics, and Statistics, University of Vienna. "Quantitative Methods in Health Care Administration, Second Edition covers a broad set of necessary and important topics. It is a valuable text that is easy to teach and learn from." David Belson, professor, Department of Industrial Engineering, Viterbi School of Engineering, University of Southern California.
Analytics is one of a number of terms which are used to describe a data-driven more scientific approach to management. Ability in analytics is an essential management skill: knowledge of data and analytics helps the manager to analyze decision situations, prevent problem situations from arising, identify new opportunities, and often enables many millions of dollars to be added to the bottom line for the organization. The objective of this book is to introduce analytics from the perspective of the general manager of a corporation. Rather than examine the details or attempt an encyclopaedic review of the field, this text emphasizes the strategic role that analytics is playing in globally competitive corporations today. The chapters of this book are organized in two main parts. The first part introduces a problem area and presents some basic analytical concepts that have been successfully used to address the problem area. The objective of this material is to provide the student, the manager of the future, with a general understanding of the tools and techniques used by the analyst.
Big Data in Healthcare: Statistical Analysis of the Electronic Health Record provides the statistical tools that healthcare leaders need to organize and interpret their data. Designed for accessibility to those with a limited mathematics background, the book demonstrates how to leverage EHR data for applications as diverse as healthcare marketing, pay for performance, cost accounting, and strategic management. Topics include:* Using real-world data to compare hospitals' performance. * Measuring the prognosis of patients through massive data* Distinguishing between fake claims and true improvements* Comparing the effectiveness of different interventions using causal analysis* Benchmarking different clinicians on the same set of patients* Remove confounding in observational dataThis book can be used in introductory courses on hypothesis testing, intermediate courses on regression, and advanced courses on causal analysis. It can also be used to learn SQL language. Its extensive online instructor resources include course syllabi, PowerPoint and video lectures, Excel exercises, individual and team assignments, answers to assignments, and student-organized tutorials. Big Data in Healthcare applies the building blocks of statistical thinking to the basic challenges that healthcare leaders face every day. Prepare for those challenges with the clear understanding of your data that statistical analysis can bring--and make the best possible decisions for maximum performance in the competitive field of healthcare.
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Seamlessly integrate the Python and R programming languages with spreadsheet-based data analysis to maximize productivity Key Features Perform advanced data analysis and visualization techniques with R and Python on Excel data Use exploratory data analysis and pivot table analysis for deeper insights into your data Integrate R and Python code directly into Excel using VBA or API endpoints Purchase of the print or Kindle book includes a free PDF eBook Book Description– Extending Excel with Python and R is a game changer resource written by experts Steven Sanderson, the author of the healthyverse suite of R packages, and David Kun, co-founder of Functional Analytics. – This comprehensive guide transforms the way you work with spreadsheet-based data by integrating Python and R with Excel to automate tasks, execute statistical analysis, and create powerful visualizations. – Working through the chapters, you’ll find out how to perform exploratory data analysis, time series analysis, and even integrate APIs for maximum efficiency. – Both beginners and experts will get everything you need to unlock Excel's full potential and take your data analysis skills to the next level. – By the end of this book, you’ll be able to import data from Excel, manipulate it in R or Python, and perform the data analysis tasks in your preferred framework while pushing the results back to Excel for sharing with others as needed. What you will learn Read and write Excel files with R and Python libraries Automate Excel tasks with R and Python scripts Use R and Python to execute Excel VBA macros Format Excel sheets using R and Python packages Create graphs with ggplot2 and Matplotlib in Excel Analyze Excel data with statistical methods and time series analysis Explore various methods to call R and Python functions from Excel Who this book is for – If you’re a data analyst or data scientist, or a quants, actuaries, or data practitioner looking to enhance your Excel skills and expand your data analysis capabilities with R and Python, this book is for you. – The comprehensive approach to the topics covered makes it suitable for both beginners and intermediate learners. – A basic understanding of Excel, Python, and R is all you need to get started.
Digital Health: A Transformative Approach is designed to prepare Australia and New Zealand's future health and social care workforce for the rapidly evolving digital health landscape. It is the first local health informatics title reflecting Australasia-specific contexts and its learning objectives are aligned to National Digital Health Strategies and Frameworks. A scaffolded approach to learning, makes this text suitable for all health and social care professionals, from early learners developing skills, to those more capable who want to adapt and lead in digital health. The text is supported by online case studies that will assist development of digital professionalism and understanding requirements of digital technology across clinical, research, education and administration in diverse health and social care environments. - Information presented across four units and 12 chapters that support learning and teaching and help build learners' work readiness - Scaffolded approach across three levels of capability – empowered, transitional, and entrusted - suitable for undergraduate, postgraduate and ongoing professional development - Supported by an Elsevier Adaptive Quizzing (EAQ) to provide formative assessment across the three levels - Includes telehealth, electronic medical/health records, clinical technologies, disaster planning, interoperability and precision health care - Additional online case studies to support advanced learning.