Praise for the first edition:

"DNP students may struggle with data management, since their projects are not research but quality improvement, and this book covers the subject well. I recommend it for DNP students for use during their capstone projects." Score: 98, 5 Stars

-- Doody's Medical Reviews

This unique text and reference—the only book to address the full spectrum of clinical data management for the DNP student—instills a fundamental understanding of how clinical data is gathered, used, and analyzed, and how to incorporate this data into a quality DNP project. The new third edition is updated to reflect changes in national health policy such as quality measurements, bundled payments for specialty care, and Advances to the Affordable Care Act (ACA) and evolving programs through the Centers for Medicare and Medicaid Services (CMS). The third edition reflects the revision of 2021 AACN Essentials and provides data sets and other examples in Excel and SPSS format, along with several new chapters.

This resource takes the DNP student step-by-step through the complete process of data management, from planning through presentation, clinical applications of data management that are discipline-specific, and customization of statistical techniques to address clinical data management goals. Chapters are brimming with descriptions, resources, and exemplars that are helpful to both faculty and students. Topics spotlight requisite competencies for DNP clinicians and leaders such as phases of clinical data management, statistics and analytics, assessment of clinical and economic outcomes, value-based care, quality improvement, benchmarking, and data visualization. A progressive case study highlights multiple techniques and methods throughout the text. Purchase includes online access via most mobile devices or computers.

New to the Third Edition:

New Chapter: Using EMR Data for the DNP Project
New chapter solidifies link between EBP and Analytics for the DNP project
New chapter highlights use of workflow mapping to transition between current and future state, while simultaneously visualizing process measures needed to ensure success of the DNP project
Includes more examples to provide practical application exercises for students

Key Features:

Disseminates robust strategies for using available data from everyday practice to support trustworthy evaluation of outcomes
Uses multiple tools to meet data management objectives [SPSS, Excel®, Tableau]
Presents case studies to illustrate multiple techniques and methods throughout chapters
Includes specific examples of the application and utility of these techniques using software that is familiar to graduate nursing students
Offers real world examples of completed DNP projects
Provides Instructor’s Manual, PowerPoint slides, data sets in SPSS and Excel, and forms for completion of data management and evaluation plan

Contents

Contributors

Foreword for the Third Edition

Preface

Instructor Resources

PART I: INTRODUCTION

Chapter 1. Introduction to Clinical Data Management

Chapter 2. Analytics and Evidence-Based Practice

PART II: DATA PLANNING AND PREPARATION

Chapter 3. Using Data to Support the Problem Statement

Chapter 4. Preparing for Data Collection

Chapter 5. Secondary Data Collection

Chapter 6. Primary Data Collection

Chapter 7. Using EHR Data for the DNP Project

PART III: PREPARING FOR PROJECT IMPLEMENTATION

Chapter 8. Determining the Project Measures

Chapter 9. Using Statistical Techniques to Plan the DNP Project

Chapter 10. Using Workflow Mapping to Plan the DNP Project Implementation

Chapter 11. Developing the Analysis Plan

Chapter 12. Best Practices for Submission to the Institutional Review Board

PART IV: IMPLEMENTING AND EVALUATING PROJECT RESULTS

Chapter 13. Creating the Analysis Data Set

Chapter 14. Exploratory Data Analysis

Chapter 15. Outcomes Data Analysis

Chapter 16. Summarizing the Results of the Project

Chapter 17. Ongoing Monitoring

PART V: KEY COMPETENCIES FOR DNP PRACTICE

Chapter 18. Data Governance and Stewardship

Chapter 19. Value-Based Care

Chapter 20. Nursing Excellence Recognition and Benchmark Programs

PART VI: ADVANCED ANALYTIC TECHNIQUES

Chapter 21. Data Visualization

Chapter 22. Risk Adjustment

Chapter 23. Big Data, Data Science, and Analytics

Chapter 24. Predictive Modeling

Index

Authors

Martha L. Sylvia, PhD, MBA, RN, is Associate Professor at Medical University of South Carolina College of Nursing, where she provides consultation on DNP curriculum and teaches in the DNP Program. Dr. Sylvia has many years of experience in population health management with a focus on the analytic infrastructure to support the spectrum of popula- tion health management (PHM) initiatives. She is the owner and president of ForestVue Healthcare Solutions, a Clinical Analytics Consulting Company. Dr. Sylvia previously served as the director of Population Health Analytics at Johns Hopkins Healthcare and the Medical University of South Carolina (MUSC), where she designed and implemented population health analytics strategies.

Mary F. Terhaar, PhD, RN, ANEF, FAAN, is Associate Dean for Graduate Programs at the Fitzpatrick College of Nursing at Villanova University. She is a respected leader in translation, education, and team collaboration. Across 40 years of leadership spanning diverse systems, roles, and clinical services; she has framed problems as challenges, built high-functioning teams with diverse talents, and led development and execution of replicable solutions. Dr. Terhaar has authored or co-authored more than 70 manuscripts and chapters, as well as two broadly adopted texts on translation, evaluation, and DNP education. She is sought as a consultant on curriculum design and continuous improvement in nursing education and provides support to programs working to deliver high impact, rigorous education. She is an active site visitor and team leader for the Commission on Collegiate Nursing Education. Dr. Terhaar has advanced DNP education by creating processes, curricula, and resources which guide faculty and students across the nation and in five countries to produce outcomes. The pioneering work of teams she has led provides guidance for IRB submission, scholarly writing, data management, translation, multiple significant practice challenges, and now entry and success in doctoral education for nurses on the rise. All are increasingly included in curricula which prepare graduates to meet the Quadruple Aim. Dr. Terhaar has led a series of programs to increase diversity in the workforce by increasing diversity in graduate and undergraduate education. Most recently, she developed and lead an innovative program to increase diversity and belonging among undergraduate nursing students in collaboration with the Independence Blue Cross Foundation, and North Philadelphia high schools. Dr. Terhaar is co-founder of an innovative program that helps prospective students remove barriers to entering doctoral study, which has increased successful applications across diverse groups of nurses. She also developed a post-doctoral program for DNPs which increased dissemination, socialization, collaboration, and impact. She has helped to increase the caliber and rigor of scholarship produced by DNPs, appropriate submissions to IRBs, reliability of data and means testing, successful publications, and outcomes from DNP projects.

Instructors

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