Clinical Analytics and Data Management for the DNP

by Martha L. Sylvia PhD, MBA, RN (Editor), Mary F. Terhaar PhD, RN, ANEF, FAAN (Editor)

Overview

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 is the only text to deliver the strong data management knowledge and skills that are required competencies for all DNP students. It enables readers to design data tracking and clinical analytics in order to rigorously evaluate clinical innovations and programs for improving clinical outcomes and to document and analyze change. This second edition has been expanded and updated to address major changes in our healthcare environment. Incorporating faculty and student input, it now includes modalities such as SPSS, Excel, and Tableau to address diverse data management tasks. Eleven new chapters cover the use of big data analytics, ongoing progress toward value-based payment, the Affordable Care Act and its future, shifting of risk and accountability to hospitals and clinicians, advancement of nursing quality indicators, and new requirements for Magnet® certification.

The text takes the DNP student step by step through the complete process of data management from planning through presentation, and encompasses the scope of skills required for students to apply relevant analytics to systematically and confidently tackle the clinical interventions data obtained as part of the DNP student project. Of particular value is a progressive case study illustrating multiple techniques and methods throughout the chapters. Sample data sets and exercises, along with objectives, references, and examples in each chapter, reinforce information.

New to the Second Edition:

• Completely updated and expanded with 11 new chapters
• Includes an extensive data management toolkit with SPSS, Excel, and Tableau
• Describes value-based purchasing and NDNQI measurement programs
• Explains use of data sources to support the problem statement for the DNP project
• Guides selection of quality measures
• Provides best practices for collecting primary and secondary data
• Offers strategic guidelines for institutional review board submission
• Explains methods for risk adjustment in program and intervention monitoring
• Explores predictive a nalytics
• Illustrates applications of big data for the DNP
• Describes Magnet requirements for measuring quality improvement

Key Features:

• Provides extensive content for rigorously evaluating DNP innovations/projects
• Takes DNP students through the complete process of data management from planning through presentation
• Includes a progressive case study illustrating multiple techniques and methods
• Offers very specific examples of application and utility of techniques
• Delivers supplemental materials, including sample data set case studies in SPSS and Excel formats, exercises, PowerPoint slides, and more

Product Details

ISBN-13:	9780826163240
Publisher:	Springer Publishing Company
Publication date:	01/18/2023
Sold by:	Barnes & Noble
Format:	eBook
Pages:	496
Sales rank:	945,903
File size:	24 MB
Note:	This product may take a few minutes to download.

About the Author

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.

Table of Contents

Contents

Contributors

Foreword

Preface

1. Introduction to Clinical Data Management

Mary F. Terhaar

2. Basic Statistical Concepts and Power Analysis

Martha L. Sylvia

3. Value-Based Purchasing

Mary F. Terhaar

4. Using Data to Support the Problem Statement

Martha L. Sylvia

5. Selecting Quality Measures

Martha L. Sylvia

6. Preparing for Data Collection

Martha L. Sylvia and Mary F. Terhaar

7. Secondary Data Collection

Emily Johnson and Martha L. Sylvia

8. Primary Data Collection

Martha L. Sylvia

9. Developing the Analysis Plan

Martha L. Sylvia and Mary F. Terhaar

10. Data Governance and Stewardship

Martha L. Sylvia and Mary F. Terhaar

11. Best Practices for Submission to the Institutional Review Board

Mary F. Terhaar and Laura A. Taylor

12. Creating the Analysis Data Set

Martha L. Sylvia

13. Exploratory Data Analysis

Martha L. Sylvia and Shannon Murphy

14. Outcomes Data Analysis

Martha L. Sylvia and Shannon Murphy

15. Summarizing the Results of the Project Evaluation

Martha L. Sylvia

16. Ongoing Monitoring

Melissa Sherry and Martha L. Sylvia

17. Data Visualization

Erik Sederstrom

18. Nursing Excellence Recognition and Benchmarking Programs

Heather Craven

19. Risk Adjustment

Martha L. Sylvia

20. Big Data, Data Science, and Analytics

Marisa L. Wilson

21. Predictive Modeling

Martha L. Sylvia

Index

Editorial Reviews

Reviewer: Michalene A King, PhD, RN, CNE (Robert Morris University)
Description: Designed to teach data management skills to DNP students, this book uses a progressive case study approach.
Purpose: The authors state that the purpose "is to describe a process and a set of strategies to be used to promote consistent, quality evaluation of the impact of translation."
Audience: The authors wrote the book for DNP students after they were unsuccessful in finding a suitable one on the subject. Both authors teach in a DNP program; one specializes in data management and the other is the director of a DNP program.
Features: This is described as a step-by-step guide for DNP students to learn analysis and management of clinical data. It covers all areas of data management. Chapter 2, on "Basic Statistical Concepts and Power Analysis," is a good review of important statistical concepts that are relevant to clinical data analysis and management.
Assessment: The authors state that they created this book to fill a specific need. 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.

Doody's Review Service