Clinical Analytics and Data Management for the DNP 3rd Edition

Praise for the First Edition:

“DNP students may find data management challenging, particularly as their projects focus on quality improvement rather than traditional research. This book effectively addresses that gap. I highly recommend it for DNP students working on their capstone projects.”
— Doody’s Medical Reviews, Score: 98, 5 Stars

This one-of-a-kind reference is the only book that thoroughly covers the entire scope of clinical data management tailored specifically for Doctor of Nursing Practice (DNP) students. Now in its third edition, it provides a solid foundation for understanding how clinical data is collected, analyzed, and applied—critical skills for designing and completing a high-quality DNP project.

Updated to align with the 2021 AACN Essentials, this edition incorporates recent changes in national health policy, including value-based care initiatives, bundled payment models, and updates to the Affordable Care Act and CMS programs. New chapters and sample datasets in Excel and SPSS formats are included to enhance hands-on learning.

The book walks students through the entire data management process—from planning and organizing data to presenting and applying it in real-world clinical settings. It covers discipline-specific data applications, selecting the right statistical tools, and customizing methods for quality improvement initiatives. Rich in practical tools, examples, and case studies, this text is an invaluable guide for both students and faculty.

Highlights:

• Fully updated content reflecting healthcare policy shifts and current DNP education standards

• Step-by-step guidance through all phases of clinical data management

• Practical examples, downloadable datasets, and exercises using Excel and SPSS

• Covers key topics like outcomes measurement, data visualization, benchmarking, and quality improvement

• Progressive case study woven throughout to demonstrate data techniques in action

A must-have resource for DNP students aiming to master data management and lead evidence-based quality improvement in healthcare settings.