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Using Predictive Analytics to Improve Healthcare Outcomes

John W. Nelson (Edited by), JW Nelson (Author), Jayne Felgen (Edited by), Mary Ann Hozak (Edited by)

9781119747758, Wiley

Hardback, published 24 August 2021

464 pages
1 x 1 x 1 cm, 0.454 kg

Using Predictive Analytics to Improve Healthcare Outcomes

Winner of the American Journal of Nursing (AJN) Informatics Book of the Year Award 2021!

Discover a comprehensive overview, from established leaders in the field, of how to use predictive analytics and other analytic methods for healthcare quality improvement.

Using Predictive Analytics to Improve Healthcare Outcomes delivers a 16-step process to use predictive analytics to improve operations in the complex industry of healthcare. The book includes numerous case studies that make use of predictive analytics and other mathematical methodologies to save money and improve patient outcomes. The book is organized as a “how-to” manual, showing how to use existing theory and tools to achieve desired positive outcomes.

You will learn how your organization can use predictive analytics to identify the most impactful operational interventions before changing operations. This includes:

  • A thorough introduction to data, caring theory, Relationship-Based Care®, the Caring Behaviors Assurance System©, and healthcare operations, including how to build a measurement model and improve organizational outcomes.
  • An exploration of analytics in action, including comprehensive case studies on patient falls, palliative care, infection reduction, reducing rates of readmission for heart failure, and more—all resulting in action plans allowing clinicians to make changes that have been proven in advance to result in positive outcomes.
  • Discussions of how to refine quality improvement initiatives, including the use of “comfort” as a construct to illustrate the importance of solid theory and good measurement in adequate pain management.
  • An examination of international organizations using analytics to improve operations within cultural context.

Using Predictive Analytics to Improve Healthcare Outcomes is perfect for executives, researchers, and quality improvement staff at healthcare organizations, as well as educators teaching mathematics, data science, or quality improvement. Employ this valuable resource that walks you through the steps of managing and optimizing outcomes in your clinical care operations.

Contributors xi

Foreword xv

Preface: Bringing the Science of Winning to Healthcare xvii

List of Acronyms xix

Acknowledgments xxv

Section One Data, Theory, Operations, and Leadership 1

1 Using Predictive Analytics to Move from Reactive to Proactive Management of Outcomes 3
John W. Nelson

2 Advancing a New Paradigm of Caring Theory 19
John W. Nelson and Jayne Felgen

3 Cultivating a Better Data Process for More Relevant Operational Insight 33
Mary Ann Hozak

4 Leadership for Improved Healthcare Outcomes 43
Linda Valentino and Mary Ann Hozak

Section Two Analytics in Action 53

5 Using Predictive Analytics to Reduce Patient Falls 55
Tara Nichols, Lance Podsiad, Josephine Sclafani Wahl, and John W. Nelson

6 Using the Profile of Caring® to Improve Safety Outcomes 67
John W. Nelson and Kenneth Oja

7 Forecasting Patient Experience: Enhanced Insight Beyond HCAHPS Scores 83
Mary Ann Hozak and John W. Nelson

8 Analyzing a Hospital-Based Palliative Care Program to Reduce Length of Stay 93
Kate Aberger, Anna Trtchounian, Inge DiPasquale, and John W. Nelson

9 Determining Profiles of Risk to Reduce Early Readmissions Due to Heart Failure 103
Mary Ann Hozak, Melissa D’Mello, and John W. Nelson

10 Measuring What Matters in a Multi-Institutional Healthcare System 125
Kay Takes, Patricia Thomas, Gay Landstrom, and John W. Nelson

11 Pause and Flow: Using Physics to Improve the Efficiency of Workflow 135
Jacklyn Whitaker, Benson Kahiu, Marissa Manhart, Mary Ann Hozak, and John W. Nelson

12 Lessons Learned While Pursuing CLABSI Reduction 153
Ana Esteban, Sebin Vadasserril, Marissa Manhart, Mary Ann Hozak, and John W. Nelson

Section Three Refining Theories to Improve Measurement 169

13 Theory and Model Development to Address Pain Relief by Improving Comfort 171
Tara Nichols and John W. Nelson

14 Theory and Model Development to Improve Recovery from Opioid Use Disorder 183
Alicia House, Kary Gillenwaters, Tara Nichols, Rebecca Smith,and John W. Nelson

Section Four International Models to Study Constructs Globally 197

15 Launching an International Trajectory of Research in Nurse Job Satisfaction, Starting in Jamaica 199
John W. Nelson and Pauline Anderson-Johnson

16 Testing an International Model of Nurse Job Satisfaction to Support the Quadruple Aim 217
John W. Nelson, Patricia Thomas, Dawna Cato, Sebahat Gözüm, Kenneth Oja, Sally Dampier, Dawna Maria Perry, Karen Poole, Alba Barros, Lidia Guandalini, Ayla Kaya, Michal Itzhaki, Irit Gantz, Theresa Williamson, and Dominika Vrbnjak

17 Developing a Customized Instrument to Measure Caring and Quality in Western Scotland 237
Theresa Williamson, Susan Smith, Jacqueline Brown, and John W. Nelson

18 Measuring the Effectiveness of a Care Delivery Model in Western Scotland 259
Theresa Williamson, Susan Smith, Jacqueline Brown, and John W. Nelson

Epilogue: Imagining What is Possible 287

Appendix 291

References 409

Index 427

Subject Areas: Mathematics [PB]
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