Using Predictive Analytics to Improve Healthcare Outcomes

✍ Scribed by John W. Nelson

• Publisher: Wiley
• Year: 2021
• Tongue: English
• Leaves: 467
• Edition: 1
• Category: Library

✦ Synopsis

Using Predictive Analytics to Improve Healthcare Outcomes

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.

✦ Table of Contents

Cover
Title Page
Copyright Page
Contents
Contributors
Foreword
Preface: Bringing the Science of Winning to Healthcare
List of Acronyms
Acknowledgments
Section One Data, Theory, Operations, and Leadership
Chapter 1 Using Predictive Analytics to Move from Reactive to Proactive Management of Outcomes
The Art and Science of Making Data Accessible
Summary 1: The “Why”
Summary 2: The Even Bigger “Why”
Implications for the Future
Chapter 2 Advancing a New Paradigm of Caring Theory
Maturation of a Discipline
Theory
Frameworks of Care
RBC’s Four Decades of Wisdom
Summary
Chapter 3 Cultivating a Better Data Process for More Relevant Operational Insight
Taking on the Challenge
“PSI RNs”: A Significant Structural Change to Support Performance and Safety Improvement Initiatives and Gain More Operational Insight
The Importance of Interdisciplinary Collaboration in Data Analysis
Key Success Factors
Summary
Chapter 4 Leadership for Improved Healthcare Outcomes
Data as a Tool to Make the Invisible Visible
Leaders Using Data for Inspiration: Story 1
Leaders Using Data for Inspiration: Story 2
How Leaders Can Advance the Use of Predictive Analytics and Machine Learning
Understanding an Organization’s “Personality” Through Data Analysis
Section Two Analytics in Action
Chapter 5 Using Predictive Analytics toReduce Patient Falls
Predictors of Falls, Specified in Model 1
Lessons Learned from This Study
Respecifying the Model
Summary
Chapter 6 Using the Profile of Caring® to Improve Safety Outcomes
The Profile of Caring
Machine Learning
Exploration of Two Variables of Interest: Early Readmission for Heart Failure and Falls
Proposal for a Machine Learning Problem
Constructing the Study for Our Machine Learning Problem
Chapter 7 Forecasting Patient Experience: Enhanced Insight Beyond HCAHPS Scores
Methods to Measure the Patient Experience
Results of the First Factor Analysis
Implications of This Factor Analysis
Predictors of Patient Experience
Discussion
Transforming Data into Action Plans
Summary
Chapter 8 Analyzing a Hospital-Based Palliative Care Program to Reduce Length of Stay
Building a Program for Palliative Care
The Context for Implementing a Program of Palliative Care
Building a Model to Study Length of Stay in Palliative Care
Demographics of the Patient Population for Model 1
Results from Model 1
Respecifying the Model
Discussion
Chapter 9 Determining Profiles of Risk to Reduce Early Readmissions Due to Heart Failure
Step 1: Seek Established Guidelines in the Literature
Step 2: Crosswalk Literature with Organization’s Tool
Step 3: Develop a Structural Model of the 184 Identified Variables
Step 4: Collect Data
Details of the Study
Limitations of the Study
Results: Predictors of Readmission in Fewer Than 30 Days
Next Steps
Chapter 10 Measuring What Matters in a Multi-Institutional Healthcare System
Testing a Model of Caring
Further Discussion
Summary
Chapter 11 Pause and Flow: Using Physics to Improve the Efficiency of Workflow
Types of Pause
Types of Flow
Methods
Sample Size and Response Rates
What We Learned About Pause
What We Learned About Flow
Application of Results to Operations
Reflections from the Medical Unit—R6S
Analyzing Pause and Flow of Work as a Method of Quality Improvement
Summary and Next Steps
Chapter 12 Lessons Learned While Pursuing CLABSI Reduction
Development of a Specified Model of Measurement for Prevention of CLABSI
First Lesson Learned: Quality Data Collection Requires Well-Trained Data Collectors
Other Lessons Learned
Summary and Next Steps
Section Three Refining Theories to Improve Measurement
Chapter 13 Theory and Model Development to Address Pain Relief by Improving Comfor
t
A New Theory
Developing a New Model Based on a New Theory
Clinicians’ Beliefs Drive Their Practice
Dimensions of Comfort
Predictors of Comfort
The Model
Summary
Chapter 14 Theory and Model Development to Improve Recovery from Opioid Use Disorder
The Current Costs of Opioid Use Disorder (OUD)
Interventions for OUD
Pain Management, OUD, and Therapeutic Relationships
Interventions Which Include Potential Trusted Others
Existing OUD Measurement Instruments
Updating the Old OUD Measurement Instrument and Model to Include the Trusted Other
Discussion
Conclusion
Section Four International Models to Study Constructs Globally
Chapter 15 Launching an International Trajectory of Research in Nurse Job Satisfaction, Starting in Jamaica
Background
The Hunch: Where Measurement Begins
The Model
Understanding the Context of Jamaica
Methods to Study Job Satisfaction and Clarity in Jamaica
Managing Disappointment with the Low Response Rate
Results on the Social and Technical Dimensions of Nurse Job Satisfaction in Jamaica
Results on the Relationship of Role Clarity and Demographics to Nurse Job Satisfaction in Jamaica
Application of the Findings
Chapter 16 Testing an International Model of Nurse Job Satisfaction to Support the Quadruple Aim
The Four Goals of Our Study
Methods
Theoretical Framework
Measurement Instruments and a Model of Measurement
Order of Operations of the Study
Simplifying the Model
Respecifying the Model to Include Caring
Results from Model 2
How Job Satisfaction Relates to Turnover and Sick Time
Recommendations Based on Findings
Chapter 17 Developing a Customized Instrument to Measure Caring and Quality in Western Scotland
Developing an Instrument to Measure Caring as Perceived by the Patient
Results
Discussion
Chapter 18 Measuring the Effectiveness of a Care Delivery Model in Western Scotland
The Caring Behaviors Assurance System (CBAS)
Implementation of CBAS
Measurement of CBAS
Findings from the PCQI, the Operations of CBAS Assessment, and the HES
Action Planning
Discussion
Epilogue: Imagining What Is Possible
Appendix A Worksheets Showing the Progression from a Full List of Predictor Variables to a Measurement Model
Appendix B The Key to Making Your Relationship-Based Care® Implementation Sustainable Is “I2E2”
Appendix C Calculation for Cost of Falls
Appendix D Possible Clinical, Administrative, and Psychosocial Predictors of Readmission for Heart Failure in Fewer Than 30 Days After Discharge
Appendix E Process to Determine Variables for Lee, Jin, Piao, & Lee, 2016 Study
Appendix F Summary of National and International Heart Failure Guidelines
National Institute for Health and Care Excellence (NICE) Guidelines
European Society of Cardiology (ESC), Acute and Chronic Heart Failure Guidelines
American College of Cardiology Foundation (ACCF)/American Heart Association (AHA), 2013 and 2017 Guidelines for Management of Heart Failure
Appendix GCrosswalk Hospital Tool and Guidelines
Appendix H Comprehensive Model of 184 Variables Found in Guidelines and Hospital Tool
Appendix I Summary of Variables That Proved Insignificant After Analysis
Appendix J Summary of Inconclusive Findings
Appendix K Nine Tools for Measuring the Provision of Quality Patient Care and Related Variables
Three Tools for Assessing “Caring for the Patient” As Perceived By the Patient
Three Tools for Assessing “Caring for the Patient” as Perceived By Staff Members
Tools to Measure Self-Care; Nurse Job Satisfaction; and Clarity of Self, Role, and System
Appendix L Data From Pause and Flow Study Related to Participants’ Ability to Recall Moments of Pause and Flow Easily or with Reflection
Appendix M Identified Pauses and Proposed Interventions Resulting from a Pause and Flow Study
Appendix N Factors Related to a Focus on Pain Versus Factors Related to a Focus on Comfort
Appendix O Comfort/Pain Perception Survey(CPPS)—Patient Version
Appendix P Comfort/Pain Perception Survey (CPPS)—Care Provider Version
Appendix Q Predictors of OUD
Appendix R Personal Qualities of Clinicians and Others Suited to Become Trusted Others
Modeling “Not Knowing”
Cultivating Self-Awareness
Commitment to Perspective-Seeking
Appendix S Qualities of Systems and Organizations Suited to Serve People Recovering from OUD
Advancing a Culture in Which “Not Knowing” Is Accepted
Advancing a Culture in Which Systemic Awareness Is Actively Sought
Advancing a Culture in Which Perspective Seeking Is Prized
Appendix T Factor Loadings for Satisfaction with Staffing/Scheduling and Resources
Appendix U Detail Regarding Item Reduction of Instruments to Measure Caring
Appendix V Factor Loading for Items in the Healing Compassions Assessment (HCA) for Use in Western Scotland
Appendix W Factor Loadings of the Caring Professional Scale for Use in Western Scotland
Appendix X Factor Loadings for the Healing Compassion Survey—7Cs NHS Scotland (Staff Version)
Appendix Y Factor Analysis and Factor Ranking for Survey Items Related to Caring for Self and Caring of the Senior Charge Nurse
Appendix Z Demographics, Particularly Ward, as Predictors of Job Satisfaction
Appendix AA Demographic as Predictors of clarity
Appendix BB Correlates of Operations of CBAS with Items from the Healing Compassion Survey—7 Cs NHS Scotland (Staff Version)
References
Index
EULA