Understanding Healthcare Delivery Science / Edition 1

Understanding Healthcare Delivery Science / Edition 1

ISBN-10:
1260026485
ISBN-13:
9781260026481
Pub. Date:
12/17/2019
Publisher:
McGraw Hill LLC
ISBN-10:
1260026485
ISBN-13:
9781260026481
Pub. Date:
12/17/2019
Publisher:
McGraw Hill LLC
Understanding Healthcare Delivery Science / Edition 1

Understanding Healthcare Delivery Science / Edition 1

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Overview

An accessible new title focused on the science of healthcare delivery, from the acclaimed Understanding series

“... a landmark text that will shape the field and inform our dialog for years to come—-and it should be part of the required curriculum at medical and nursing schools around the world. Excellence in healthcare delivery science should become a core competency of the modern physician. Howell and Stevens have given medicine an important gift that may enable just that.”
- Sachin H. Jain, MD, MBA, FACP; President and CEO, CareMore and Aspire Health; Co-Founder and Co-Editor-in-Chief, Healthcare: The Journal of Delivery Science and Innovation

“You hold in your hands 35 years of investigation and learning, condensed into understandable principles and applications. It is a guidebook for effective care delivery leadership, practice, and success.”
- Brent C. James, MD, MStat, Clinical Professor, Stanford University School of Medicine

“...a must-read for anyone who, like me, is frustrated with the pace of our progress and is committed to creating a learning health system for all.”
- Lisa Simpson MB, BCh, MPH, FAAP, President and CEO, AcademyHealth

“... will quickly become the go-to, must-read resource for practitioners looking to have an impact as innovators in healthcare delivery.”
- David H. Roberts, MD, Steven P. Simcox, Patrick A. Clifford, and James H. Higby Associate Professor of Medicine, Harvard Medical School

Today’s healthcare system is profoundly complicated, but we persist in trying to roll out breakthroughs as if the healthcare system were still just the straightforward “physician’s workshop” of the early 20th century. Only rarely do we employ research-quality analytics to assess how well our care delivery innovations really work in the practice. And shockingly, the US healthcare delivery system spends only 0.1% of revenue on R&D in how we actually deliver care.

Small wonder that we find ourselves faced with the current medical paradox: Treatments that seemed miraculous at the beginning of our lifetimes are routine today, but low-quality care and medical errors harm millions of people worldwide even as spiraling healthcare costs bankrupt an unacceptable number of American families every year.

Healthcare delivery science bridges this gap between scientific research and complex, real-world healthcare delivery and operations.

With its engaging, clinically relevant style, Understanding Healthcare Delivery Science is the perfect introduction to this emerging field. This reader-friendly text pairs a thorough discussion of commonly available healthcare improvement tools and top-tier research methods with numerous case studies that put the content into a clinically relevant framework, making this text a valuable tool for administrators, researchers, and clinicians alike.





Product Details

ISBN-13: 9781260026481
Publisher: McGraw Hill LLC
Publication date: 12/17/2019
Pages: 496
Product dimensions: 7.40(w) x 9.20(h) x 0.80(d)

About the Author

Michael Howell, MD MPH is a nationally recognized expert on healthcare quality and patient safety who has served on quality- and safety-related national advisory panels for the CDC, Medicare, the National Academy of Medicine, and others. An active healthcare delivery scientist with more than 100 research articles, editorials, and book chapters, his research has been covered by The New York Times, CNN, and Consumer Reports.

Jennifer Stevens, MD directs the Center for Healthcare Delivery Science at Beth Israel Deaconess Medical Center in Boston, MA. A member of the Harvard Medical School faculty since 2015, she is actively training the next generation of healthcare delivery scientists. Dr. Stevens’ research on the opioid epidemic in ICUs, new ways to identify and mitigate patient harm in overtaxed ICUs, and other critical healthcare delivery science issues has been featured in the Washington Post, NPR, and on the front page of the Boston Globe.


Table of Contents

Contributors xiii

Preface xv

Dedication xvii

Introduction xix

Part I What Is Healthcare Delivery Science, and Why Do We Need It?

Chapter 1 Introduction 3

The Problem: How Research and Operations Are Organized in Healthcare Today 3

Historical Context: How Did It Get This Way? 4

Why Now Is Different: Two Key Changes in Context 5

Why It Matters: Problems with Thinking Too Simply About Healthcare 12

Healthcare Delivery Science 17

References 19

Chapter 2 Complexity 23

What Happens When We View Healthcare as Complicated? 23

What Is a Complex Adaptive System? 26

Why It Matters: Fitting the Right Measurement Tool to the Question 31

Healthcare Delivery Science: A Field of Research Where Healthcare Itself Is the Organism Under Study 34

References 35

Chapter 3 Quality and Safety in Healthcare 37

The Best the World Has Ever Seen 37

Three Critical Papers to Know 37

An Inflection Point: To Err Is Human and Crossing the Quality Chasm 39

More Recent Estimates About Deaths from Medical Error 41

International Comparisons 42

Have Improvement Efforts Worked? 45

How We Put It All Together 46

References 49

Chapter 4 What Does the Future Hold? 51

Introduction 51

Value Drives Change 53

The "Postsafety" Era 55

Healthcare Delivery That Delivers Health 56

Consumerism Versus Personalization 60

The Doctor Will See You Now? 62

Informed Healthcare Information Technology (IT) 64

Conclusions 66

References 68

Part II Making Change in the Real World-Tools for Healthcare Improvement

Chapter 5 Human Factors 73

Human Factors: An Introduction 74

Cognitive Reasoning, Errors, and Biases in Healthcare 77

Hierarchy: What Is It, How Do We Measure It, and Why Does It Matter? 86

Tools for Understanding Complex Systems 91

Conclusions 96

References 97

Chapter 6 How Teams Work 104

Types of Teams 105

What Do Teams Need to Succeed? 107

Poorly Functioning Teams in Healthcare 108

Teams in Aviation and the Birth of Crew Resource Management (CRM) 110

CRM in Healthcare 111

Leading Teams Through Change 112

References 114

Chapter 7 Leadership and Culture Change 117

Leading Change Is Difficult 117

Where to Start 121

What Is Implementation Science? 123

Implementation Science Frameworks 123

Integrating Implementation Science Frameworks for the Purpose of Change Management 132

References 133

Chapter 8 Standard Quality Improvement Tools and Techniques 137

Introduction 137

Preventing Adverse Events and Improving Patient Safety 137

Identifying Patient Safety Events 139

Root Cause Analysis (RCA) 142

Failure Mode Effects (and Criticality) Analysis (FMEA and FMECA) 151

Safety I and Safety II 154

Process Improvement and Quality Improvement 155

References 159

Chapter 9 Lean Improvement Techniques in Healthcare 162

A Brief History of Lean 163

The Rules of Lean 165

A Concrete Definition of the Ideal 166

The 8 Wastes 167

Tools from Lean 170

Summary 175

References 176

Chapter 10 Partnering with Community, Professional, and Policy Organizations 178

Introduction 178

How Health Is Created 179

Key Stakeholders in Shaping Health 181

Engaging with Local Public Health Agencies 186

Approaches to Successful Partnerships 194

Concluding Thoughts 195

Acknowledgments 196

References 196

Part III Seeing the Truth-Analytics in Healthcare

Chapter 11 Data in Healthcare 203

Part 1 Fundamental Issues in Healthcare Data 203

Part 2 The Importance of Understanding Data Lineage, and How This Leads Mature Organizations to Both Informal and Formal Data Governance 206

Part 3 Basic Understanding of Relational Database Structures 211

Part 4 Review of Common Approaches to Actually Accessing Healthcare Data 212

Conclusion 214

References 214

Chapter 12 Measuring Quality and Safety 216

Quality Measurement Frameworks 216

What Are You Trying to Achieve? Improvement, Comparison, or Accountability 221

What Makes a Good Measure? 222

Challenges 223

Common Measure Sets and Major Pay-For-Performance Programs 225

References 230

Chapter 13 Overview of Analytic Techniques and Common Pitfalls 233

Dinosaur Footprints and What They Tell Us About Data Analysis in Healthcare 233

The Four Horsemen of Mistaken Conclusions 235

The Critical Importance of Missing Data 243

The Shape of Data: Categories of Data and Why They Matter 245

Overview of Analytic Methods 251

References 254

Chapter 14 Everyday Analytics 256

Summarizing Your Data 257

Displaying Data 261

Outcomes Over Time, Part I - Run Charts 268

How to Tell if Two Groups Are Different: Univariable Tests of Difference and Measures of Comparison 270

Outcomes Over Time, Part 2-Statistical Process Control (SPC) Charts 279

Everyday Analytics 282

References 288

Chapter 15 Survey-Based Data 289

Introduction 289

Perhaps the Most Important Thing You'll Learn in This Chapter 289

What Are Some of the Main Purposes of Surveys? 290

Overview of Conducting a Survey 293

Some Pitfalls 303

References 308

Chapter 16 Predictive Modeling 1.0 and 2.0 312

What to Expect in This Chapter 312

Predictive Modeling 1.0 313

Predictive Modeling 2.0 333

Taking Predictions to the Next Level 338

References 339

Chapter 17 Predictive Modeling 3.0: Machine Learning 341

Definitions: What Is Artificial Intelligence? Machine Learning? 341

A Brief History of Artificial Intelligence 344

Translating Epidemiology to Machine Learning 346

Categories of Machine Learning Used in Healthcare 347

Pitfalls in Using Machine Learning in Healthcare 369

The Future 372

References 373

Chapter 18 What Everyone Should Know About Risk Adjustment 377

What Is Risk Adjustment and Why We Should Care? 377

What Risk Adjustments Are Available, and How Should We Assess Them? 381

Examples of Risk Adjustment Gone Awry 384

Using Risk Adjustment in Local Healthcare Delivery Science 385

References 387

Chapter 19 Modeling Patient Flow: Understanding Throughput and Census 390

Why Does Understanding Patient Flow Matter? 391

Understanding Patient Flow Conceptually 393

Analytical Approaches to Understanding Patient Flow 397

Summary 412

References 413

Chapter 20 Program Evaluation 416

Causal Methods 417

Quasi-Experimental Designs-Causal Inference in Observational Data 422

Evaluations in the Real World 430

References 431

Chapter 21 How to Embed Healthcare Delivery Science Into Your Health System 434

Introduction 434

How Do I Join (or Build) a Community of Healthcare Delivery Science? 434

How to Embed Healthcare Delivery Science in Your Health System 439

Summary 444

Reference 445

Index 447

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