Michael Howell, Jennifer P Stevens

Understanding Healthcare Delivery Science

• Broschiertes Buch

Produktbeschreibung

An accessible new title focused on the science of healthcare delivery, from the acclaimed Understanding series A Doody's Core Title for 2024! "... 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.

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Produktdetails

• Verlag: McGraw Hill LLC
• Seitenzahl: 496
• Erscheinungstermin: 17. Dezember 2019
• Englisch
• Abmessung: 233mm x 187mm x 25mm
• Gewicht: 894g
• ISBN-13: 9781260026481
• ISBN-10: 1260026485
• Artikelnr.: 56035062

Autorenporträt

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.

Inhaltsangabe

PART I: WHAT IS HEALTHCARE DELIVERY SCIENCE, AND WHY DO WE NEED IT?
Chapter 1 Introduction The Problem: How Research and Operations Are
Organized in Healthcare Today Historical Context: How Did It Get This Way?
Why Now Is Different: Two Key Changes in Context Why It Matters: Problems
with Thinking Too Simply About Healthcare Healthcare Delivery Science
References
Chapter 2 Complexity What Happens When We View Healthcare as Complicated?
What Is a Complex Adaptive System? Why It Matters: Fitting the Right
Measurement Tool to the Question Healthcare Delivery Science: A Field of
Research Where Healthcare Itself Is the Organism Under Study References
Chapter 3 Quality and Safety in Healthcare The Best the World Has Ever Seen
Three Critical Papers to Know An Inflection Point: To Err Is Human and
Crossing the Quality Chasm More Recent Estimates About Deaths from Medical
Error International Comparisons Have Improvement Efforts Worked? How We Put
It All Together References
Chapter 4 What Does the Future Hold? Introduction Value Drives Change The
"Postsafety" Era Healthcare Delivery That Delivers Health Consumerism
Versus Personalization The Doctor Will See You Now? Informed Healthcare
Information Technology (IT) Conclusions References
PART II: MAKING CHANGE IN THE REAL WORLD-TOOLS FOR HEALTHCARE IMPROVEMENT
Chapter 5 Human Factors Human Factors: An Introduction Cognitive Reasoning,
Errors, and Biases in Healthcare Hierarchy: What Is It, How Do We Measure
It, and Why Does It Matter? Tools for Understanding Complex Systems
Conclusions References
Chapter 6 How Teams Work Types of Teams What Do Teams Need to Succeed?
Poorly Functioning Teams in Healthcare Teams in Aviation and the Birth of
Crew Resource Management (CRM) CRM in Healthcare Leading Teams Through
Change References
Chapter 7 Leadership and Culture Change Leading Change Is Difficult Where
to Start What Is Implementation Science? Implementation Science Frameworks
Integrating Implementation Science Frameworks for the Purpose of Change
Management References
Chapter 8 Standard Quality Improvement Tools and Techniques Introduction
Preventing Adverse Events and Improving Patient Safety Identifying Patient
Safety Events Root Cause Analysis (RCA) Failure Mode Effects (and
Criticality) Analysis (FMEA and FMECA) Safety I and Safety II Process
Improvement and Quality Improvement References
Chapter 9 Lean Improvement Techniques in Healthcare A Brief History of Lean
The Rules of Lean A Concrete Definition of the Ideal The 8 Wastes Tools
from Lean Summary References
Chapter 10 Partnering with Community, Professional, and Policy
Organizations Introduction How Health Is Created Key Stakeholders in
Shaping Health Engaging with Local Public Health Agencies Approaches to
Successful Partnerships Concluding Thoughts Acknowledgments References
PART III: SEEING THE TRUTH-ANALYTICS IN HEALTHCARE
Chapter 11 Data in Healthcare Part 1: Fundamental Issues in Healthcare Data
Part 2: The Importance of Understanding Data Lineage, and How This Leads
Mature Organizations to Both Informal and Formal Data Governance Part 3:
Basic Understanding of Relational Database Structures Part 4: Review of
Common Approaches to Actually Accessing Healthcare Data Conclusion
References
Chapter 12 Measuring Quality and Safety Quality Measurement Frameworks What
Are You Trying to Achieve? Improvement, Comparison, or Accountability What
Makes a Good Measure? Challenges Common Measure Sets and Major
Pay-For-Performance Programs References
Chapter 13 Overview of Analytic Techniques and Common Pitfalls Dinosaur
Footprints and What They Tell Us About Data Analysis in Healthcare The Four
Horsemen of Mistaken Conclusions The Critical Importance of Missing Data
The Shape of Data: Categories of Data and Why They Matter Overview of
Analytic Methods References
Chapter 14 Everyday Analytics Summarizing Your Data Displaying Data
Outcomes Over Time, Part I - Run Charts How to Tell if Two Groups Are
Different: Univariable Tests of Difference and Measures of Comparison
Outcomes Over Time, Part 2-Statistical Process Control (SPC) Charts
Everyday Analytics References
Chapter 15 Survey-Based Data Introduction Perhaps the Most Important Thing
You'll Learn in This Chapter What Are Some of the Main Purposes of Surveys?
Overview of Conducting a Survey Some Pitfalls References
Chapter 16 Predictive Modeling 1.0 and 2.0 What to Expect in This Chapter
Predictive Modeling 1.0 Predictive Modeling 2.0 Taking Predictions to the
Next Level References
Chapter 17 Predictive Modeling 3.0: Machine Learning Definitions: What Is
Artificial Intelligence? Machine Learning? A Brief History of Artificial
Intelligence Translating Epidemiology to Machine Learning Categories of
Machine Learning Used in Healthcare Pitfalls in Using Machine Learning in
Healthcare The Future References
Chapter 18 What Everyone Should Know About Risk Adjustment What Is Risk
Adjustment, and Why We Should Care? What Risk Adjustments Are Available,
and How Should We Assess Them? Examples of Risk Adjustment Gone Awry Using
Risk Adjustment in Local Healthcare Delivery Science References
Chapter 19 Modeling Patient Flow: Understanding Throughput and Census Why
Does Understanding Patient Flow Matter? Understanding Patient Flow
Conceptually Analytical Approaches to Understanding Patient Flow Summary
References
Chapter 20 Program Evaluation Causal Methods Quasi-Experimental
Designs-Causal Inference in Observational Data Evaluations in the Real
World References
Chapter 21 How to Embed Healthcare Delivery Science Into Your Health System
Introduction How Do I Join (or Build) a Community of Healthcare Delivery
Science? How to Embed Healthcare Delivery Science in Your Health System
Summary Reference
Index