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    1. Medicin
    2. Andra medicinska specialiteter
    3. Odontologi

    Understanding Healthcare Delivery Science

    AvMichael Howell,Jennifer Stevens

    Häftad, Engelska, 2020

    931 kr

    Beställningsvara. Skickas inom 3-6 vardagar. Fri frakt över 249 kr.

    Beskrivning

    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.



    Produktinformation

    • Utgivningsdatum:2020-01-21
    • Mått:188 x 233 x 20 mm
    • Vikt:846 g
    • Format:Häftad
    • Språk:Engelska
    • Antal sidor:496
    • Förlag:McGraw-Hill Education
    • ISBN:9781260026481

    Utforska kategorier

    • Odontologi inom Medicin

    Innehållsförteckning

    • PART I: WHAT IS HEALTHCARE DELIVERY SCIENCE, AND WHY DO WE NEED IT?Chapter 1 IntroductionThe 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 2ComplexityWhat 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 ReferencesChapter 3Quality and Safety in HealthcareThe 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 4What 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 IMPROVEMENTChapter 5Human FactorsHuman 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 6How 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 7Leadership and Culture ChangeLeading 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 8Standard Quality Improvement Tools and TechniquesIntroduction 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 9Lean Improvement Techniques in HealthcareA Brief History of Lean The Rules of Lean A Concrete Definition of the Ideal The 8 Wastes Tools from Lean Summary References Chapter 10Partnering with Community, Professional, and Policy OrganizationsIntroduction 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 HEALTHCAREChapter 11Data in HealthcarePart 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 12Measuring Quality and SafetyQuality 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 13Overview of Analytic Techniques and Common PitfallsDinosaur 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 14Everyday AnalyticsSummarizing 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 15Survey-Based DataIntroduction 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 16Predictive Modeling 1.0 and 2.0What to Expect in This Chapter Predictive Modeling 1.0 Predictive Modeling 2.0 Taking Predictions to the Next Level References Chapter 17Predictive Modeling 3.0: Machine LearningDefinitions: 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 18What Everyone Should Know About Risk AdjustmentWhat 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 19Modeling Patient Flow: Understanding Throughput and CensusWhy Does Understanding Patient Flow Matter? Understanding Patient Flow Conceptually Analytical Approaches to Understanding Patient Flow Summary References Chapter 20Program EvaluationCausal Methods Quasi-Experimental Designs—Causal Inference in Observational Data Evaluations in the Real World References Chapter 21How to Embed Healthcare Delivery Science Into Your Health SystemIntroduction 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