Apply engineering and design principles to revitalize the healthcare delivery system Healthcare Systems Engineering is the first engineering book to cover this emerging field, offering comprehensive coverage of the healthcare system, healthcare delivery, and healthcare systems modeling. Written by leading industrial engineering authorities and a medical doctor specializing in healthcare delivery systems, this book provides a well-rounded resource for readers of a variety of backgrounds. Examples, case studies, and thoughtful learning activities are used to thoroughly explain the concepts…mehr
Apply engineering and design principles to revitalize the healthcare delivery system Healthcare Systems Engineering is the first engineering book to cover this emerging field, offering comprehensive coverage of the healthcare system, healthcare delivery, and healthcare systems modeling. Written by leading industrial engineering authorities and a medical doctor specializing in healthcare delivery systems, this book provides a well-rounded resource for readers of a variety of backgrounds. Examples, case studies, and thoughtful learning activities are used to thoroughly explain the concepts presented, including healthcare systems, delivery, quantification, and design. You'll learn how to approach the healthcare industry as a complex system, and apply relevant design and engineering principles and processes to advance improvements. Written with an eye toward practicality, this book is designed to maximize your understanding and help you quickly apply toward solutions for a variety of healthcare challenges. Healthcare systems engineering is a new and complex interdisciplinary field that has emerged to address the myriad challenges facing the healthcare industry in the wake of reform. This book functions as both an introduction and a reference, giving you the knowledge you need to move toward better healthcare delivery. * Understand the healthcare delivery context * Use appropriate statistical and quantitative models * Improve existing systems and design new ones * Apply systems engineering to a variety of healthcare contexts Healthcare systems engineering overlaps with industrial engineering, operations research, and management science, uniting the principles and practices of these fields together in pursuit of optimal healthcare operations. Although collaboration is focused on practitioners, professionals in information technology, policy and administration, public health, and law all play crucial roles in revamping health care systems. Healthcare Systems Engineering is a complete and authoritative reference for stakeholders in any field.Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.
PAUL M. GRIFFIN, PHD, is the Joseph C. Mello Chair and Professor of Industrial Engineering at Georgia Tech. HARRIET B. NEMBHARD, PHD, Is a Professor of Industrial Engineering at Pennsylvania State University. She is Director of the Center for Integrated Healthcare Delivery Systems. CHRISTOPHER J. DEFLITCH, MD, is the Chief Medical Information Officer and an Associate Professor of Emergency Medicine at the Pennsylvania State University Hershey Medical Center. NATHANIEL D. BASTIAN, PHD, is a Healthcare Operations Research Analyst in the United States Army Medical Department. HYOJUNG KANG, PHD, is a Research Assistant Professor of Systems and Information Engineering at the University of Virginia. DAVID A. MUÑOZ, PHD, is a consultant at McKinsey & Company.
Inhaltsangabe
Acknowledgments xi Chapter 1 The Healthcare Delivery System 1 Overview 1 1.1 Healthcare Delivery Components 2 1.2 Major Stakeholders 6 1.3 Global Issues in Health 6 1.4 Drivers for Healthcare Systems 13 Questions and Learning Activities 22 References 23 Chapter 2 Complexity and Systems in Healthcare 25 Overview 25 2.1 Taking a Systems Approach to Healthcare 25 2.2 Complex Adaptive Systems 28 Case Study 2A: Complexity in Chronic Kidney Disease 31 2.3 Systems Thinking and System Dynamics 34 Case Study 2B: Systems Thinking and Causal Loop Diagrams in CKD 40 Case Study 2C: System Dynamics and Stock Flow Diagrams in CKD 45 Questions and Learning Activities 48 References 49 Chapter 3 Patient Flow 53 Overview 53 3.1 Healthcare Settings and Clinical Workflows 53 3.2 Patient Flow through a Hospital 64 3.3 Care Transitions 71 3.4 Process Mapping 75 3.5 Queuing 78 Case Study 3: ED Crowding - A Patient Flow Solution 80 Questions and Learning Activities 83 References 83 Chapter 4 Healthcare Financing 91 Overview 91 4.1 Financing Models for Health Services 91 4.2 Compensation Models for Providers 95 4.3 Cost Allocation and Charges 97 4.4 Capital Budgeting 103 Questions and Learning Activities 107 References 108 Chapter 5 Health Data and Informatics 111 Overview 111 5.1 Healthcare Data 116 5.2 Electronic Health Records 121 5.3 Health Information Exchange 130 5.4 Publicly Reported Healthcare Data 132 Case Study 5: Health Informatics at a Hospital-A 10-Year Journey 136 Questions and Learning Activities 139 References 140 Chapter 6 Lean 141 Overview 141 6.1 Lean Philosophy and Methods 141 6.2 Drivers for Lean Healthcare Systems 143 6.3 A Toolset for Eliminating Wastes 146 6.4 Value Stream Mapping 148 6.5 A3 150 6.6 5S 157 6.7 Kanban 160 6.8 Lean Implementations 164 6.9 Lean Thinking 165 Questions and Learning Activities 166 References 166 Chapter 7 Six Sigma 169 Overview 169 7.1 Six Sigma Philosophy 169 7.2 Six Sigma Quality 170 Case Study 7A: Quantifying Complexity in Translational Research 201 Case Study 7B: Evaluating Collaboration in Translational Research 205 Case Study 7C: Resource Allocation in Translational Research 208 Questions and Learning Activities 210 References 212 Chapter 8 Reliability and Patient Safety 217 Overview 217 8.1 Human Reliability 217 8.2 Errors in Healthcare 218 8.3 Medication Errors 220 8.4 Patient Falls 222 8.5 Human Factors and Ergonomics for Patient Safety 227 Questions and Learning Activities 236 References 237 Chapter 9 Health Analytics 245 Overview 245 9.1 Data Mining 245 Case Study 9A: Predicting Parkinson's Disease Using Data Mining 251 9.2 Data Visualization 255 Case Study 9B: Data Visualization in Obesity Counseling 269 9.3 Social Network Analysis 271 Case Study 9C: SNA in a Pediatric Intensive Care Unit (PICU) 277 9.4 Data Envelopment Analysis 280 Case Study 9D: Using DEA for Finding Best-in-Class Hospitals in a Network 285 9.5 Multicriteria Decision Making 287 Case Study 9E: Use of GP to Optimize Helicopter Emplacement at Medical Treatment Facilities 291 Questions and Learning Activities 292 References 293 Chapter 10 Capacity Management 297 Overview 297 10.1 Capacity Management Challenges 297 10.2 Managing Nursing Units 299 10.3 Managing Operating Rooms 310 10.4 Managing Diagnostic Units 316 10.5 Nurse Staffing and Scheduling 317 Questions and Learning Activities 320 References 321 Chapter 11 Healthcare Logistics 323 Overview 323 11.1 Facility Location 323 Case Study 11: Location of Federally Qualified Healthcare Centers 337 11.2 Home Healthcare Routing and Scheduling 341 Questions and Learning Activities 347 References 349 Chapter 12 Health Supply Chains 351 Overview 351 12.1 Forecasting Demand 351 12.2 Inventory Control 357 12.3 Healthcare Distribution 363 12.4 Coordinating Activities in the Supply Chain 369 Questions and Learning Activities 375 References 377 Chapter 13 Infection Control 379 Overview 379 13.1 Historical Perspective 379 13.2 Infection Control Classification 381 13.3 Checklists for Infection Control 383 13.4 The Case of Sepsis 385 13.5 Mathematical Modeling of Hospital Infection Control 388 Case Study 13: Impact of Interventions on TB Infection in a Clinic 398 Questions and Learning Activities 402 References 403 Index 405
Acknowledgments xi Chapter 1 The Healthcare Delivery System 1 Overview 1 1.1 Healthcare Delivery Components 2 1.2 Major Stakeholders 6 1.3 Global Issues in Health 6 1.4 Drivers for Healthcare Systems 13 Questions and Learning Activities 22 References 23 Chapter 2 Complexity and Systems in Healthcare 25 Overview 25 2.1 Taking a Systems Approach to Healthcare 25 2.2 Complex Adaptive Systems 28 Case Study 2A: Complexity in Chronic Kidney Disease 31 2.3 Systems Thinking and System Dynamics 34 Case Study 2B: Systems Thinking and Causal Loop Diagrams in CKD 40 Case Study 2C: System Dynamics and Stock Flow Diagrams in CKD 45 Questions and Learning Activities 48 References 49 Chapter 3 Patient Flow 53 Overview 53 3.1 Healthcare Settings and Clinical Workflows 53 3.2 Patient Flow through a Hospital 64 3.3 Care Transitions 71 3.4 Process Mapping 75 3.5 Queuing 78 Case Study 3: ED Crowding - A Patient Flow Solution 80 Questions and Learning Activities 83 References 83 Chapter 4 Healthcare Financing 91 Overview 91 4.1 Financing Models for Health Services 91 4.2 Compensation Models for Providers 95 4.3 Cost Allocation and Charges 97 4.4 Capital Budgeting 103 Questions and Learning Activities 107 References 108 Chapter 5 Health Data and Informatics 111 Overview 111 5.1 Healthcare Data 116 5.2 Electronic Health Records 121 5.3 Health Information Exchange 130 5.4 Publicly Reported Healthcare Data 132 Case Study 5: Health Informatics at a Hospital-A 10-Year Journey 136 Questions and Learning Activities 139 References 140 Chapter 6 Lean 141 Overview 141 6.1 Lean Philosophy and Methods 141 6.2 Drivers for Lean Healthcare Systems 143 6.3 A Toolset for Eliminating Wastes 146 6.4 Value Stream Mapping 148 6.5 A3 150 6.6 5S 157 6.7 Kanban 160 6.8 Lean Implementations 164 6.9 Lean Thinking 165 Questions and Learning Activities 166 References 166 Chapter 7 Six Sigma 169 Overview 169 7.1 Six Sigma Philosophy 169 7.2 Six Sigma Quality 170 Case Study 7A: Quantifying Complexity in Translational Research 201 Case Study 7B: Evaluating Collaboration in Translational Research 205 Case Study 7C: Resource Allocation in Translational Research 208 Questions and Learning Activities 210 References 212 Chapter 8 Reliability and Patient Safety 217 Overview 217 8.1 Human Reliability 217 8.2 Errors in Healthcare 218 8.3 Medication Errors 220 8.4 Patient Falls 222 8.5 Human Factors and Ergonomics for Patient Safety 227 Questions and Learning Activities 236 References 237 Chapter 9 Health Analytics 245 Overview 245 9.1 Data Mining 245 Case Study 9A: Predicting Parkinson's Disease Using Data Mining 251 9.2 Data Visualization 255 Case Study 9B: Data Visualization in Obesity Counseling 269 9.3 Social Network Analysis 271 Case Study 9C: SNA in a Pediatric Intensive Care Unit (PICU) 277 9.4 Data Envelopment Analysis 280 Case Study 9D: Using DEA for Finding Best-in-Class Hospitals in a Network 285 9.5 Multicriteria Decision Making 287 Case Study 9E: Use of GP to Optimize Helicopter Emplacement at Medical Treatment Facilities 291 Questions and Learning Activities 292 References 293 Chapter 10 Capacity Management 297 Overview 297 10.1 Capacity Management Challenges 297 10.2 Managing Nursing Units 299 10.3 Managing Operating Rooms 310 10.4 Managing Diagnostic Units 316 10.5 Nurse Staffing and Scheduling 317 Questions and Learning Activities 320 References 321 Chapter 11 Healthcare Logistics 323 Overview 323 11.1 Facility Location 323 Case Study 11: Location of Federally Qualified Healthcare Centers 337 11.2 Home Healthcare Routing and Scheduling 341 Questions and Learning Activities 347 References 349 Chapter 12 Health Supply Chains 351 Overview 351 12.1 Forecasting Demand 351 12.2 Inventory Control 357 12.3 Healthcare Distribution 363 12.4 Coordinating Activities in the Supply Chain 369 Questions and Learning Activities 375 References 377 Chapter 13 Infection Control 379 Overview 379 13.1 Historical Perspective 379 13.2 Infection Control Classification 381 13.3 Checklists for Infection Control 383 13.4 The Case of Sepsis 385 13.5 Mathematical Modeling of Hospital Infection Control 388 Case Study 13: Impact of Interventions on TB Infection in a Clinic 398 Questions and Learning Activities 402 References 403 Index 405
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