The updated 2nd edition of Healthcare Management Engineering In Action in the Business Guides on the Go series provides a comprehensive exploration of healthcare management operations. Through a systematic comparison of predictive and analytic decision-making methodologies with traditional management approaches, the book employs case studies derived from real-world hospital and clinic scenarios. It addresses a spectrum of problem encompassing patient flow, capacity management, resource allocation, staffing and scheduling, statistical data analytics, and cost distribution among cooperating providers.

The revised edition contains enhanced content, spotlighting key management principles vital for effective operational decision-making. The book encompasses a wide array of quantitative methods, including discrete event simulation, queuing analytic theory, linear, integer and probabilistic optimization, among others. By acting as a bridge between management engineering experts and healthcare administrators, Healthcare Management Engineering is an invaluable resource for hospital and clinic leadership, aiding them in their managerial roles. Furthermore, it serves as a comprehensive repository of introductory challenges and projects suitable for graduate-level students in healthcare management and administration.

Compares healthcare management engineering methodology with traditional approaches Includes multiple examples adapted from hospital management and clinic practice Illustrates the broad use of management engineering in hospital operations

Autorentext

^ ^ Alexander Kolker, Ph.D., has served as Operations Project Manager with Children's Hospital and Health System, Froedtert Hospital, Wisconsin, and as a Data Scientist at General Electric (GE) Healthcare. Dr. Kolker is the primary author of Healthcare Management Engineering (2012) and Management Engineering for Effective Healthcare Delivery (2011), and has been a frequent speaker at international conferences and webinars in healthcare operations management and data analytics. He has previously taught healthcare operations research and management science for the National Health System (NHS)-Midland & Lancashire Support Unit, UK.

Klappentext

The updated 2nd edition of Healthcare Management Engineering In Action in the Business Guides on the Go series provides a comprehensive exploration of healthcare management operations. Through a systematic comparison of predictive and analytic decision-making methodologies with traditional management approaches, the book employs case studies derived from real-world hospital and clinic scenarios. It addresses a spectrum of problem encompassing patient flow, capacity management, resource allocation, staffing and scheduling, statistical data analytics, and cost distribution among cooperating providers. The revised edition contains enhanced content, spotlighting key management principles vital for effective operational decision-making. The book encompasses a wide array of quantitative methods, including discrete event simulation, queuing analytic theory, linear, integer and probabilistic optimization, among others. By acting as a bridge between management engineering experts and healthcare administrators, Healthcare Management Engineering is an invaluable resource for hospital and clinic leadership, aiding them in their managerial roles. Furthermore, it serves as a comprehensive repository of introductory challenges and projects suitable for graduate-level students in healthcare management and administration.

Inhalt
Chapter 1. Traditional and Management Engineering in Operational Decision-Making.- Chapter 2. Capacity and Patient Flow Problems.- Chapter 3. Staffing and Scheduling Problems with Uncertain Patient Demand.- Chapter 4. Staffing and Resource Allocation Problems Amenable to Analytic Optimization Methods.- Chapter 5. Resource Allocation and Service Lines Problems and Linear Optimization Methodology.- Chapter 6. Staffing and Scheduling of Full-time and Part-time Employees with Sliding Mandatory Days-off for Multiple Shift Operations using Integer Linear Optimization Methodology.- Chapter 7. Comparative Efficiency of Units with Multiple Inputs and Outputs. Introduction into Data Envelopment Analysis..- Chapter 8. Advanced Multivariable Statistical Data Analysis.- Chapter 9. Introduction into the Concept of the Shapley Value.- Chapter 10. Summary of Fundamental Management Engineering Principles