Introduction into Discrete Event Simulation Methodology (DES): Part 1 - Dynamic Supply & Demand Balance and Capacity Problems

Discrete event simulation (DES) is the most powerful methodology used in healthcare data analytics. It is widely used in situations that are too complex because of random and non-random variabilities and multiple feedback loops typical in healthcare settings. Most queuing models presented in the previous webinar cannot be applied to such processes because of a violation of the main queuing assumptions. Simple simulation models will be presented as well as playing various scenarios to discover and illustrate some fundamental management principles. Comparisons with analytic queuing models presented in the previous webinar will also be provided.

Method: DES using Process_Model simulation software

While one could find rich literature on various aspects of discrete event simulation (DES), it is typically presented as a fictitious example in a format that is difficult to use or replicate by a layman. One should attend this webinar because it is focused on examples from real hospital practice, not fictitious examples.

All presented examples are illustrated using the powerful DES software Process_Model by the instructor with dozens of years of hospital experience as a lead simulation consultant. His experience, in particular with DES, was presented in his widely cited book with more than 10,000 sales worldwide: Kolker, A., “Healthcare Management Engineering: What does this fancy word really mean?” Springer Briefs, NY, 2012.

This book was used as a main text for the training course by the National Health System, the UK, as well as by the Lubar School of Business at the University of Wisconsin-Milwaukee for the graduate course on healthcare delivery systems and data analytics.

Learn:

• What is discrete event simulation modelling
• Why and when to use simulation modelling in healthcare settings
• Simulation vs. analytic queuing: pros and cons
• What are the typical components of a simulation model
• Input information required by a typical simulation model
• Why discrete event simulation is the most powerful methodology for analysis in healthcare settings
• Summary of some fundamental management principles in healthcare settings

• The concept of simulation and its use in healthcare services
• Demonstrating manually a simple discrete event simulation model: step-by-step
• Reviewing components of a simulation model
• Demonstrating simulation models for capacity analysis and supply and demand balance and patient flow
    • Applying DES to Queuing examples considered in the previous webinar as well as presenting other examples beyond the capability of analytic queuing theory.
• The following examples will be presented: 
      • Outpatient clinic: centralized or separate locations? 
      • Outpatient clinic: non-steady-state operations
      • Outpatient Clinic: limited queue size with leaving ‘inpatient’ patients
      • Outpatient Clinic: Time-varying arrival rates
    • Separate or interchangeable (shared) operating rooms for competing emergency and scheduled surgeries, and some others

• Quality Engineers/Analysts 
• Hospital Quality Analysts
• Nursing Managers
• Chief Nursing Officers
• Directors and VP of quality and operations improvements of healthcare organizations interested in learning practical methods of data analytics for optimal nursing staffing, the required number of exam rooms and pieces of equipment, and other resources.