Healthcare Data Analytics: Methods of Matching Scarce Resources with Uncertain Patient Demand: Introduction to Discrete Event Simulation Methodology (DES), Dynamic Supply & Demand Balance and Capacity Problems
Overview:
While one could find a rich literature on various aspects of discrete event simulation (DES), it is typically presented in a format which 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 the fictitious examples. All presented examples are illustrated using powerful DES software ProcessModel by the instructor with years of hospital experience as a lead simulation consultant. His experience, in particular with DES, was presented in his widely cited book worldwide: Kolker, A., "Healthcare Management Engineering in Action?", 2nd Ed., Springer Nature, NY, 2024.
The 1st Edition of 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 system and data analytics.
Why should you Attend:
Discrete event simulation (DES) is the most powerful methodology used in process data analytics/Operation Research. The following examples will be covered:
- 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
Method: DES using ProcessModel simulation software. Building simple simulation models and playing various scenarios to discover and illustrate some basic management principles.
Areas Covered in the Session:
- 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, patient flow and supply and demand in healthcare settings
- Applying DES to Queuing examples considered in the previous webinar as well as presenting other examples beyond the capability of analytic queuing theory
Who Will Benefit:
- Quality Engineers/Analysts
- Nursing Managers
- Chief Nursing Officers
- Directors and VP of Quality and Operations Improvements of Healthcare Organizations
Speaker Profile
Alexander is the lead editor and author of 2 books, 8 book chapters, 10 journal papers, and a speaker at 18 international conferences & webinars in the area of operations management and data analytics. As an adjunct faculty at the UW-Milwaukee Lubar School of Business, he developed and taught a graduate course Business 755-Healthcare Delivery Systems-Data Analytics. He worked 12 years for GE (General Electric) Healthcare as a Data Scientist and CT Detector design engineer, 3 years for Froedtert Hospital, the largest healthcare facility in Southern state of Wisconsin, and 5 years for Children’s Hospital of Wisconsin as a lead computer simulation and system improvement consultant.
Currently he is teaching a 12-sessions online course “Healthcare Operations Research and Management Science” for the UK, National Health System (NHS).