introduction-discrete-event-simulation-methodology

OVERVIEW

Discrete event simulation (DES) is the most powerful methodology used in healthcare data analytics. It is widely used for processes with a lot of random variabilities that are too complex to be analyzed by statistical or machine learning methods.

Simple simulation models will be presented by playing various scenarios to discover and illustrate some fundamental management principles. Comparisons with analytic queuing models will also be provided.

Method: DES using Process_Model simulation software.

WHY SHOULD YOU ATTEND?

The focus of this webinar is the DES application for resource utilization and staffing & scheduling problems for highly variable random processes typical in healthcare settings.

You should attend this webinar if you are interested in learning real-life examples of the application of the discrete event simulation methodology for resource utilization and staffing & scheduling problems in healthcare settings.

LEARNING OBJECTIVES

Learn:

What is discrete event simulation modelling for resource utilization and staffing & scheduling problems
Why and when to use simulation modelling for resource utilization and staffing & scheduling problems
Input information required by a typical simulation model for resource utilization and staffing & scheduling problems
Why discrete event simulation is the most powerful methodology for analysis in healthcare settings
Summary of some fundamental management principles in healthcare settings

AREAS COVERED

Scheduling orders for appointments with different duration variability. Is 30 min +60 min always equal to 60 min +30 min?
Centralized discharge vs. individual unit discharge
Staffing of the hospital receiving center
Outpatient clinic cost and staffing: Is the right staff used at the right time?
Analysis of the optimal staffing for improving the Eye Institute performance: A case study of the Eye Institute, Aurangabad, Maharashtra, India.

WHO WILL BENEFIT

Hospital Quality Analysts
Nursing Managers
Chief Nursing Officers
Directors/ VP of Quality & 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.

Purchase options

Option	Price
Recorded Link Only	$299
Recorded USB Only	$349
Corporate Recording (Upto 10 Attendees)	$599

*Training USB will be shipped within 7-10 working days. *Buy Now Pay Later option is available in the payment cart page.
*In case you're unable to attend the live session, we'll make sure you receive the recording promptly.

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Alexander Kolker

Expert in Healthcare Information Technology and Data Analytics

About speaker

Alexander Kolker holds a Ph.D. in applied mathematics. He is an expert in advanced data analytics for operations management, computer simulation, and staffing optimization with a main focus on healthcare applications. 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.

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 the Southern state of Wisconsin, and 5 years for the Children’s Hospital of Wisconsin as a lead computer simulation and system improvement consultant.

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.

In 2022 he taught a 2-semester 12-session online course “Healthcare Operations Research and Management Science” for the UK, National Health System (NHS)-Midland & Lancashire Support Unit.

Alexander has also completed four business consulting projects using simulation modeling for optimal staffing and capacity analysis for: US Bank, Boston Consulting Group, Children’s Hospital of Wisconsin, and Ohio Hospital Association.