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Healthcare Analytics: Matching Scarce Resources: Integer Linear optimization for Staffing and Scheduling
- Integer Linear Optimization for Staffing and scheduling:
- Full-time and part-time staffing & scheduling with 1, 2 and 3 consecutive sliding days off:
- Weekly full-time staffing & scheduling with 2 consecutive sliding days off
- Weekly staffing & scheduling with employees preference and employees seniority
- Staffing and scheduling for 24/7 three-shift operations
Overview of the webinar
This webinar is focused on a special case of LO called Integer Linear Optimization for finding the cost optimal staffing with the various requirements for scheduled mandatory and sliding days off. Staff scheduling is a typical but difficult and time-consuming task for nursing managers especially in teams with a large number of associates, where the manager has to give considerations to the preference of each employee. Further, the number of associates required to be present on a shift might vary depending on various factors like weekday vs weekend, the workload forecasted for the week and some others.
Who should attend?
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 with sliding days-off.
Why should you attend?
You should attend this webinar if you are interested in methods for finding the lowest cost optimal staffing for the units with various requirements for scheduled mandatory and sliding days off.
The instructor’s hospital experience, in particular with linear optimization, was presented in his widely cited book with more than 10,000 sales worldwide: Kolker, A., “Healthcare Management Engineering in Action” Springer, 2nd Ed., 2024. 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 (USA) for the graduate course on Healthcare delivery system and data analytics.
Faculty - Mr.Alexander Kolker
Alexander Kolker holds a Ph.D. in applied mathematics and statistics. He is an expert in advanced data analytics for operations management, computer simulation modelling and staffing optimization with the 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.
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)-Midland & Lancashire.
Alexander has also completed four business consulting projects using simulation modelling for the optimal staffing and capacity analysis for: Boston Consulting Group, Children’s Hospital of Wisconsin, Ohio Hospital Association, and US Bank Corporation.