Purchase any WEBINAR and get
10% Off
CODE: SAVE10
T&C applicable, please referFAQ
Validity : 10th Aug'25 to 20th Aug'25
Healthcare Analytics: Matching Scarce Resources: Optimized budgeted nursing staffing with random patient demand
- The main Concept and Some Definitions.
- The “newsvendor” framework approach.
- Optimized annual staffing level
- Optimized monthly staffing level
- Optimized staffing for caregivers’ skills mix
- Comparison of the 3 main methodologies for modelling staffing with variable patient demand
Overview of the webinar
Because of the inevitable variability of the patient census (uncertainty), the planned (budgeted) staffing is usually: (i) either not enough to deliver proper quality of care or (ii) is excessive, resulting in idle time for some employees and/or pay under contractual obligation for the idle time.
This webinar is providing a methodology called the ‘newsvendor’ framework that helps in planning (budgeting) the staffing level that minimizes the overall cost of under- and overstaffing.
Reference: Kolker, A., The Optimal Workforce Staffing Solutions With Random Patient Demand in Healthcare Settings. In Encyclopedia of Information Science and Technology, 4-th Ed, IGI-Global, chapter 322, pp. 3711-3724, 2017
Kolker, A., Healthcare Management Engineering in Action, 2nd Ed, Springer.
Tool: Excel spreadsheet
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
Why should you attend?
Typically, nursing staffing is based on the past historical average daily patient demand (midnight census), and the average required daily hours of care per patient depending on the acuity level (supply of resources).
However, the variation and the uncertainty of the supply and demand creates two types of problems:
- Over-staffing over the planned level which hurts operation margins;
- Under-staffing over the planned level, which requires overtime and/or premium pay that also hurts margins and causes lower quality of care.
The latter problem affects patients’ and staff satisfaction.
The objective of this webinar is providing an overview and examples of application of the methodology called the “newsvendor” framework.
This methodology helps to determine the optimal staffing for the specified time periods for hospital units with randomly fluctuating patient census.
The optimal staffing provides the total minimal possible cost of over- and under-staffing.
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.