The encyclopedia · Engineering & Operations · Operational decision · 2022–2023
McLeod Health cut room-cleaning staff 20% with an integer-programming model
An optimizer at McLeod Health found 20% lower room-cleaning staffing or 30% more capacity at the same headcount.
McLeod Health
the move
Patient room cleaning is often ignored, but slow room turnaround impairs hospital capacity and treatment speed, and poor assignment raises infection transmission risk.
A researcher from the University of South Carolina's Darla Moore School of Business developed and piloted an integer-programming model for assigning rooms to McLeod Health's cleaning staff.
The model identified an opportunity for a 20% reduction in staffing at current demand, worth about $575,000 a year, or handling 30% greater dirty-room demand with the existing staff.
McLeod Health integrated the recommendations into its staffing strategy immediately, and the study was published in INFORMS Journal on Applied Analytics.
why it works
- The model balanced demand, travel and infection risk that manual lists ignored.
- It quantified the choice: fewer cleaners or more throughput.
- A $575,000 annual saving made the case for immediate adoption.
- Room turnaround gains flow straight into patient capacity.
what transfers
Neglected back-office processes like room cleaning hide real capacity; modeling the assignment, not just the headcount, turns a cost center into patient throughput.
what came after
McLeod Health adopted the staffing recommendations right away. The paper, based on a consulting project through the University of South Carolina Operations and Supply Chain Center, was published in IJAA (2023) and is cited as a model for hospital environmental-services optimization.
references
- McLeod Health Optimizes Staffing for Patient Room Cleaning
- McLeod Health Optimizes Staffing for Patient Room Cleaning
- McLeod Health Optimizes Staffing for Patient Room Cleaning
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