McLeod Health Optimizes Staffing for Patient Room Cleaning

Abstract

Patient room cleaning is an often-neglected hospital process. But it has serious implications for clinical outcomes and patient satisfaction. Delays in turning rooms around between patients can impair hospital capacity and capability to speed up patient treatment. Inefficient assignment of rooms to the cleaning staff also can lead to higher incidence of infection transmission. We systematically developed and piloted an efficient room assignment logic for this critical process through an integer-programming staff optimization model at McLeod Health, a leading hospital system in South Carolina. We identified an opportunity for a 20% reduction in staffing level to handle the prevalent demand and annual staffing cost savings of about $575,000 or to handle a 30% greater demand in dirty rooms using the current staffing levels. McLeod Health integrated our recommendations into their staffing strategy immediately. History: This paper was refereed. Funding: This paper is based on a consulting project funded through the University of South Carolina Operations and Supply Chain Center at McLeod Health under the sponsorship of Donna Isgett.