Planning a Reliable Hospital-Wide Cleaning Workforce

Background: Every year, tens of thousands of patients die world-wide because of infections associated with the health system. One source of hospital-acquired infections which reportedly have reached prevalence levels of 7-10%, are poor hygiene measures. These can be addressed, among others, by scheduling a reliable hospital cleaning workforce, responsive to hospital requirements and safety standards. Methods: To model the problem, we develop a hybrid simulation model which captures features such as variation in demand as well as cleaning durations. Our model enables us to evaluate the current workforce schedule from a collaborating European hospital using a variety of performance metrics (e.g., waiting time for ad-hoc cleaning jobs) and levels of detail (e.g., response time broken down by time of day). Using a mixed-integer linear programming approach, we generate alternative schedules. Results: Our results indicate substantial improvements as compared to current planning: While the baseline workforce planning model with 13 cleaners sometimes fails to adequately cope with the demand, the demand coverage can be improved substantially with reshuffling the same number of cleaners. Conclusions: Using our simulation model and the MIP approach, hospital managers can provide a more reliable and safer environment for patients and staff.