Inpatient dialysis units face an uncertain daily demand of hemodialysis procedures for end-stage renal disease (ESRD) patients hospitalized for health conditions that may or may not be directly related to their renal disease. While hospitalized, these patients must receive hemodialysis in addition to any medical services needed for their primary diagnosis. As a result, when demand for inpatient dialysis is high, treatments and procedures required by these inpatients may be delayed increasing their length of stays (LOS). This research presents an optimization approach for daily scheduling of inpatient hemodialysis to maximize the efficiency of the dialysis unit while minimizing delays of other scheduled procedures that could extend the LOS of the inpatients. The optimization approach takes into account the dialysis protocols prescribed by a treating nephrologist for each dialysis patient, the variable duration of the dialysis treatments, the limited capacity of the dialysis equipment and personnel, as well as the isolation requirements used to mitigate the spread of healthcare-associated infections (HAI). In addition, a variant of the optimization approach is developed that considers uncertainty associated with rescheduling procedures that are delayed and the expected impact on LOS. An experimental performance evaluation illustrates the capability and effectiveness of the proposed scheduling methodologies. The results of this research indicate that the optimization-based scheduling approaches developed in this study could be used on a daily basis by an inpatient dialysis unit to create efficient dialysis schedules
