An application of multi-attribute value theory to patient-bed assignment in hospital admission management: An empirical study

Abstract

Hospital beds are considered economically scarce and hospitalists strive to balance between utilizing beds more efficiently and complying with preference of physicians and patients when pairing patients to beds. This research is to develop preference-based decision rules for patient-bed assignment in a dynamic environment. A multi-attribute value theory (MAVT) model with additive value function is proposed to quantitatively deploy hospital policies in bed management. To elicit scaling factors and value functions for attributes, a linear programming model is constructed for all preference conditions. An empirical study was conducted with real data collected from two branches of a medical center. The simulated results using value function showed greater benefits when the patient-bed ratio was high and more flexible ward assignment was allowed. Further, a detailed analysis showed that this MAVT model was better in preference matching for both physicians/nurses and patients. At least 79 percent of patients were given beds in designated wards in accordance with their attending physicians' subspecialty, and more than 48 percent of patients' room preferences were matched in the simulated assignment for one branch.