Real-Time Nurse Dispatching Using Dynamic Priority Decision Framework

Abstract

The increase in medical treatment complexity can cause experienced nurses to have difficulty determining priorities among patient needs. Electronic health record systems will enable automated decision support to assist medical professionals in making these determinations. This article details a framework that uses a discrete-event simulation, programmed in Python, to determine how priorities should be assigned in real time based on characteristics of patient needs. The severity of patient needs is dynamic because severity increases over time until the need is addressed. The simulation framework is applied to a cardiac care unit with 14 patients, who collectively have 125 needs. Four different priority schemes are evaluated and their effectiveness compared under the assumption of an 8 or 9 nurse capacity. The results illustrate the importance of modeling the dispatching of nurses according to severity because, although fewer nurses result in longer average queue times, they can handle higher-severity needs effectively.