Queuing Theory to Guide the Implementation of a Heart Failure Inpatient Registry Program

Design: We used a queuing theory model to simulate 3 different potential solutions to decrease the delay from patient identification to connection with discharge services. Measurements: The measures included average rate at which patients were being connected to the post discharge heart failure services program, average number of patients in line, and average patient waiting time. Results: Using queuing theory model simulations, we were able to estimate for our current system the minimum rate at which patients need to be connected (262 patients/mo), the ideal patient arrival rate (174 patients/mo) and the maximal patient arrival rate that could be achieved by adding 1 extra nurse (348 patients/mo). Conclusions: Our modeling approach was instrumental in helping us characterize key process parameters and estimate the impact of adding staff on the time between identifying patients with heart failure and connecting them with appropriate discharge services. J Am Med Inform Assoc. 2009;16:516–523. DOI 10.1197/jamia.M2977.