Determining Waiting Room Occupancy at an Outpatient Clinic Using Simulated Observations and Probability-Duration Curves.

Abstract

Adequate allocation of physical resources in hospitals has become increasingly important with the rise of health care costs. Seat utilization in outpatient clinic waiting rooms is one resource that is particularly important to monitor, to not only ensure patient satisfaction but also accommodate patient flow. Currently, very few studies are available on seat occupancy and patient flow in standard waiting rooms, and studies often neglect important factors, such as hourly patterns of patient influx and occupancy duration. These factors were taken into consideration in our study of visitor occupancy and patient flow in an imaging-facility waiting room. This paper discusses the simulated observation approach that we have developed, which coupled in-person observations with RIS data analysis. Using RIS data to guide our initial in-person observations, we built a model for simulated observations, based on the merged RIS and observation data. To determine the appropriate number of seats needed to accommodate patients and their companions, simulated observation results were analyzed using a probability-duration curve. This curve considers maximum room occupancies as temporal events, with certain probabilities and durations. We demonstrated how simulated observations and probability-duration curves can provide hospital managers with an efficient and pragmatic way to determine waiting room occupancy.