It seems like wait times in the emergency department are getting crazier every day. Research has found that waiting times in the emergency room have increased by 36% for all patients, averaging at a 30-minute wait per patient. The sickest patients are sometimes the ones who have to wait the longest as well, with a quarter of all heart attack patients having to wait 50 minutes or longer before they see a doctor. Many factors come into play when looking at rising ER wait times – many have closed their doors, and more patients than ever are going to the emergency department when injured or sick. Other internal factors such as bottlenecking due to lack of inpatient bed space and lack of specialist availability exist as well. In order to better serve patients, something must be done about these increasing wait times. One possible solution is queuing theory.
So what is queuing theory? Well, it’s defined by a stream of arriving customers or tasks that are handled by a server. It originated over a century ago, emerging from the study of telephone delays and congestion. The purpose of queuing models is to eliminate the disparity between the demand for service and the ability to meet that demand. Many service industries use queuing to strategize how to improve efficiency. An example of this would be a grocery store that struggles with long lines at check-out. In order to raise efficiency, they could add an express lane for customers with smaller amounts of items, which could reduce waiting time all around. Call centres for customer service have also used tech that improves caller wait times by using a “virtual queue”, putting customers in line and allowing them to hang up, then receiving a call when an agent is free.
Now how do we take queuing theory and make it work in the emergency department? The easiest way is to use a multiple servers, single-phase queue. This is when patients wait in one line (in this case, the waiting room) for servers. The servers, in this case, would be the triage nurse, the bedside nurse, and the physician. Queuing calculations in healthcare are typically based on patient arrival rate, service rate, and the number of servers. The most popular model is the Poisson arrival process, which assumes patients arrive according to a random process. Arrival and service times tend to vary depending on the time of day, or the season, such as during the holidays.
The question is if queuing theory can actually work. At its core, queuing theory can be used to predict the effect of patient arrivals, treatment time, and emergency department boarding on the patients who leave without being seen. Some institutions have taken the theory further by discovering that the emergency department was understaffed during peak overs and overstaffed during non-peak hours. Many variables come with using queuing theory in the emergency room due to how complex they can be, but using the theory can and should be considered if hospitals ever want to decrease wait times in their emergency departments.