Minimize clinic waiting times to avoid virus spread

Minimize clinic waiting times to avoid virus spread

Anna Oom |March 11 2020 5 min

In times of coronavirus breakouts and in the middle of the regular influenza season, there is an ongoing debate on how to avoid spreading of infections. One should point out that people suspected to carry the corona virus are treated with extra care, but it actualizes the never-ending story of the risks of getting infected by virus or bacteria from other people in a clinic waiting room.

Sitting in a waiting room together with others is a high risk especially to those with compromised immune defense. On top of that, people that don’t show symptoms of infections could still potentially spread them. So even though the waiting room should be the doorstep to getting better, it could actually be the other way around. Below I will tell you more about what medical caregivers can do to minimize the waiting time in clinic and hospital waiting rooms to avoid infection spread. 

How air-borne infections spread in a waiting room

A group of researchers (Beggs et al.*) constructed a stochastic model to analyze the transmission of airborne infection in a hypothetical hospital waiting area in which occupancy levels, waiting times and ventilation rate could all be varied. The study showed that the number of new infections cases increased dramatically with waiting time. Also, the number of susceptible individuals in the room, increased the number of new infection cases quite clearly. The authors concluded that when seeking to prevent the transmission of airborne viral disease the first thing to do is to minimize waiting times and the number of susceptible individuals present, before turning to expensive ventilation solutions etc.

Based on this, medical providers should seek to reduce waiting times not only to increase patient satisfaction and to reduce cost but also to avoid spreading of air-borne infections.

How to reduce waiting time in the waiting room to avoid infection

When aiming to reduce the waiting time- and number of patients in a waiting room, there are a few things to consider. The first thing is to streamline the queue process, basically analyze and map the existing queue process / patient journey and identify the main improvement areas. For sure, some of the things I mention below will be of significant help once it is time to improve the patient journeys at your hospital or clinic.

Appointment solutions

One of the most important things to consider in order to reduce the waiting time in the waiting room, is an appointment solution. By enabling patients to book an appointment in advance, you decrease the number of patients waiting for a drop-in appointment as drop-ins often cause long waiting times and crowded waiting rooms. An appointment solution allows you to plan work-load in advance and steer appointments to less busy hours. 

Virtual queuing

What really makes a difference in order to avoid patients waiting physically, is to have a virtual queuing system. By enabling patients to get a virtual queuing ticket in their mobile phone, they can wait for example at home, outdoors or in their car until they are called to see the doctor. No need to sit in the waiting room at all. 

Manage peak-hours

It can be hard to completely avoid peaks of patients at a clinic. In order to manage those peaks, it is great to have a queue management system that can monitor real-time data and steer over to a different set of calling rules with a single goal of decreasing the number of people waiting, for example. These different calling rule scenarios are programmed in advance and are integrated with the staff profiles so that no manual changes are needed.


Qmatic has long experience of patient journey management and queuing solutions. If you want to know more about implementing virtual queuing for your organization, download our Virtual Queuing guide, Safer Queuing with Virtual Solutions.


Download the Virtual Queuing Guide


*Reference: Beggs CB, Shepherd SJ and Kerr KG. Potential for airborne transmission of infection in the waiting areas of healthcare premises: stochastic analysis using a Monte Carlo model. BMC Infectious Diseases 2010, 10:247doi:10.1186/1471-2334-10-247.


Anna Oom

Anna Oom

Global Content Marketing Manager.

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