Modelling Patient Flow to Improve Service Delivery

Running a hospital is a highly complex activity. There is not one division with one need, however, hundreds of areas are highly interconnected and all rely on each other to deliver life saving outcomes. Patient flow in such a complex system is a serious challenge.

In 2019 alone, there were over 11 million separations in Australia (a separation from a healthcare facility occurs anytime a patient leaves because of death, discharge, sign-out against medical advice or transfer, it is the most commonly used measure of the utilization of hospital services). These were just the patients who were discharged, let alone those who may have unnecessarily visited a hospital and sent home immediately.

Managing these millions of patients and providing the high level of care we have come to expect is extremely difficult.

This is why a Victorian Hospital recently turned to Biarri to get some help with their patient flow challenges. Biarri turned its mathematical expertise on the problem and what came out of our work was a great result with substantial improvements and clear benefits to the most important person of all – you.

The Patient Flow Challenge

The hospital approached Biarri after realising that its emergency department was consistently overcrowded at seemingly predictable times and for seemingly predictable reasons. The staff and executive team at the hospital knew that they could better plan and manage their overcrowding problem, and we at Biarri knew that we could provide them with the tools with which to inform those decisions.

One of the key metrics that quantifies the overcrowding of an emergency department is the NEDOCS score. In our case it wasn’t that the NEDOCS score didn’t provide value, it was that the staff were not able to anticipate when the score would rise or fall. Both management and clinical staff felt it should be possible to better predict when these spikes would occur, and therefore better prepare for them.

So the business problem for Biarri became, can we produce a tool that is able to accurately forecast the bottlenecks and queue lengths within an emergency department?

It was this fascinating challenge we solved and have developed a unique tool specific to this hospital.

The Approach

Biarri’s approach to this challenge was to build a custom simulation model that would act as a digital twin for the hospital’s emergency department. This allows the staff to simulate how the patients move through the different streams of the emergency department. The simulation model is built upon three main objects: 

1. agents, 
2. processes and 
3. resources. 

Let’s define these relative to the emergency department.

Patients are the agents that move through the system. They possess attributes such as scan type and scan priority that indicate how long it takes them to move through the system. Agents go through processes such as triage, scanning and reporting, which move them along the emergency department. Finally, doctors, nurses and the machines they use are the resources that are required to move our patients through the processes.

All the quantitative values, such as the frequency of arrival, or the time it takes for a CT scan, etc are found using the historical data from the emergency department. Using the past data is the best way to get a digital twin that emulates the workings of the emergency department accurately. This was combined with some smart twists on existing tools such as Discrete Event Simulation to simulate a high fidelity model able to accurately model the emergency department.

The Patient Flow Solution

At its core, Biarri’s patient flow tool provides users with the information to better understand how the future of their emergency department looks like. It does this by providing staff with feedback on the development of patient queues and bottlenecks at different stages of the emergency departments process.

Given the nature of simulation modelling, the tool provides a distribution of future queue times, with confidence intervals to encapsulate the likely ranges expected in the future. This provides insight into the changes over time of queue lengths at different stages of the emergency department. Not only does it give a general overview of the emergency department, but a more granular look at each queue.

A big plus for the patients is that from this queue length we were able to derive expected wait times so that patients are now able to know how long they expect to wait based on how busy the hospital is.

The tool also allows for scenario analysis. This gives hospital staff the agency to compare how their current conditions compare against changes in rostering when it comes to influencing patient flow.

With this solution, Biarri aims to give hospital staff the information to make sound decisions around the rostering of their resources and the structure of their emergency department.

What’s next?

Biarri’s new patient flow modelling tool was a great success and has proven its ability to accurately model patient flow and provide timely and accurate warnings of future bottlenecks.

The tool is tailored to the Australian environment and now having been demonstrated on a Victorian hospital, Biarri is looking to roll it out across Australia. If you have patient flow challenges and could benefit significantly by being able to better plan and allocate limited resources, then get in touch.