Why Flu Season Modeling is Critical - Especially This Year

The impact of flu seasons on hospitals has always been difficult to predict. It generally depends on several factors, including the amount of virus circulating, the efficacy of vaccines (which can fluctuate year-to-year), and more.

Anticipating the impact of this year’s flu season will be especially challenging. That’s because we’ve never had a season where the flu, RSV, and COVID-19 were so prevalent in communities. Consider that we’re barely into the fall and some hospitals have already begun to see surges in flu cases. Indeed, some of those surges began during the summer, long before the traditional flu season typically begins.

Perhaps this is why many experts are already predicting that this flu season will be unusually long and severe. Already, we are seeing surges in flu cases, particularly in children’s hospitals. And Australia—typically a harbinger of what’s to come in the Northern hemisphere—is experiencing a terrible flu season.

Whatever the case, it’s clear that hospitals need to start capacity planning and process optimization procedures now to prepare for best and worst-case scenarios and anything in between.

Staffing and Resource Shortages Drive the Need for Accurate Modeling

A surge in flu cases this year could not have come at a worse time for hospitals. Already, many organizations are dealing with significant staff and resource shortages, leaving them straining to care for even more manageable censuses. Consider:

• 22% of nurses are thinking of leaving their current positions
• 99% of nurses report staffing shortages in their workplaces
• An estimated one million nurses will retire by 2030—making this an ongoing challenge that will likely reverberate throughout the foreseeable future.

Things are already reaching the crisis stage. Staffing shortages are now among patients’ top healthcare concerns. For further evidence, look no further than Zuckerberg San Francisco General Hospital, which recently had to divert patients due to insufficient capacity. Per the article, “For the most part, hospital crowding isn’t due to a lack of physical beds, but inefficient use of nursing resources.”

What happens to that—or other—healthcare facilities when flu cases rise this season? Or when the flu and RSV combine with COVID-19 to create a possible “tripledemic” scenario?

How do they maximize their resources and ensure they have the right number of staff for the right number of patients?

Accurate Flu Season Modeling Requires New Processes and Technologies

One thing is certain: traditional capacity planning processes, like Monte Carlo simulations and manual prediction methods, will be insufficient in the face of such an event. That’s because they do not take into consideration the many interdependencies and continually fluctuating patient data—all of which can influence a hospital’s capacity.

Accurate flu season modeling requires more advanced, intelligent, and dynamic predictive analytics software. Software that not only considers historical data based on past flu seasons but incorporates unique patient information into that data, pairs it with discrete-event simulation, and extrapolates it via dynamic, stochastic, and changeable digital twin technologies.

How Discrete-Event Simulation Contributes to Accurate Flu Season Modeling

Discrete-event simulation simulates real-life operational behavior patterns. It considers events as they occur and incorporates AI software for hospitals—including machine learning—to determine what’s likely to happen.

For example, discrete-event simulation can be used to model where and how patients are likely to progress through a hospital. It can show with remarkable clarity how an individual patient will move from the ER to a bed to discharge, or any other points.

With this information, nurses and hospital administrators can gain insights into potential lengths of stays for each patient, the number of beds that will be needed, and more. This information can help administrators plan staffing resources to accommodate the number of patients in their facilities.

How Digital Twins Help Hospitals Plan Capacity During Flu Season

Discrete-event simulation can be paired with digital twin technology to provide administrators with an unparalleled view into census and capacity—both in the present and in the future.

A digital twin is, in essence, a virtual replica of a hospital. It can show what a hospital’s capacity will look like in the next few hours, weeks, or months. The digital twin can show the simulations that originate from the discrete-event models, giving planners better insights that translate into operational improvements.

Digital twins can also help manage What If Scenario Analysis (WISA) to show potential outcomes. WISA is used to determine the impact of different variables and process changes can have on hospital planning and operations.

For instance, digital twins can provide nurses and administrators with the ability to “see into the future” of what their hospital’s capacity will look like during a potential flu surge in January. With this glimpse, they can begin planning their staffing and resource needs long before that date range. They can have right-size staffing and have the right number of resources in place to accommodate the surge, resulting in better care orchestration and avoidance of patient diversions.

“Hope is Not a Strategy”

Hospital administrators have every reason to believe the 2022-2023 flu season will be worse than the average season. We can hope that’s not the case, but as a famous saying goes, “Hope is not a strategy.” Having the right predictive analytics software and processes in place is—and they are what will help hospitals manage possible flu season surges.

For more information about the benefits of predictive analytics, discrete-event simulations, and digital twin technologies this flu season, download our latest white paper: Preparing for a Tripledemic: Resource Planning in the Face of Covid-19 / Flu / RSV.

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FutureFlow Rx uses a digital twin of your hospital or hospital system to plan for the right resources and staffing when and where you need it most. Learn more about our AI solutions for your healthcare environment.