COVID-19 Is Transforming the Future of Clinical Operations

As the pandemic has created the need to optimize healthcare delivery, nursing and clinical leadership are leading the change.

Editor's note: Betty Jo Rocchio, MS, RN, CRNA, CENP, is the senior vice president and chief nursing officer at Mercy in Missouri.

When I look at what COVID-19 has taught us, it has highlighted three major problems that were present before the pandemic; 2020 just brought them into focus. They are workforce management, capacity management, and patient outcomes.

Though these three are often discussed as separate issues, COVID-19 brought to light how connected they actually are. The use of predictive analytics helped "connect the dots" so that our team at Mercy was able to solve the ever-changing challenges they faced throughout the pandemic. We were in many ways able to improve upon seemingly unchangeable processes, which quickly fell by the wayside as we adapted to our new reality.

In times of crisis, it was important to lean on the right outside partners to supplement our own resources. It wasn't about working harder; it was about working smarter and finding the right partner to help us because healthcare is one sector in a broader industry, and we can learn so much on the outside that we can bring in.

Pictured: Betty Jo Rocchio, MS, RN, CRNA, CENP, is senior vice president and chief nursing officer of Mercy health system in Greater St. Louis, Missouri. Photo courtesy of Mercy.

Workforce management

As I'm sure many chief nursing officers will agree, we were well aware of the nursing shortage leading up to COVID-19. I don't think we realized how short we would become, faced with increased demands, priorities, and an acute patient population. Generally, our inpatient departments had a general ebb and flow to the type of patients that we saw.

Well, that did not happen in the pandemic. As a matter of fact, what was so scary to us as a health system and everywhere nationally, was that patient population we were used to treating went away. In the early days of the pandemic, volumes at many hospitals dropped initially and had fewer patients. Then, like many other hospitals, we faced surges with COVID-19 patients displacing regular populations. We were forced into a spot to do demand planning around an uncertain population—a scary spot to be if you've not been in it before.

In the midst of the crisis, our team saw the solution by asking the question we had not asked before: "Do we have a nursing shortage or are we not designing the care model to fit and manage within our workforce market?"

And when you take a look at total workforce, it's not just nurses. It is about the total clinical help that we have at the front lines. It took the wildly variable volume of patients, increase in patient acuity, and change in the types of patients that COVID-19 brought to Mercy to lead to permanent changes in workforce management.

Capacity management 

In the process of moving across our whole system, we've touched so many departments and any hiccup along that path for the patient affects capacity management. There's so much to consider and each diagnosis has a variation in the patient population. You can see how this probably would become a huge math problem for us.

That's where workforce management and capacity management intersect. We know that when you have a workforce shortage, or you think you have a workforce shortage, looking at demand hours for patient care is based on a pre-determined ratio of licensed and non-licensed personnel. And if the patient need isn't correct, or we're not optimizing patient need, demand hours become variable or a "best guess."

This leads us to the question—are we not optimizing capacity management for the workforce or do we have an actual shortage in the workforce?

Patient outcomes

Being a nurse leader means understanding how to use analytics to improve performance, care, patient experience, and nurse engagement. With workforce management, capacity management, and patient outcomes all inextricably connected, the use of predictive analytics to improve performance was critical.

Those who had technology and analytics heading into this pandemic, I guarantee were more successful. At Mercy, we saw our long-term investment in technology as an advantage to pivot quickly to adapt to the new demands. Those of us who had automated analytics in systems to know how much personal protective equipment we had on hand did far better in acquiring it.

Mercy has advanced analytics and we were able to get out in front of the market and acquire what we needed faster. There was not a day that we didn't have what we needed.

From a mathematical modeling and predicting perspective, the data that we could use to predict what's going to happen was also upended during COVID-19. We had to quickly adapt models to say, "What problem am I really trying to solve?" Is it opening up more capacity, for example, to get more elective surgeries done?

With most ORs utilizing Block Time management, COVID-19 presented an opportunity. Was it time to consider going back to handing blocks of time to individual surgeons or groups because "it's the way it was always done," or was this a time to actually get everyone to work together in a much more collaborative way because everybody's patients are important and there was a huge backlog built? We ended up finding that the problem statement and capacity management was less about predicting and prescribing based on historical data.

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