Harnessing some of today’s most transformative technological tools, including artificial intelligence and machine learning—with a dose of Lean principles—can enable healthcare provider organizations to achieve greater capacity and workforce-staffing efficiencies, according to Mohan Giridharadas, CEO, LeanTaaS.
“Today’s organizations need tools to address the overwhelming complexity of the current healthcare field—tools that can help minimize rework and keep patient flow going,” he says. Tools, ultimately, that will help healthcare organizations deliver on their missions to provide the best care to their patients and the communities they serve.
AI-based tools that use advanced mathematical principles proactively address the biggest challenges, according to Giridharadas, especially when it comes to streamlining administrative tasks, addressing scarce capacity, improving patient and workforce engagement, and reducing clinician burnout.
The Power of Prediction
One way to tackle patient flow and capacity and staffing challenges—and improve a patient’s overall journey throughout the health system—is using powerful, “smart” algorithms that can predict demand, which have proven beneficial in the airline, package delivery and ride-hailing industries. In healthcare, these predictions can optimize capacity, improve patient flow and promote overall efficiency.
AI-powered solutions, such as LeanTaaS’ iQueue suite, match supply with demand to dynamically manage capacity and improve utilization of constrained resources like operating rooms, infusion chairs and inpatient beds. They also predict the type of patients, volume and timing of patient demand across hours, days and weeks, allowing hospital leaders to better understand their staffing needs and more efficiently create schedules.
“Based on patterns, our algorithms predict where the demand is going to be,” Giridharadas says. “For example, we can predict that unit two, four hours from now, will be four beds short. If you know that, you can start to figure out, ‘Do I have the right staff?’ Or if you can predict what the demand’s going to be three days from now, you can look at your nursing roster and say, ‘I’m predicting the med-surg unit is going to be bursting at the seams with patients, and I don’t have enough staff. Let me look to the float pools.”
From there, Giridharadas says, hospitals can “layer on additional complexity” into the algorithm that fits their unique circumstances, such as considering what credentials or skill sets the team needs to fill upcoming shifts or which staff members have already taken overtime.
Reducing Burnout
In addition to streamlining scheduling, these tools can reduce workforce burnout and frustration on the job. This is particularly true among nurses, who are often weighed down by an abundance of nonclinical work and a scarcity of staff members.
“Nurses desire to take care of patients,” says Giridharadas. With that in mind, there are tools in the iQueue suite designed to reduce nurses’ “cognitive burden regarding things they don’t need to worry about, so they can focus on engaging with patients and staff,” he says. For example, the recommendations the tools make to nursing schedules and rosters, based on predicted patient volume and staffing requirements, augment the front-line staff’s decisions, not overrule them, an important distinction, according to Giridharadas.
“We think of it as an amplifier—as augmenting, not replacing,” he says. “It’s making the recommendation, but the staff owns the last mile” when finalizing staff schedules and patient timeslots, based on their professional assessment of patients’ medical histories and other factors that might influence urgency of certain cases.
A Force Multiplier
These AI-powered solutions, coupled with Lean principles, serve as what Giridharadas calls a “force multiplier.” That is, they allow healthcare provider organizations to get more work done with fewer staff and with more efficient use of the assets and resources they already have. This is welcome news in an era of persistent workforce shortages and post-pandemic-related financial pressures that continue to reverberate throughout the field.
According to Giridharadas, there is substantial value that can be uncovered when hospitals can use technology’s newest tools to achieve more efficient resource and asset utilization.
“Consider the impact on 5,000 hospitals, which have an average of $300 to $400 million in assets, such as ORs, inpatient units and imaging machines,” he says. “This means $150 to $200 billion in value could be unlocked each year if we can get just 10 percentage points better at improving asset utilization within our health systems.”
Giridharadas estimates that could be worth between $30 and $40 million per hospital, which could be a huge boost to their bottom line and ability to serve patients more effectively.
“Demand is up, nursing and physician shortages still exist, and reimbursements are down,” Giridharadas says. “We have to learn to do more with greater efficiency while taking care of our most precious assets—our patients.”
For more information, please contact Kate Soden, communications director, LeanTaaS, at kate.s@leantaas.com.