Health systems and hospitals throughout the country face severe shortages of physicians, nurses, and other hospital staff. While this is not a new problem, last year alone there were 33% more open nursing roles than three years ago. Filling these vacancies poses a challenge, as AHA’s latest numbers indicate a 20.8% increase in hospital labor cost. There’s also an impending 90K physician shortage. These circumstances significantly impact the day-to-day experience and capacity of the frontline, who are overburdened and stretched thin both at the hospital and at home — with work often bleeding over into “pajama time.”
This manifests not only in provider burnout, but in hospitals operating well below their capacity. Hospitals, depending on size, have $300-400 million of fixed assets, such as ORs, inpatient beds, and infusion centers, which are underutilized. With limited staff to operate these assets, hospitals are forced to run fewer inpatient units and operating rooms than they actually have available.
The impact of this idle time is huge — unlocking even ten points of productivity in these assets amounts to $30 or 40 million of pure bottom-line impact for each hospital. And it’s achievable: LeanTaaS works with 185 health systems and on average, through AI-powered capacity management they perform 2-4 more OR cases per OR per year, accommodate 6+ new patients per bed per year, and generate an additional $20k per infusion chair per year.
Solving the underlying problem of capacity management
To get to this ROI, the root cause of idle time and imbalanced staff must be identified and treated. Optimizing assets and empowering a constrained workforce are interlinked and solved the same way: by matching supply with demand through AI, machine learning, and predictive analytics. Unlike manufacturing where an imbalance between supply and demand can be offset by changes in the inventory level, healthcare has to balance them continuously — otherwise a patient or a provider is forced to wait or an expensive asset will sit idle. We have invested enormous amounts of time, effort and capital to build algorithms that predict the demand signal with a high level of accuracy and incorporate the constraints on the supply side (facilities, staff, equipment, etc.) in figuring out the optimal allocation that can keep patients moving smoothly through the system.
Most staffing solutions in health systems are time and attendance systems that keep track of who is working in which unit and how staff should be paid. This has nothing to do with optimization. An AI-powered solution will accurately predict the volume, type and timing of the incoming patient demand over the upcoming hours, days and weeks, understand a hospital’s staffing requirements, and then construct shift schedules and rosters to meet that demand. In addition to prediction, the right tool offers prescriptive, intelligent recommendations that are resilient to shocks on either the demand or the supply side.
How AI and automation empower and optimize frontline hospital staff
Operating at the edge of capacity every single day is exhausting, and spending a large chunk of each day doing routine, mundane tasks is frustrating. That’s why the best AI tools eliminate as much of the manual work as possible through automation. Every day, hospitals ask their highly skilled people to pull numbers, send text messages, leave voicemails and chase people in order to complete tasks that could easily have been automated.
By automating routine tasks and providing intelligent recommendations — such as inpatient units to open, surgical cases to schedule in an operating room, or infusion nurses to assign to patients — frontline staff can make data-driven decisions. This is how AI becomes an ally, by augmenting human decision making — not replacing it. In a sense, an AI-powered operations solution in the hospital is like a navigation system in the car — always suggesting an intelligent route to get to the destination faster but expecting that the driver may sometimes override the recommendation based on unique knowledge (e.g., not exiting the freeway at night in an unknown part of town just to get home five minutes earlier). Over time, as the frontline gains confidence in these recommendations, they will rely on the tool more often and it will feel like a natural and integral part of their day, as we all do when Google Maps suggests our driving route or Netflix makes a recommendation for a new TV series.
Minimizing manual tasks and reducing cognitive overload empowers staff to operate at the top of their license and frees up their time and mindspace to do what they love doing: taking care of patients. This is key to reducing burnout and optimizing valuable staffing resources, as well as supporting efficient care delivery overall.
Proven results and ROI
AI technology, in the hands of frontline staff and health system leaders, mitigates the impact of both staff shortages and capacity problems. Solutions such as LeanTaaS’ iQueue suite are designed to fit precisely this need, and have demonstrated tangible impact in nearly 200 health systems across the country.
By deploying the iQueue for Inpatient Flow solution, the Florida-based Health First reduced weekly staff hours of manual data collection by 200%. Children’s Nebraska, using iQueue for Operating Rooms to streamline communications among scheduling stakeholders, grew surgical case volume by 12%. In an ambulatory setting, Oklahoma Cancer Specialists and Research Institute continually relied on iQueue for infusion Centers to align nurse resources with patient demand, leading to a 21% increase in average completed daily appointment volumes without having to hire additional nurses.
The next horizon of AI in hospital operations
LeanTaaS is dedicated to continuing to help our customers achieve these outcomes. To this end, in 2023 we released several enhancements across our entire iQueue product suite, targeted at empowering and optimizing staff in hospitals and ambulatory centers. These AI-powered capabilities help reduce administrative burden, forecast future staffing needs, right-size and optimize staff assignments, and overall reduce daily chaos for frontline staff by predicting and matching supply and demand. Functions include predicting future hourly staffing needs in the operating room; helping organize inpatient clinical staff across health system, hospital and unit levels; and adjusting nurse assignments in infusion centers in real time, per workloads, preferences and patient acuity.
We are also harnessing the potential of generative AI. By eliminating redundant tasks like transcription, and using human language to intelligently assist leaders and staff in their day-to-day work, generative AI can save time, reduce burden, and empower staff to act strategically. The Form Automation tool we’re releasing for iQueue for Operating Rooms leverages generative AI to automate surgery booking requests, parsing information from language-based sources like notes, scanned images, and PDFs to autofill form fields. Going forward, we envision a future where this technology combined with automation makes real-time, intelligent adjustments to schedules and staffing, running these historically manual tasks on autopilot.
This future, which we are already delivering to our customers, will enable hospitals to efficiently direct assets and resources to care delivery in order to do more with less, safely and sustainably.
To view an in-depth discussion on the role of AI in empowering and optimizing hospital workforce, see my recent session with Scott Becker, Founder of Becker's Healthcare.