How three health systems are using AI and better math to improve hospital capacity utilization

Hospitals are speeding towards a head-on collision.

Patient volume is rising as the population ages, chronic disease rates increase, and patients return to deferred care. At the same time, we are in the midst of a burgeoning staffing shortage while margins are decreasing and reimbursement ​​pressures are increasing. It is simply no longer possible for many health systems to build or buy the capacity they need. The only way to thrive is to learn how to do more with less.

Unfortunately, while healthcare personnel can often see where their assets are not being fully utilized, they struggle to make meaningful changes. Optimizing spaces like operating rooms and their staff, and resources like infusion chairs and nurses, requires complex matching of supply/demand signals and the aligning of linked services in different areas. Meanwhile, adapting inpatient bed units to best accommodate daily flow involves looking into likely future patterns of admissions and discharges. These tasks require too much high level math to manually address, and yet staff are often forced to do so, equipped only with tools that merely highlight current capacity issues without offering predictions or solutions.

As part of the upcoming Becker’s Annual Meeting, LeanTaaS, a leading healthcare analytics company, will showcase a half-day Transform Hospital Operations event beginning at 8am CT on Tuesday, April 26. This will offer a deep dive into the strategy and experience of successful capacity management across hospital operations. In this in-person event, which will be made available via virtual streaming the following week, health system leaders and technology partners will explain their journeys, outcomes, and learnings throughout five sessions. Some healthcare systems have implemented more advanced, data-driven strategies and tools, and have yielded greater capacity as a result. The following case studies will be discussed in more depth at the upcoming event.

Rush University Medical Center deploys data to break barriers to operating room utilization and sees 16% drop in abandoned block time

Like other perioperative leaders, those at Rush University Medical Center were challenged to improve accessibility and efficient use of operating room time. To address underlying issues preventing successful operating room scheduling and utilization, they needed to foster a standardized approach to key operational decision-making with a visible and transparent “single source of truth” of data. In their process of adopting a culture of data transparency and metric standardization, Rush implemented analytical scheduling software and reaped the benefits of transparent data, defensible metrics, powerful visualizations, and easy-to-use analytics tools built into workflows.

In less than a year, Rush saw a 3% increase in overall room utilization, showing surgeons and staff were able to perform more cases within preferred hours and avoid early mornings and late nights. The OR minutes for Rush’s top requesters of time also grew by 30%, while abandoned block time decreased by 16%.

Speaker: Alena Shelton, Director of Business Operations, Perioperative & Interventional Services, Rush University Medical Center

UCHealth achieves digital transformation of inpatient throughput, driving 8% decrease in opportunity days – equating to millions of dollars in additional value for the system

As they managed an extremely large and diverse patient population, front line inpatient bed staff at Colorado-based integrated care network UCHealth struggled to predict discharges and admissions, place the right patients in the right beds at the right time, uncover bottlenecks, and highlight high-impact transfers. Implementing cloud-based technology to help support these capacity management tasks was key, but ensuring that technology was ingrained logically as part of the staff’s workflow was just as critical.

By utilizing predictive analytics through a “virtual distributed capacity command center”, which made actionable information clear and accessible to bed staff immediately, UCHealth reduced time to place by 16% and time to transfer from the ICU by 65%. UCHealth has seen an 8% decrease in opportunity days (difference between Med/Surg LOS & CMS LOS).

Speaker: Jamie Nordhagen, MS, RN, NEA-BC, Director of Capacity Management and Patient Representatives, UCHealth

Vanderbilt-Ingram Cancer Centers uses optimized scheduling to slash patient wait times by 30%

Without the powerful analytics needed to coordinate the many factors involved in scheduling infusion appointments, Vanderbilt-Ingram Cancer Center (VICC) lacked the resources to increase capacity. The center experienced the typical pain points of high patient wait times, unmanageable midday peaks in volume, and burnt out nurses who could not take lunch breaks. By adopting a data-driven solution that acknowledged and addressed the factors causing these capacity problems, VICC achieved a nearly 30% decrease in patient chair wait time, with a 20% decrease in drug wait time at its largest infusion center; as well as building scheduling templates that level-loaded appointment demand across the day, ensuring predictable workloads and breaks for nurses.

Speaker: Cody C. Stansel MSN, RN, NE-BC, OCN, CMSRN, Interim Director, Nursing, Vanderbilt-Ingram Cancer Center

Session attendees will learn more about the approaches these health systems took and the solutions they found, and discover key learnings they can apply to unlock capacity at their own organizations and navigate the challenging years ahead.

To hear directly from these leaders and engage further with these solutions, learn more about the Transform subevent here.

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