UCHealth University of Colorado Hospital is located in Aurora, Colorado, and is part of UCHealth, a health system serving Colorado, southern Wyoming and areas of Nebraska. The hospital is home to 703 beds and sees 50,000 inpatient admissions and 140,000 ER visits per year. The entire health system, consisting of 12 hospitals with a total of nearly 2,000 inpatient beds, performs 140,000 admissions and observation visits per year.

THE PROBLEM

All UCHealth hospitals used to use homegrown bed management tools that required daily manual preparation. As a result, UCHealth encountered the following three problems:

1. Making consistent, data-driven decisions about capacity regardless of who was managing the capacity decisions that day
2. Planning proactively for census changes and getting out of constant crisis mode
3. Finding the right bed for the right patient among a diverse patient population

"The manual bed management system required nurses to enter when patients were ready to move after physicians wrote downgrade orders for transfer to lower levels of care," said Steve Hess, CIO at UCHealth. "While the organization had access to reports, dashboards, worklists, and an extensive and even overwhelming amount of data, none of these provided real-time data or accurate predictions of what would happen in the future.

"The health system needed a solution that would eliminate guesswork and anecdotal information from the decision-making process – specifically, it needed a data-driven approach involving predictive and prescriptive analytics to help both plan for tomorrow and manage the immediate needs for today," he continued. 

"UCHeath staff can quickly see, at any time and from any location, capacity status, as well as which units are performing strongly with discharges, and which are falling behind and need more focused support from staff to decrease delays."

Steve Hess, UCHealth

"UCHealth also was looking for a single source of truth for capacity management that could be shared in real time across departments, clinical disciplines and the health system as a whole."

PROPOSAL

So UCHealth implemented iQueue for Inpatient Beds from health IT vendor LeanTaaS. The health system already had been working with LeanTaaS for its operating rooms and infusion spaces.

"This close partnership allowed us the opportunity to co-develop a beds product – iQueue for Inpatient Beds – at our flagship academic hospital, UCHealth University of Colorado Hospital," said Isobel Handler, director of operational intelligence at UCHealth. "Working with the vendor allowed us to translate our capacity management expertise into more meaningful and scalable tools.

"The entire LeanTaaS team took great care to shadow our house supervisors, patient placement, charge nurses and others so they could understand the complexity of our patient flow ecosystem," she added. "During the pandemic, the vendor adapted the tool to meet our new operational needs and provided critical information for our incident command centers."

The iQueue for Inpatient Beds platform is designed to provide real-time data plus predictive and prescriptive analytics that enable operational teams to move away from reactive capacity planning and toward proactive problem solving. 

"This close partnership allowed us the opportunity to codevelop a beds product. Working with the vendor allowed us to translate our capacity management expertise into more meaningful and scalable tools."

Isobel Handler, UCHealth

The solution also is designed to improve patient flow by reducing wait times at key steps along the patient journey and mitigate the chaos historically inherent in managing bed capacity.

MEETING THE CHALLENGE

UCHealth worked with LeanTaaS to implement iQueue for Inpatient Beds at UCHealth University of Colorado Hospital starting in February 2020, and at all 12 hospitals starting in October 2020. 

As a result, UCHealth staff now are able to predict future admissions and discharges, balance beds across the network, hospital and unit, and make strategic decisions to get the right patient in the right bed at the right time, Hess said.

"Using iQueue, UCHeath staff can quickly see, at any time and from any location, capacity status, as well as which units are performing strongly with discharges and which are falling behind and need more focused support from staff to decrease delays," he explained. 

"They also can identify the specific patients who could be discharged soon, and facilitate their discharges as needed."

RESULTS

Across the health system, the organization uses iQueue for Inpatient Beds to run daily bed meetings, perform hourly administrative management and drive capacity protocol standardization, which has noticeably improved patient flow metrics, Handler reported.

Since implementation, she said that UCHealth has seen the following metrics:

• 37% reduction in time to complete ICU transfers
• 8% decrease in opportunity days (difference between med/surg LOS and CMS LOS)
• 4% decrease in time to admit (despite 18% increase in COVID-19 census)
• 90% improved confidence in critical capacity decisions (compared with only 50%)

"Predictions allow UCHealth to be proactive with capacity planning so that it always is actively managing capacity rather than responding to a crisis," she noted. "This is a more successful approach operationally and has made a huge impact on staff and provider satisfaction.

"Additionally, we've observed reductions in discharge delays, which we believe the team was able to achieve during the chaos of the pandemic partially due to support from iQueue tools," she added.

ADVICE FOR OTHERS

In either case, where the EHR or a separate system acts as the patient placement system, the key to better capacity management is getting real-time data, Handler advised. EHRs are great transactional systems but often lack the ability to aggregate this data and visualize the intelligence in a meaningful and actionable manner, she said.

"Capacity management gets very local very fast, so a good tool will allow easy drill-down from hospital-wide summaries to level of care and unit detail," she said. "In our organization, staff and providers with a wide variety of roles use this tool, so it's critical to make it an accessible and flexible user experience."

Capacity management challenges also vary widely from hospital to hospital.

"Some have to closely monitor ICU utilization, while others are more often faced with a dearth of med/surg beds," she concluded. "Some hospitals have a higher tolerance for ED boarding than others, and some have very limited surge capacity compared to their peers. For this reason, it's important to build a tool that can highlight each individual hospital's challenges and triggers to take action."

Twitter: @SiwickiHealthIT
Email the writer: bsiwicki@himss.org
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