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UCHealth Decreased Overall Time to Admit by 16%

Summary

UCHealth is an integrated healthcare delivery system serving Colorado, southern Wyoming, and areas of Nebraska. The system consists of 12 hospitals with a total of 1,997 inpatient hospital beds and performs over 141,000 admissions and observation visits per year.

Problem

The analytics tools UCHealth relied on to manage inpatient throughput, created internally, pulled from an extensive amount of data and highlighted users’ knowledge and expertise. But these required daily labor-intensive preparation and did not provide managers and frontline workers with the real-time information they needed to make important decisions about patient placement and patient flow. They were also not equipped to provide predictions of what would happen in the future. As a result, the daily process of managing inpatient capacity was chaotic.

UCHealth needed a solution to eliminate guesswork from the inpatient decision-making process, to help teams manage today’s needs and strategize for tomorrow. Further, UCHealth 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. 

Solution

Before the onset of COVID-19 made inpatient management especially critical, UCHealth had already partnered with LeanTaaS to implement iQueue for Inpatient Flow. The flagship University of Colorado Hospital went live with the solution in February 2020, and UCHealth implemented new processes and structures to support user adoption of the technology. 

Using iQueue’s predictive analytics tools, UCHealth inpatient staff became quickly able to plan for future admissions and discharges, balance beds across the network, hospital, and unit, and make data-based decisions to ensure the right patient was placed in the right bed at the right time. They also used iQueue to support unique strategies, such as assigning appropriate primary and secondary units for patient placement, to keep capacity flexible during times of unpredictable surges. 

iQueue for Inpatient Flow was expanded to the 11 remaining UCHealth hospitals through October 2020. Patient flow metrics noticeably improved, and the solution continues to drive alignment across the UCHealth network to facilitate patient flow and throughput. Across the system, the daily chaos associated with a previously manual and labor intensive process has significantly decreased, while inpatient metrics have improved. 

Key Takeaways

01

Describe the daily challenges faced by hospital staff in managing inpatient throughput

02

Recognize how predictive analytics tools support inpatient bed decisions

03

Understand the importance of customized processes in adopting new technology across an organization

04

Apply external technology to support solutions created to address unique organizational challenges

Results

65% decrease in time to complete ICU Transfers
8% decrease in opportunity days
16% decrease in overall time to admit
10% decrease in in time to admit from the ED (despite 18%+ increase census)
Hospital executives need…access to historical and real-time data to inform a proactive… approach to patient throughput. Operational leaders need…a good understanding of patient demand and organizational bed capacity by level-of-care and specialty service. Frontline clinical teams need tools that provide situational awareness and drive standard work to decrease the cognitive load and chaos they navigate day-to-day. iQueue for Inpatient Flow checks all of these boxes. It has been an instrumental tool to facilitate smooth patient flow and hardwire daily operations across UCHealth.
Jamie Nordhagen
Senior Director of Patient Flow and Capacity Management, UCHealth

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Download the full iQueue for Inpatient Flow case study booklet

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