University Health Reduces ED Boarding Time by 46%

16% Increase in discharge volume
46% Reduction in ED boarding time
16% Increase in admission volume
9% Increase in ED visit volume

Summary

University Health is an academic health system in San Antonio, Texas, currently operating one hospital with 1,255 licensed beds and 48 ORs. As a Level I trauma center, the system serves a high-volume patient community with steadily increasing adult admissions and ED visits.

To reduce length of stay, improve ED throughput, and optimize capacity without adding beds, University Health partnered with LeanTaaS to implement predictive patient flow capabilities.

Profile

48 ORs; 1,255 licensed beds

One hospital; 3 acute surgery centers

Academic Health System

Epic® EHR

Problem

University Health faced a common challenge: its ED was backed up with long hold times, but the root cause wasn’t in the emergency department itself.

The health system was managing operations from hindsight using dashboards that showed yesterday’s problems when it was too late to act. Despite trying multiple approaches to improve ED flow—optimizing triage and adjusting staffing—improvements wouldn’t last. Opening additional beds only filled them without solving the underlying throughput issue.

With adult admissions and ED visits climbing steadily month after month, the organization needed to predict and prepare for demand rather than simply react to it. University Health lacked visibility into barriers to discharge and couldn’t forecast surge capacity needs.

Solution

University Health implemented iQueue for Inpatient Flow to transform how it manages patient throughput. The AI-based system integrates data from its EHR to provide predictive discharge recommendations and early visibility into daily demand.

From day one, clinical teams trusted the data because of rigorous validation during implementation. The health system restructured its morning huddles around the predicted discharge numbers, with flash rounds identifying barriers early in the day.

Staff across EVS, transport, case management, and nursing aligned on shared discharge goals visible to the entire enterprise. The system automatically flagged candidates for the transition to care lounge and hospital at home program.

The LeanTaaS team’s clinical backgrounds and seamless implementation approach helped bridge the gap between operations and IT, making data collection and interpretation straightforward for go-live.

Everything LeanTaaS said they were going to do, they did, plus more that we didn’t even see coming. When a promise turns into a reality, that’s just a no brainer.
Bill Phillips
Executive Vice President, Chief Operating Officer at University Health

Download the full iQueue for Inpatient Flow case study booklet

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