Leading Indianapolis Health System reduces ED boarding 45% through LeanTaaS-powered departure lounge optimization

Leading Indianapolis Health System deployed Machine Learning & Predictive Analytics for Patient Flow & Hospital Operations in Hospital & Health System. As reported by leantaas.com: 45% (20 hrs → 11 hrs) ed boarding reduction.

Maintained by Peter Korpak, Lead EditorHow evidence is checked
45% (20 hrs → 11 hrs)ED Boarding Reduction
250% (10 → 35 patients/day)Departure Lounge Utilization Increase
18%Discharge Processing Time Variance Reduction

Source-reported figures (cited source: leantaas.com)

Leading Indianapolis Health System
Metric Before After Impact
ED Boarding Time 20 hours 11 hours 45% reduction
Departure Lounge Utilization 10 patients/day 35 patients/day 250% increase
Discharge Processing Time Variance — Reduced 18% 18% variance reduction

What Leading Indianapolis Health System was trying to fix

This Indianapolis acute care health system experienced significant ED boarding challenges, where admitted patients remained in the ED due to insufficient inpatient bed availability. This resulted in extended patient wait times, inefficient use of ED resources, inconsistent discharge processes, and suboptimal utilization of an existing departure lounge.

What Leading Indianapolis Health System deployed

From November 2023 to June 2024, the health system implemented a multi-faceted departure lounge optimization initiative using LeanTaaS iQueue for Inpatient Flow. This included physical space redesign, specialized staff training on discharge procedures, early multidisciplinary discharge planning starting at admission, and a real-time software system to track bed availability, predict discharges, and manage departure lounge capacity.

Results

The initiative achieved a 45% decrease in ED boarding, reducing average boarding time from 20 hours to 11 hours per patient. Departure lounge utilization increased 250%, rising from an average of 10 patients per day to 35. Discharge processing time variance was reduced by 18%, with the organization planning to expand the model to additional facilities.

Key Takeaways

  • A holistic approach combining physical redesign, staff training, technology integration, and patient education is essential for sustainable patient flow improvement.
  • Real-time predictive analytics for bed availability and discharge forecasting are critical enablers of proactive capacity management.
  • Empowering staff with streamlined discharge workflows reduces administrative burden and allows more focus on direct patient care.

Evidence for Leading Indianapolis Health System's Patient Flow & Hospital Operations deployment

Reported outcome metrics
3 cited below
Cited source
leantaas.com
Last updated
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