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Baptist Health Arkansas

Baptist Health Arkansas increases patient transfers by 23% with LeanTaaS AI-powered inpatient flow optimization

Curated & reviewed by Peter Korpak, Founder & Chief Analyst, 100SignalsHow we verify
23%Patient Transfers Increase
32%Discharge Processing Time Reduction
34%GMLOS Variance Reduction

Vendor-reported figures — source: leantaas.com

Baptist Health Arkansas
Metric Before After Impact
Patient Transfers 23% increase Improved system-wide flow with 13% fewer transfer declines
Discharge Processing Time 32% reduction Faster discharge with 11–14% more early orders
GMLOS Variance 34% reduction More predictable length of stay; 25% fewer opportunity days
Overall Admissions 6% increase Increased admission volume and system capacity

The Challenge

Baptist Health Arkansas, operating 10 acute-care hospitals with ~2,500 licensed beds, struggled with inconsistent discharge planning, lack of data transparency, and siloed decision-making across individual hospitals. Despite implementing a system-wide operations command center, disparate processes created bottlenecks and limited centralized operational efficiency. The organization needed to shift from a reactive to a proactive decision-making model to improve patient access and system-wide coordination.

The Solution

Baptist Health implemented LeanTaaS' iQueue for Inpatient Flow, starting with flagship Little Rock and North Little Rock hospitals and the command center, then expanding to Conway and Fort Smith campuses. The platform provided AI-driven discharge date predictions, real-time patient status visibility, shared dashboards, and automated escalation alerts. This created a unified source of truth for capacity protocols, enabling standardized care transitions and proactive bottleneck resolution across the network.

Results

The implementation delivered a 23% increase in patient transfers and a 13% reduction in transfer declines, significantly improving system-wide flow. Discharge processing time was reduced by 32%, with early order entry before 11am increasing by 11% and before 2pm by 14%. The health system also achieved a 34% reduction in GMLOS variance, a 25% reduction in opportunity days, and a 6% increase in overall admissions.

Key Takeaways

  • Centralizing capacity visibility across previously siloed hospitals through a single platform enables proactive transfer management and reduces transfer declines.
  • AI-driven discharge predictions combined with shared dashboards and automated escalations align multi-disciplinary teams around discharge priorities, accelerating patient throughput.
  • Phased rollout starting with flagship facilities and command center before expanding to additional campuses allows for iterative adoption and system-wide standardization.

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Quality
Curated
Last verified
Jul 28, 2026

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