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Health First

Health First Eliminates 517 Avoidable Days/Month and Reduces Core Floating Staff by 44% with AI-Powered Inpatient Flow

Curated & reviewed by Peter Korpak, Founder & Chief Analyst, 100SignalsHow we verify
517 daysAvoidable Days Eliminated Monthly
6 hoursLength of Stay Reduction Per Patient
44%Reduction in Core Floating Staff

Vendor-reported figures — source: leantaas.com

Health First
Metric Before After Impact
Avoidable Inpatient Days Monthly 517 eliminated 517 avoidable days eliminated monthly
Length of Stay Per Patient 6-hour reduction 6-hour reduction
Core Floating Staff 44% reduction 44% reduction
Manual Data Collection Workload 200 hours/week eliminated 200 hours weekly reduction

The Challenge

Health First, a 4-campus Florida health system with 900 beds and 50,000 annual discharges, struggled to streamline patient flow across its large footprint. Multi-functional teams traditionally operated independently, creating siloed workflows and communication gaps. Manual processes for discharge management, nurse staffing coordination, and capacity planning were inefficient and limited cross-team collaboration.

The Solution

Health First deployed LeanTaaS iQueue for Inpatient Flow across three operational areas. For discharge management, the platform automated workflows and used predicted discharge barriers (missing labs, post-acute care needs) to prioritize patients. For nurse staffing, AI-driven demand forecasting combined with real-time visibility into float history enabled proactive staffing across all units. For capacity management, AI-enabled situational awareness empowered nurses, hospitalists, radiology, and transport services to coordinate in daily huddles using shared real-time data.

Results

Health First eliminated 517 avoidable inpatient days per month and achieved a 6-hour reduction in length of stay per patient. Core floating staff across the health system was reduced by 44%, reflecting dramatically improved staffing efficiency. Manual data collection and phone call workload was reduced by 200 hours weekly, freeing clinical staff for direct patient care.

Key Takeaways

  • AI-driven demand forecasting enables proactive nurse staffing, reducing reactive float reliance and cutting floating staff needs by nearly half.
  • Replacing manual discharge coordination with automated barrier prediction directly shortens length of stay and eliminates avoidable days at scale.
  • Centralizing real-time visibility across all units and support services (radiology, transport) is the foundation for enterprise-wide throughput improvement.

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Details

Company Size
Enterprise
Quality
Curated
Last verified
Jul 28, 2026

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