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

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.

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.

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.

• 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.