HonorHealth saves $62M and cuts LOS by 0.65 days with Qventus AI-powered inpatient capacity management

HonorHealth's six-hospital Arizona health system was experiencing inefficient patient flows resulting in excess days and a poor patient experience. Staff lacked real-time decision-support resources, contributing to burnout. Delays in care progression were systemic, and built-in EHR functionality failed to provide the efficiency or quality of insights needed to address them.

HonorHealth implemented the Qventus Inpatient Solution across all six hospitals starting in 2021. The platform uses AI and ML models to predict estimated discharge dates (EDD), identify discharge barriers, and surface next-best-action recommendations. Key modules include Disposition Intelligence and Automation (auto-populating EDD and dispositions), Care Progression Manager (streamlining MDRs), Flow Prioritization (sequencing orders to maximize throughput), and an Insights Suite for leadership accountability.

86% of patients now receive an early discharge plan — a 72% increase from pre-implementation. LOS was reduced by 0.65 days per patient on average, generating 50,673 cumulative days saved over three years. The system auto-populated 62,259 EDDs and 38,173 dispositions, eliminating over 260,000 manual clicks. $62M was saved by reducing excess days.

• Early discharge planning at scale (86% coverage) requires automated prediction and workflow integration, not just data access.
• Automating repetitive clinical documentation tasks (EDD, disposition entry) meaningfully reduces care team burden and accelerates discharge workflows.
• AI-driven flow prioritization — sequencing which orders to complete first — has measurable LOS impact even before discharge planning is complete.