HonorHealth saves $69M and creates 181 beds of capacity with Qventus AI-powered care operations
HonorHealth deployed Machine Learning & Predictive Analytics for Patient Flow & Hospital Operations in Hospital & Health System. As reported by www.qventus.com: $69M cost savings from reduced excess days.
Source-reported figures (cited source: www.qventus.com)
What HonorHealth was trying to fix
HonorHealth, a six-hospital non-profit integrated health system in Arizona, struggled with inefficiencies in patient flow that limited inpatient bed capacity and increased length of stay. Built-in EHR functionality was insufficient to achieve their goals across surgical volume growth, OR utilization, and inpatient capacity management. Pre- and post-surgical coordination was bogged down by manual processes, paperwork, and administrative tasks that led to avoidable surgery cancellations and left PAT staff with little time for direct pre-op care.
What HonorHealth deployed
HonorHealth deployed Qventus' AI platform enterprise-wide across three solution areas. The Surgical Growth Solution provided a digital OR booking interface and ML-powered block release nudges that predict unused blocks and automatically route freed time to best-fit surgeons based on case type and history. The Inpatient Capacity Solution used Disposition Intelligence — localized ML algorithms that auto-populate estimated discharge dates from EHR data — alongside Flow Prioritization to sequence care orders for optimal patient flow. The Perioperative Care Coordination Solution gave PAT staff AI Teammates that handle chart summarization, patient record retrieval, risk stratification, and patient outreach via text, email, and phone.
Results
HonorHealth achieved $69M in savings by reducing excess patient days and created 181 beds of additional inpatient capacity. The health system added 224 incremental surgeries per month and realized a 9.6x return on investment. Flow Prioritization drove a 7% increase in completion of high-priority orders, correlating to 0.4 fewer excess days per patient.
Key Takeaways
- Enterprise-wide AI deployment across surgical, inpatient, and perioperative care compounds ROI beyond what any single point solution can deliver.
- ML-powered nudges that provide block owners with context about utilization likelihood and the downstream impact of releasing time are more effective than manual OR scheduling processes.
- AI Teammates that absorb administrative PAT tasks — record retrieval, patient communication, chart summarization — allow nurses to operate at the top of their license and improve pre-op care quality.
Evidence for HonorHealth's Patient Flow & Hospital Operations deployment
- Reported outcome metrics
- 3 cited below
- Cited source
- www.qventus.com
- Last updated
- Source link checked
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- Industry
- Hospital & Health System
- AI Technology
- Machine Learning & Predictive Analytics
- Company Size
- Enterprise
- Company
- HonorHealth
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