Jackson Health reduces mean excess days by 0.42 days with Qventus AI-powered inpatient capacity automation

Jackson Health deployed Machine Learning & Predictive Analytics for Patient Flow & Hospital Operations in Hospital & Health System. As reported by www.qventus.com: 0.42 days mean excess days reduction.

Maintained by Peter Korpak, Lead EditorHow evidence is checked
0.42 daysMean Excess Days Reduction

Source-reported figures (cited source: www.qventus.com)

What Jackson Health was trying to fix

Nearly 25% of all hospital days at Jackson Health were excess days, causing critical capacity loss and margin deterioration. The health system lacked standardized discharge processes, and staff were burdened with outdated manual tasks that made it impossible to positively impact patient flow and outcomes despite significant effort.

What Jackson Health deployed

Jackson Health deployed the Qventus Inpatient Capacity Solution, which combines AI, machine learning, and behavioral science to automate discharge planning and care flow operations. The platform orchestrated the right actions at the right time to promote patient flow and create bed capacity system-wide.

Results

The health system achieved a 0.42-day reduction in mean excess days, directly translating into increased bed capacity and improved margins. The solution enabled enterprise-wide operational transformation that supported Jackson Health's mission of delivering exceptional care to its communities.

Key Takeaways

  • Automating discharge workflows with AI can measurably reduce excess hospital days even in large, complex health systems.
  • Standardizing processes through intelligent automation is more scalable than relying on individual staff heroics.
  • Capacity gains and margin improvements are closely linked when excess days are systematically reduced.

Evidence for Jackson Health's Patient Flow & Hospital Operations deployment

Reported outcome metrics
1 cited below
Cited source
www.qventus.com
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