Tech

Responsible AI, Data‑Driven Decision‑Making and Industry Collaboration Key Themes at AGILE 2026

At AGILE 2026, the home-care industry’s shift to AI-driven clinical workflows took center stage, with 800 executives debating how federated learning models—trained on de-identified EHR data from 12,000 agencies—can now predict hospital readmissions 48 hours earlier than legacy rule-based systems. The spotlight fell on Axxess’s new “Care Orchestrator” agent, which autonomously re-routes visit schedules in real time using reinforcement learning, cutting missed-care events by 37% in pilot markets.

At AGILE 2026, the home-care industry’s shift to AI-driven clinical workflows took center stage, with 800 executives debating how federated learning models—trained on de-identified EHR data from 12,000 agencies—can now predict hospital readmissions 48 hours earlier than legacy rule-based systems. The spotlight fell on Axxess’s new “Care Orchestrator” agent, which autonomously re-routes visit schedules in real time using reinforcement learning, cutting missed-care events by 37% in pilot markets.

Overview

AGILE 2026, the Axxess Growth, Innovation and Leadership Experience, brought together more than 800 leaders from home health, hospice and home care in Dallas. The three-day conference featured 13 educational sessions and six immersive workshops led by more than 60 faculty members, alongside participation from more than 60 sponsors.

What was announced

Axxess unveiled three new AI-powered agents as part of the Axxess intelligence ecosystem:

  • Ambient Agent – captures clinical notes from natural conversation during visits.
  • Intake Agent – automates patient intake and eligibility verification.
  • Billing Agent – handles claims processing and denial management.

These join the previously announced “Care Orchestrator” agent, which uses reinforcement learning to dynamically re-route visit schedules. In pilot markets, it reduced missed-care events by 37%.

Axxess also released new business intelligence dashboards and enhancements to its interactive Ask Axxess feature, which now supports connected workflows and interoperability across care-at-home operations.

Federated learning for readmission prediction

A key technical discussion at AGILE 2026 centered on federated learning models trained on de-identified EHR data from 12,000 agencies. These models can predict hospital readmissions 48 hours earlier than legacy rule-based systems, according to conference materials. The approach keeps patient data local to each agency, training the model across distributed datasets without centralizing sensitive information.

Responsible AI and governance

Throughout the conference, speakers emphasized responsible AI adoption with clear oversight. Axxess Founder and CEO John Olajide stated in his opening remarks: “The future of care at home depends on how well we work together to apply technology in ways that truly help organizations grow and deliver better care.”

Panelists repeatedly stressed that AI should reduce administrative burden and support clinical decision-making while preserving human judgment. Sessions covered practical execution, governance and collaboration amid rapid technological change and increasing operational complexity.

Awards and next event

AGILE 2026 included the AGILE Distinction Awards, recognizing 11 organizations for leadership and excellence. Bill Dombi received the David Merk Enduring Legacy Award for his contributions to advancing the industry.

AGILE 2027 is scheduled for May 3-5 in Dallas. Registration is open.

Bottom line

Axxess is expanding its AI agent lineup beyond scheduling into clinical documentation, intake and billing. The federated learning approach for readmission prediction addresses a key pain point for home-care agencies: reducing hospital returns while maintaining data privacy. Providers should evaluate whether these agents integrate with their existing EHR systems and whether the 37% reduction in missed-care events translates to their specific patient populations.

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