You can’t control policy. But you can control mid-cycle performance. Your biggest lever for financial resilience. AKASA GenAI gives health systems the ability to:
AKASA GenAI is trained on 43M+ clinical documents and refined specifically for mid-cycle tasks like coding and CDI. Each model is trained on your health system’s documentation patterns, case mix, and specialties — ensuring the most accurate, relevant results possible.
Unlike human-driven reviews and rules-based tools, AKASA analyzes 100% of encounters and identifies missed documentation, unsupported codes, and quality risks. Every suggestion is backed by clinical references, with quotes and links directly to the chart. We show our work.
AKASA improves DRG accuracy, reduces denial risk, and strengthens quality metrics. With just minutes of review time per case, you ensure accurate, compliant financial performance — without adding headcount or disrupting workflows.
Medicaid funding cuts are accelerating, and health systems must act fast. In this expert post, AKASA co-founder and healthcare economist Ben Beadle-Ryby shares a practical plan for protecting margins with GenAI.