HIPAA-First AI Enablement + an LLM Workflow that Improved Revenue Cycle Collections

Challenge

AI adoption in healthcare is often blocked by legitimate concerns: HIPAA, privacy, security, and auditability. Leaders needed a practical enablement model that let teams move fast—while staying defensible. In parallel, revenue cycle collections presented a clear, high-impact opportunity where better workflow support could improve outcomes without introducing patient safety risk.

What we did

• Designed and launched HIPAA-compliant AI and cloud literacy programs for leaders and operators.
• Established governance patterns for secure AI adoption (repeatable approvals, controls, and checklists).
• Deployed an LLM-based payer negotiation workflow focused on collections uplift, with appropriate oversight.
• Scaled enablement to expand the portfolio of ROI-generating AI programs.

Results

• Expanded the number of ROI-generating AI programs by ~30×.
• Delivered a targeted LLM workflow that increased collections by ~23%.

Strategic impact

This created a repeatable 'safe acceleration' operating model: training + governance + deployable workflows. Instead of treating AI as one-off pilots, the organization gained a scalable way to build, approve, and adopt AI solutions in a regulated environment.

Optics + governance

• HIPAA-first posture: privacy and compliance were design inputs, not afterthoughts.
• Positioned AI as workflow augmentation, not workforce reduction.
• Built for audit readiness with governance checklists and repeatable controls.