AI Consulting for Healthcare in Michigan

Risk tiering models combine clinical data (diagnoses, utilization history, treatment patterns) with contextual factors like social determinants of health to score patients by likelihood of adverse events such as avoidable ED visits. These scores are embedded into care manager workflows so they can prioritize outreach and adjust visit frequency for rising-risk patients before a crisis occurs.

Yes. AI can assist with clinical note summarization, structured data extraction from unstructured notes, and draft documentation that clinicians review and approve. This reduces the hours clinicians spend on documentation while maintaining accuracy. We design these systems with human-in-the-loop review for patient safety.

Healthcare AI requires strict data handling. We work with de-identified or minimum-necessary datasets, use HIPAA-compliant infrastructure, implement role-based access controls, and maintain audit trails. For AI API usage, we use enterprise agreements that include BAAs (Business Associate Agreements) and ensure no patient data is used for model training.

Yes. While we're based in Southeast Michigan and can meet in person across the metro Detroit area, we work with healthcare companies nationwide. Most engagements are hybrid—combining in-person workshops with remote collaboration.