APCM AI Care Plan Documentation Checklist

AI must confirm at least two identifiers (e.g., DOB, Name) before discussing PHI during automated calls.

Use NLP to extract patient-defined health goals and treatment preferences from natural conversation.

AI should identify social determinants of health and map them to structured EHR fields for risk assessment.

AI sentiment analysis should flag patient-reported barriers like transportation or financial constraints.

Automate the collection of current medication lists and flag discrepancies for clinical review.

Capture and time-stamp patient consent for ongoing AI-led care management and automated outreach.

AI generates a structured care plan draft based on call transcripts for provider sign-off.

Apply AI algorithms to patient data to assign a clinical risk score within the documentation.

Ensure AI-suggested problem lists correspond accurately with current ICD-10 diagnostic codes.

AI flags differences between new patient inputs and existing EHR records to prevent data duplication.

AI sets automated milestones for chronic condition management based on clinical guidelines.

Schedule the next AI outreach touchpoint directly within the care plan documentation.

Verify that all AI-processed care plan data is encrypted using AES-256 at rest and in transit.

AI must log exact minutes spent in patient interaction to support APCM billing requirements.

Confirm that the AI agent can push care plan updates directly to the EHR via secure API.

Implement a mandatory 'human-in-the-loop' step to verify AI-generated summaries before finalization.

Every AI-generated note must include a standard disclaimer regarding its automated origin.

Ensure AI telephonic outreach parameters comply with specific state-level healthcare automation laws.