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Overview

HANA’s voice engagement framework provides extensive customization capabilities to adapt to the specific needs of healthcare organizations, clinical specialties, and individual patients.

Personalization Dimensions

Organization-level Settings

  • Brand Alignment: Customizable voice persona and greeting language to match healthcare organization’s identity
  • Terminology Adaptation: Support for organization-specific medical terminology and abbreviations
  • Workflow Integration: Tailored insertion points within existing clinical processes (scheduling, intake, follow-up)
  • Security Controls: Granular access management aligned with organizational policies
  • Operating Hours: Configurable call scheduling, after-hours behavior, and retry policies

Specialty-specific Customization

  • Specialty Protocols: Pre-configured conversation templates for 20+ medical specialties
  • Condition-specific Content: Tailored conversation flows for common conditions within each specialty
  • Assessment Instruments: Specialty-appropriate screening tools (PHQ-9, GAD-7, AUDIT-C, CAGE-AID, etc.)
  • Regulatory Compliance: Specialty-specific documentation requirements built into protocols
  • Billing Integration: CPT/HCPCS code suggestions relevant to each specialty and conversation type

Individual Patient Preferences

  • Language: Primary language detection and preference storage; clinically validated for English, Spanish, Italian, French, and German with additional languages available at varying coverage levels
  • Communication Style: Adjustable pacing, detail level, and formality based on patient profile
  • Contact Preferences: Best time to call, preferred channel (voice, SMS), callback scheduling
  • Personal Templates: Patient-specific conversation adjustments that persist across interactions
  • Learning Adaptation: System adapts to individual communication patterns over time

Personalization Infrastructure

Longitudinal Memory Architecture

HANA builds a patient interaction profile that grows richer with every conversation. This is distinct from EHR data — the organization’s clinical systems remain the source of truth for medical information. HANA’s memory layer captures interaction intelligence: how to communicate with each patient most effectively. Memory Layers:
LayerSourcePurpose
Clinical contextEHR (pulled fresh before each call)Diagnoses, medications, care plans, appointments
Communication preferencesLearned from interactionsChannel preference, best time to call, pacing, formality level
Conversation historyBuilt by HANAPrior topics discussed, goals set, issues flagged
Behavioral patternsObserved over timeResponse style, engagement triggers, dropout risk signals
Vocal baselineVocal intelligence engineProsodic profile for longitudinal deviation detection
How Memory Improves Conversations:
  • A patient who prefers texts over calls gets SMS outreach first
  • A patient with lower health literacy gets simpler language and more confirmation checks
  • A chronic care patient’s third monthly check-in references what was discussed in the first two
  • A patient who expressed frustration about insurance in a prior call gets a more empathetic tone when the topic comes up again

Patient Profile Management

  • Preference Persistence: Secure storage of patient settings across conversations and channels
  • Role-based Defaults: Initial settings based on clinical protocol and patient demographics
  • Preference Portability: Settings follow patients across departments, locations, and provider changes
  • Version Compatibility: Patient preferences maintained through system updates

Personalization Workflow

  • Guided Setup: Interactive onboarding for initial organization and protocol personalization
  • Continuous Refinement: Ongoing opportunities to adjust preferences based on conversation outcomes
  • Clinician Input Integration: Clinical staff can annotate patient profiles with notes about communication preferences, sensitivities, or context that enriches future conversations — similar to how care teams pass notes between shifts
  • Preference Analytics: Insights into which personalization options improve engagement and completion rates
  • Protocol Sharing: Ability to share effective protocol configurations within organizations

Technical Implementation

  • Efficient Caching: Local caching of personalization settings for fast conversation initialization
  • Synced Preferences: Real-time synchronization across channels (voice, SMS) and sessions
  • Fallback Handling: Graceful defaults when personalization data is unavailable
  • Performance Optimization: Minimal impact on conversation response latency regardless of personalization level
  • Privacy Compliance: All preference data encrypted, auditable, and deletable per patient request
  • Data Ownership: Patient interaction data belongs to the healthcare organization. HANA processes and stores it per the organization’s retention policies and provides full export capability.