> ## Documentation Index
> Fetch the complete documentation index at: https://docs.hana.health/llms.txt
> Use this file to discover all available pages before exploring further.

# User-level Personalization

> Extensive customization capabilities adapting to the specific needs of healthcare organizations, departments, and individual patients.

## 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:**

| Layer                     | Source                              | Purpose                                                        |
| ------------------------- | ----------------------------------- | -------------------------------------------------------------- |
| Clinical context          | EHR (pulled fresh before each call) | Diagnoses, medications, care plans, appointments               |
| Communication preferences | Learned from interactions           | Channel preference, best time to call, pacing, formality level |
| Conversation history      | Built by HANA                       | Prior topics discussed, goals set, issues flagged              |
| Behavioral patterns       | Observed over time                  | Response style, engagement triggers, dropout risk signals      |
| Vocal baseline            | Vocal intelligence engine           | Prosodic 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.