CARE by MarianaAI

AI Native Clinical Copilot for Documentation and Decision Support

CARE by MarianaAI Clinical copilot interface showing patient encounter workflow

OVERVIEW

Executive Summary

CARE is an AI native clinical copilot platform designed to reduce documentation burden, provide real-time decision support, and streamline downstream administrative workflows for healthcare providers. The product integrates directly with existing clinical systems and EHRs, enabling ambient documentation and AI assistance without disrupting clinician-patient interactions.

This project documents my work on the early design and foundational clinician experience for CARE, with a focus on workflow alignment, explainability, and scalable personalization across specialties. The goal was to design AI assistance that functions as background infrastructure supporting clinical work without adding cognitive or interaction overhead.

DEMO

Product Walkthrough

An interactive walkthrough of the clinician experience is available below, showcasing the core workflows and AI-assisted features designed for CARE.

CARE platform appointments interface showing patient list and calendar

SCOPE

Scope of Work
Documentation

Clinician facing documentation and review workflows

Real-time Support

Real-time AI assisted decision support patterns

Human in the loop

Human in the loop control and validation

EHR Integration

UX considerations for deep EHR integration

APPROACH

Design Principles

The design approach centered on creating AI assistance that functions as background infrastructure supporting clinical work without adding cognitive or interaction overhead. Key principles guided the work:

Workflow Alignment

Designing AI features that integrate seamlessly into existing clinical workflows rather than creating parallel processes.

Explainability

Ensuring AI suggestions are transparent and traceable, building trust through clear reasoning and source attribution.

Scalable Personalization

Creating adaptive experiences that learn from individual clinician preferences while maintaining consistency across specialties.

Minimal Cognitive Load

Reducing interaction overhead so clinicians can focus on patient care rather than managing AI tools.

Additional Details

Due to the sensitive nature of healthcare product development, detailed design artifacts and research findings are available upon request in a confidential context. Feel free to reach out at raza2393@gmail.com.