Ascribe: Closing the gap in clinical documentation

Ascribe: Closing the gap in clinical documentation

An AI solution that supports nurses’ “Shadow Practices,” turning spoken notes, photos, and quick texts into structured documentation.

Role: UX & UI designer

Tools: Figma, Base44

Timeline: 4 weeks

Client: Mount Sinai Health Systems

About this Project

About this Project

This project aims to reimagine how nurses handle documentation by integrating AI into their daily workflow. Instead of relying on handwritten notes or memory, our solution Ascribe provides AI-powered assistant that helps nurses to organize information seamlessly, reducing stress and allowing nurses to focus on patient care. 

This project aims to reimagine how nurses handle documentation by integrating AI into their daily workflow. Instead of relying on handwritten notes or memory, our solution Ascribe provides AI-powered assistant that helps nurses to organize information seamlessly, reducing stress and allowing nurses to focus on patient care. 

Explore Prototype

The Main Problem

The Main Problem

Clinicians spend 34–55% of their time on documentation instead of patients. The result: stress, burnout, and reduced quality of care.

Clinicians spend 34–55% of their time on documentation instead of patients. The result: stress, burnout, and reduced quality of care.

Goal

Goal

To simplify and speed up medical documentation for nurses, reducing workload and minimizing errors through a digital solution.

To simplify and speed up medical documentation for nurses, reducing workload and minimizing errors through a digital solution.

How Might We

How Might We

How might we help the ICU medical staff with their workarounds & Shadow Practices, by developing AI real-time documentation-based tools?

How might we help the ICU medical staff with their workarounds & Shadow Practices, by developing AI real-time documentation-based tools?

JBTD

JBTD

01

When I document during emergency care,

I want to reduce time and effort,

so I can focus on treating patients

02

When I discharge or transfer patients,

I want documentation to be fast and accurate,

so I can ensure smooth care and compliance.

Solution

Solution

Ascribe is an AI-powered assistant that transforms unsafe shadow practices into structured, real-time documentation. It captures photos, voice notes, and checklists at the bedside, reducing cognitive load, preventing errors, and giving clinicians more time with patients.

Key features

01

Smart Photo Capture: snap monitors, IV drips, or glove notes; OCR + AI extract values and log them instantly.

02

Voice-to-Checklists: dictate observations that
auto-convert into structured tasks and clinical fields.

03

Patient-by-Room Organization: entries grouped by bed with automatic timestamps for a clear, reliable timeline.

Target Audience

Target Audience

We focus on critical care nurses, as they carry the heaviest and most time-sensitive documentation burden in high-pressure ICU environments. Streamlining their workflow reduces errors, cognitive overload, and shadow practices. By improving nursing documentation, we also indirectly benefit critical care physicians and care coordinators.

We focus on critical care nurses, as they carry the heaviest and most time-sensitive documentation burden in high-pressure ICU environments. Streamlining their workflow reduces errors, cognitive overload, and shadow practices. By improving nursing documentation, we also indirectly benefit critical care physicians and care coordinators.

Critical Care Physicians

Critical Care Physicians

Responsible for diagnosis & medico-legal notes, benefit from accurate nursing documentation.

Responsible for diagnosis & medico-legal notes, benefit from accurate nursing documentation.

Critical Care Nurses

Critical Care Nurses

Carry the heaviest,
time-sensitive documentation burden.

Our primary persona.

Carry the heaviest,
time-sensitive
documentation burden.

Our primary persona.

Care Coordinators

Care Coordinators

Rely on updated records for smooth discharge and communication.

Rely on updated records for smooth discharge and communication.

User Journey Map

User Journey Map

For the user journey map, I fully customized medical illustrations to align with the specific scenario discussed in the interview with the PICU nurse and clearly reflect how the proposed solution is used.

For the user journey map, I fully customized medical illustrations to align with the specific scenario discussed in the interview with the PICU nurse and clearly reflect how the proposed solution is used.

Design Process

Design Process

01

Brainstorm & Hand Sketches Feature discussion and quick whiteboard notes.

04

Design System & UI Kit
Creating a tailored design system for unified visual language.

02

Quick Prototype in Base44
First test and idea visualization.

02

Quick Prototype in Base44
First test and idea visualization.

03

Wireframing in Figma
Creating detailed screens and low fidelity flows.

05

Implementation to Base44
Exported UI elements from Figma using prompts and plugins.

04

Design System & UI Kit
Creating a tailored design system for unified visual language.

03

Wireframing in Figma
Creating detailed screens and low fidelity flows.

05

Implementation to Base44
Exported UI elements from Figma using prompts and plugins.

06

Bug Fixing & Usability Testing Ensured UI consistency, resolving issues and improving usability.

Final UI

Figma

Figma

Base44

Base44

Final UI

Audio Note Flow

Audio Note Flow

Explore Prototype

Our Team

Our Team

I am very proud of my team gave their best. The biggest challenge, however, was not just meeting deadlines but doing so while maintaining good relationships within the team. I believe this was one of the hardest parts of the process, and I’m proud that we managed it successfully.

I am very proud of my team gave their best. The biggest challenge, however, was not just meeting deadlines but doing so while maintaining good relationships within the team. I believe this was one of the hardest parts of the process, and I’m proud that we managed it successfully.

What did I learn

What did I learn

During the Hackathon, I learned a completely new approach of design that I knew before. Normally, I start by creating something myself in Figma and only then turn to AI vibe coding tools for feedback. This time the process was different. I discovered that this requires a lot of patience, especially when something doesn’t come out the way you want, and you have to keep adjusting until it works. It was both challenging and eye-opening, as it forced me to rethink my design workflow.

During the Hackathon, I learned a completely new approach of design that I knew before. Normally, I start by creating something myself in Figma and only then turn to AI vibe coding tools for feedback. This time the process was different. I discovered that this requires a lot of patience, especially when something doesn’t come out the way you want, and you have to keep adjusting until it works. It was both challenging and eye-opening, as it forced me to rethink my design workflow.

Future Considerations

Future Considerations

We were one of 8 teams awarded the opportunity to present our solution to the medical staff at Mount Sinai in New York. Moreover, we gained the chance to implement the project in collaboration with Wix and Base44. Looking ahead, our next steps include designing a clear onboarding process, aligning UI elements for consistency, and conducting both user testing and QA testing.

We were one of 8 teams awarded the opportunity to present our solution to the medical staff at Mount Sinai in New York. Moreover, we gained the chance to implement the project in collaboration with Wix and Base44. Looking ahead, our next steps include designing a clear onboarding process, aligning UI elements for consistency, and conducting both user testing and QA testing.

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