Halie Kwon

Gates Foundation

Anne Maternal — Maternal Patient Monitoring System

Anne Maternal is a sensor-driven monitoring platform designed to support clinical decisions during labor in LMICs. By enabling better risk assessment and timely C-section decisions, it aims to improve outcomes for mothers and newborns. I led the design of the integrated monitoring solution used in hospitals across Nigeria, India, and Pakistan.

Red Dot Design Award

Healthcare

Mobile

ROLE

Design Lead

OUTCOME

2.5 hrs saved in charting time per shift
87% reported improved workflow
91% rated the system easy to use

TIMELINE

Sep 2024 - Apr 2025

TEAM

1 Product Manager, 1 Project Manager

1 Engineer Lead, 1 System Engineer

Quality Team, Regulatory Team

Problem

Did you know nearly 300,000 women die each year from childbirth and 94% are in LMICs?

When every minute matters, paper fails. In many LMICs, over 75% of clinicians still record patient vitals by hand. This manual process is time-consuming, error-prone, and delays urgent decisions—especially during labor. Without access to real-time data, care teams rely on fragmented notes and memory. Clinical scoring systems like MEOWS (Modified Early Obstetric Warning Score) and LCG (Labour Care Guide) also require hours of manual tracking, adding to the pressure on already overextended providers.

Solution

Designing for Clarity in Critical Moments

I led the end-to-end design of a product that replaced manual charting with real-time vitals from wearable sensors. By automating MEOWS and LCG scoring, the system reduced clinical workload and enabled faster, more confident decisions during labor.

User testing revealed the importance of factoring in preexisting conditions. I introduced category and time-based sorting in the LCG screen to help clinicians surface risk more quickly. Built-in tutorials supported onboarding and ease of use in low-resource settings.