Data-driven diagnostic and predictive app for improving infant outcomes.
Astarte Medical is a precision nutrition company that turned to us to build software based on proprietary predictive analytics. The solution is meant to improve outcomes for preterm infants with a suite of digital tools and diagnostics.
We had to build a forecasting & tracking web application for the infants’ treatment plans from scratch.
MAIN COMPONENTS MEANT TO BE:
- AI-based suggestions for feeding time, amount, and constituents
- Graphs and tools to monitor feeding
- A thorough interface to track infant growth.
To standardize feeding, optimize nutrition, and quantify gut health of preterm infants with our app, we implemented:
- Integrations with various protocols to suggest feedings for babies based on the clinical indicators, growth speed and other historical data (like previous feedings)
- Tracking of the protocol suggestion modifications
- Central identity server
- Rounding report tab to show consolidated information about the patient
- Analytics (with charts) for organization performance metrics visualization
- Epic EHR integration
- Ability to download data/reports.
Core to Astarte Medical is their comprehensive and proprietary dataset, which integrates feeding protocols, microbiome profiles, and clinical information. We synchronized it with the web application making it generate actionable suggestions in the form of a decision tree.
- Infant parameters are logged into the app which measures the Protocol compliance for tracking & optimizing their nutrition.
- Decision tree – AI-based platform that suggests a diet based on the lessons learned from the previous cases