I was given an exercise to research and understand what major challenges is the health care system of the United sates undergoing.

Through analysis, research, interviews and data collecting I understood that one of the top complaints amongst doctors, physicians, nurses and patients is the way that the Electronic Health Records system is organized.

Unstructured data and difficult time-consuming paperwork make it difficult to locate patient records and frustrating to interact with the current EHR system.

Instead of listening to patients, doctors spend most of the time completing EHR tasks.

Developing a theoretic solution, ATLAS - an A.I.-powered “co-pilot” created to solve some of these challenges, plus enabling doctors and patients some extra features to maximize their personal relationship, was a very interesting challenge.

By listening to doctors interviewing patients, analyzing the words used and taking insights from historical data and artificial neural networks, ATLAS is able to understand the context and patterns in conversations thus creating standard easy-to-access EHR reports that will be interoperable between systems. 

ATLAS records conversations between patients and doctors, produces instant EHR standard reports and gives patients access to the EHR database so they can manage their data access.

When ATLAS communicates with the EHR database it combines historical data, finds patterns and improves accuracy and quality so it becomes easier with time to interact with the system.