Data Scientists in healthcare are often building very successful models that are leading to healthier patients and reduced costs. However, we also tend to hear: -Cleaning up messy data and feature engineering prohibit Data Science teams from practicing at the top of their license -Models are difficult to explain to the clinical side of the house, causing a lack of trust in the scores -Operational deployment is not exactly a click of a button -Team members are all working on the same model, and versions are difficult to manage

Healthcare data is messy, let us find the signal. ClosedLoop uses all available data points to inform our risk scores, predictions and recommendations on an individual patient basis. Incomplete records? Small population? No problem. ClosedLoop leverages all your data streams including EHR, clinical notes, labs, pharmacy, claims, health risk assessments, device data and more. Our AI platform learns from patterns in your data along with millions of health records in our own data warehouse to generate more accurate predictions and recommendations.