Case Study: Phoenix Children's fills 9,000 appointments annually with DataRobot AI
Key results
The challenge
Phoenix Children's wanted to use analytics to improve both clinical and operational decisions, but manually building a single predictive model took the better part of a year — roughly nine months — making the approach neither scalable nor sustainable.
The solution
The healthcare system adopted the DataRobot AI Platform to automate much of its predictive analytics, enabling business and IT users to reach viable models without a dedicated data-science team.
“The return both clinically and financially with DataRobot has far exceeded the cost. You can't put a price on improving a child's life.”
DHDavid HigginsonExecutive Vice President, Chief Innovation Officer at Phoenix Children's
The results, in context
Non-data scientists at Phoenix Children's now reach viable models in minutes. By predicting possible malnutrition the organization surfaces 4-5 at-risk children each week, and it proactively fills 9,000 appointments annually that might otherwise be missed.