Case Study: Phoenix Children's Hospital achieves rapid predictive insights—uncovering 4–5 at-risk children weekly and preventing 9,000 missed appointments annually with DataRobot

AI Elevates Patient Care at Phoenix Children’s

Phoenix Children’s Hospital wanted to use analytics to improve clinical and operational decisions but found that manually building a single predictive model took about nine months, making the effort unsustainable. To accelerate and democratize predictive analytics, Phoenix Children’s Hospital turned to DataRobot, deploying DataRobot’s AI Foundation and Predictive AI on-premises and integrating the platform with its Microsoft data and Power BI environment.

DataRobot automated model development so non‑data scientists can produce viable models in minutes; Phoenix Children’s Hospital now uncovers 4–5 children at risk of malnutrition each week, flags about 25 likely no-shows daily (preventing roughly 9,000 missed appointments per year), and uses forecasts to better staff emergency care. By deploying DataRobot on-prem and integrating it with existing systems, the hospital cut model timelines from months to days and achieved measurable clinical and operational impact.

Phoenix Children’s Hospital

David Higginson

Executive Vice President, Chief Innovation Officer