DataRobot > Case Studies > AI Elevates Patient Care at Phoenix Children’s

AI Elevates Patient Care at Phoenix Children’s

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Customer Company Size
Large Corporate
Region
  • America
Country
  • United States
Product
  • DataRobot AI Cloud
  • AutoML
  • AutoTS
Tech Stack
  • Microsoft Power BI
Implementation Scale
  • Enterprise-wide Deployment
Impact Metrics
  • Productivity Improvements
  • Customer Satisfaction
Technology Category
  • Analytics & Modeling - Predictive Analytics
Applicable Industries
  • Healthcare & Hospitals
Applicable Functions
  • Quality Assurance
  • Business Operation
Use Cases
  • Predictive Maintenance
  • Remote Patient Monitoring
Services
  • Data Science Services
About The Customer
Phoenix Children’s is one of the nation’s largest pediatric health systems. It comprises Phoenix Children’s Hospital–Main Campus, Phoenix Children’s Hospital–East Valley at Dignity Health Mercy Gilbert Medical Center, four pediatric specialty and urgent care centers, 11 community pediatric practices, 20 outpatient clinics, two ambulatory surgery centers, and six community service-related outpatient clinics throughout the state of Arizona. The system has provided world-class inpatient, outpatient, trauma, emergency, and urgent care to children and families for more than 38 years. Phoenix Children’s Care Network includes more than 850 pediatric primary care providers and specialists who deliver care across more than 75 subspecialties.
The Challenge
Phoenix Children’s is one of the nation’s largest pediatric health systems. It provides world-class inpatient, outpatient, trauma, emergency, and urgent care to children and families for more than 38 years. The organization is continuously at the forefront of innovation and is recognized among the nation’s top-ranked children’s hospitals. Phoenix Children’s wanted to use analytics to improve both clinical and operational decisions. However, manually building a single model took the better part of a year. The healthcare system knew that a certain percentage of children who present with other health concerns may actually have undiagnosed malnutrition. If they could identify cases of malnutrition, they could intervene and influence outcomes.
The Solution
Phoenix Children’s turned to DataRobot AI Cloud to automate its predictive analytics and for ease of use for business and IT users. The solution was deployed on-premise and integrated with the hospital’s Microsoft data and analytics suite, including Microsoft Power BI. The project was up and running within a couple of days. Phoenix Children’s applies DataRobot AI Cloud for both clinical and operational applications. They built a comprehensive dataset based on 10 years of hospital data and used modeling to identify children who may be at-risk for malnutrition. With subsequent nutritionist evaluations of identified patients, they now uncover several patients every week. Phoenix Children’s also turned to DataRobot to predict no-shows for appointments, which traditionally happen about 10 to 20 percent of the time.
Operational Impact
  • Non-data scientists find viable models in minutes.
  • By predicting cases of possible malnutrition, they uncover 4-5 at-risk children each week.
  • They identify and proactively fill 9,000 appointments annually that might be missed otherwise.
  • Phoenix Children’s has additionally applied DataRobot to predicting emergency room visits, which can vary from three patients a day to 400. If they can predict volume, then they can adjust staffing accordingly.
Quantitative Benefit
  • Uncover 4-5 at-risk children for malnutrition each week.
  • Identify and proactively fill 9,000 appointments annually that might be missed otherwise.
  • Predict emergency room visits, enabling better staffing adjustments.

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