The Heritage Health Prize: Bringing Data Science to Preventative Medicine
Company Size
1,000+
Region
- America
Country
- United States
Product
- Heritage Health Prize
- Kaggle
Tech Stack
- Predictive Analytics
- Data Anonymization
Implementation Scale
- Enterprise-wide Deployment
Impact Metrics
- Cost Savings
- Innovation Output
- Productivity Improvements
Technology Category
- Analytics & Modeling - Predictive Analytics
- Application Infrastructure & Middleware - Data Exchange & Integration
Applicable Industries
- Healthcare & Hospitals
Applicable Functions
- Business Operation
Use Cases
- Remote Patient Monitoring
Services
- Data Science Services
- System Integration
About The Customer
The Heritage Provider Network (HPN) is a healthcare organization focused on improving patient outcomes and reducing healthcare costs. They are known for their innovative approaches to healthcare challenges and their commitment to leveraging data science for better patient care. HPN's initiative, the Heritage Health Prize, was a groundbreaking competition aimed at developing predictive models to prevent unnecessary hospitalizations. By partnering with Kaggle, a platform known for hosting data science competitions, HPN engaged a global community of data scientists, including Nobel Prize winners, physicians, scientists, and actuaries. This diverse group of participants brought a wealth of expertise to the challenge, contributing to the advancement of predictive analytics in healthcare.
The Challenge
The Heritage Provider Network (HPN) identified a significant challenge in the U.S. healthcare system: more than 71 million people are hospitalized annually, leading to at least $30 billion in avoidable costs. To address this, HPN launched the Heritage Health Prize, aiming to develop new algorithms that could predict and prevent unnecessary hospitalizations. The competition sought to revolutionize preventative medicine by enabling care providers to intervene before emergencies occur. Participants were given anonymized claims and provider data to predict hospitalizations for the next year. Despite the complexity of anonymizing sensitive patient data, which often results in a tradeoff between data anonymization and predictive accuracy, the competition aimed to push the boundaries of what is possible with existing healthcare data.
The Solution
HPN chose Kaggle to run the Heritage Health Prize, a competition that spanned from 2011 to 2013. Participants were provided with anonymized claims and provider data and tasked with predicting which days each patient would spend in the hospital within the next year. The competition offered substantial prizes, including $500,000 for the final winner and $230,000 in milestone prizes, with a $3MM Grand Prize contingent on achieving a very high threshold for accuracy. Despite the challenges posed by data anonymization, which often leads to a loss of information, the competition saw over 1600 data scientists submit more than 25,000 models. Although no team met the accuracy required for the Grand Prize, the competition fostered the development of new approaches and advanced the field of predictive analytics in healthcare.
Operational Impact
Quantitative Benefit
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