Helping a top 5 US payer provide analytical services to its internal and external customers
This leading U.S. healthcare payer wanted to build analytical models for machine learning and offer analytical services to both internal and external customers, including healthcare providers, developers and researchers.
A leading U.S. healthcare payer required the capability to provide analytical services to both internal and external customers.
Atos was engaged to perform the following objectives:
- Implement Analytics as-a-Service (AaaS) for diabetes treatment, Rx rejections and readmission risk
- Build a scalable, independent deployment service platform
- Expose the analytics API to internal teams as well as external stakeholders
- Enable fast time to market for this new service line
Atos worked with the health insurer to understand its business areas and the purpose of the machine learning models, in order to develop the architecture for development and deployment. Atos was involved with:
- Designing and implementing analytics services using a microservices architecture
- Building a platform to deploy and evaluate machine learning models with R and Python
- Exposing the endpoints to be used by microservices
- Managing APIs for consumption by external customers and user engagement via web and mobile devices
- Microservices testing and deployment on cloud
After just two months, Atos was able to get the health insurer’s machine learning API up and running.
- Algorithms and business rules produce patient predictions based on health records
- Easy plug-and-play analytics across the organization
- Improved business agility for accessing predictive models
- Increased revenue potential with a new analytics service line
- Automated model deployment and productivity improvements
- Robust platform to build, deploy and evaluate machine learning models
- Open source technology with no license cost
Healthcare is evolving along two dimensions. The first is a mega shift from in-hospital care to remote and at-home care, while the second is a change of focus from treatment to prevention to wellness.
The data-ization and connection of all things, alongside a massive rise in computing power is making AI a reality now; turning data into valuable insights and creating tremendous opportunities for business.
Rapid developments in high performance computing, edge technology and artificial intelligence are creating new opportunities to accelerate research and deliver innovative solutions into frontline healthcare.
Artificial Intelligence and Machine Learning:
Ruud van der Loo
VP Global Healthcare market