Using internal and external data we observed what locations an individual will seek care in and commute over a period of time. Using demographic data coupled with location data we mapped an individuals location and commute pattern. Using machine learning and domain experts we were able to build a custom clustering algorithm that not only would give us specific locations with flexile radius per individuals but also was able to execute at scale with optimized computation resources while mentioning the performance high. 

As a result, Local Expert empowered every site of care recommendation to individuals to make sure the physical locations of recommendation are on the same route of care seekers commute pattern. 

This initiative resulted in increase level of behavior change, thus increase level of preventive actions. Local Expert not only helped to elevate the health level of the population but also generated millions of dollars in medical cost savings and lowering the populations risk.