Amino Corporation

Shashank Shekhar

A system trains a predictive model based on training data including records of non-public healthcare insurance claims and public healthcare fee schedule data. The system determines a multiplier for each of multiple healthcare facilities based on the predictive model. The system then receives, from a consumer device, a query for a particular cost estimate of a healthcare service provided by the multiple healthcare facilities. The query includes constraints for a preferred geographic region or a preferred insurer. The system predicts a first cost estimate for the healthcare service at a first healthcare facility based on a first multiplier and a second cost estimate for the healthcare service at a second healthcare facility based on second multiplier. The system then causes the consumer device to display query results including indications of the first and second cost estimates.

Machine learning models in location based episode prediction

The disclosed embodiments include a method performed by server computer(s). The method includes obtaining private healthcare insurance claims data and public healthcare procedure code data from one or more data source(s), generating a model based the training data, and determining a multiplier for each of the many facilities based on the model. The model provides predictive results for variability between healthcare facilities thereby enabling consumer research in light of considerations in facility variability. The multiplier is indicative of a value used to scale the public healthcare procedure code data for a facility such that a healthcare service associated with the facility can be estimated based on the multiplier.

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San Francisco, CA, United States of America

Shashank Shekhar