×

Automated mapping of service codes in healthcare systems

  • US 10,403,391 B2
  • Filed: 09/26/2013
  • Issued: 09/03/2019
  • Est. Priority Date: 09/28/2012
  • Status: Active Grant
First Claim
Patent Images

1. A method for automatic mapping of semantics in healthcare, the method comprising:

  • accessing first transaction data of a first healthcare entity in a first database, the first transaction data having a first set of values for a plurality of fields corresponding to a first semantic system;

    calculating, by a processor, a first distribution of the first set of values in the first transaction data, wherein the first distribution corresponds to the first semantic system;

    accessing second transaction data of a second healthcare entity in a second database, the second transaction data having a second set of values for a plurality of fields corresponding to a second semantic system that is different than the first semantic system;

    calculating, by the processor, a second distribution of the second set of values in the second transaction data, wherein the second distribution corresponds to the second semantic system;

    comparing, by the processor, the statistical similarity of the first distribution corresponding to the first semantic system and the second distribution corresponding to the second semantic system that is different than the first semantic system with machine learning, wherein comparing includes;

    determining a probability that a first field in the plurality of fields corresponding to the first semantic system is a particular field type based on a number of distinct values for the first field,determining a probability that a second field in the plurality of fields corresponding to the second semantic system is the particular field type based on a number of distinct values for the second field, andwhen it is determined that the number of distinct values of the first field of the first semantic system and the number of distinct values of the second field of the second semantic system are not within a predetermined threshold of one another, determining the first field and the second field are not the same particular field type;

    automatically outputting, from the machine learning, a map relating syntax of the first transaction data of the first semantic system to syntax of the second transaction data of the second semantic system, the map being a function of the comparing the statistical similarity of the first distribution corresponding to the first semantic system and the second distribution corresponding to the second semantic system;

    using the map for semantic interoperability between the first and second semantic systems, communicating information between the first and second healthcare entities; and

    updating the map each time new transaction data of the first healthcare entity is accessed, wherein updating the map includes;

    re-calculating the first distribution using the new transaction data; and

    comparing the statistical similarity of the first distribution, as updated, to the second distribution.

View all claims
  • 4 Assignments
Timeline View
Assignment View
    ×
    ×