Correlating personal IDs to online digital IDs
A computer obtains records of multiple digital events from multiple vendors of digital event records, each digital event record having a digital ID of a user that initiated the respective digital event. A computer obtains at least one list of professional registry numbers of professionals in a profession. A computer classifies at least some portion of the digital event records and at least some internet web pages based on a standard taxonomical index. A computer identifies correlated identification data points among the digital event records and the professional registry records, and based on the taxonomic classification of pages and digital events, to infer a correlation between digital IDs from digital event records and actual physical identities of physical persons, and computing a parameter reflecting a degree of certainty of the inference.
1. A method, comprising the steps of:
at a computer, obtaining records of multiple digital events from multiple vendors of digital event records, each digital event record having a digital ID of a user that initiated the respective digital event;
at the computer, obtaining at least one list of professional registry numbers of professionals in a profession;
by the computer, classifying at least some portion of the digital event records and at least some internet web pages based on a standard taxonomical index;
by the computer, identifying correlated identification data points among the digital event records and the professional registry records, and based on the taxonomic classification of pages and digital events, to infer a correlation between digital IDs from digital event records and actual physical identities of physical persons, and computing a parameter reflecting a degree of certainty of the inference.
2. The method of claim 1 , wherein:
the correlating considers at least three of a cookie value from a user's browser, IP address, user ID assigned by an onboarder, mobile device ID, mobile phone number, and email address.
3. The method of claim 2 , wherein:
the correlating considers at least four of a cookie value from a user's browser, IP address, user ID assigned by an onboarder, mobile device ID, mobile phone number, and email address.
4. The method of claim 1 , wherein:
the identification of correlation includes identifying multiple digital IDs assigned by multiple sources that correspond, to high probability, to a single, identifiable individual.
5. The method of claim 1 ,
wherein the list of professional registry numbers includes the NPI (National Provider ID) assigned by CMS (the Center for Medicare & Medicaid Services).
6. The method of claim 1 ,
wherein the web pages and digital events are taxonomically classified under at least two of SNOMED CT, the Medical Subject Headings (MeSH), the Unified Medical Language System (UMLS), and International Classification of Diseases (ICD).
7. A method, comprising the steps of:
at a computer, obtaining records of multiple digital events from multiple vendors of digital event records, each digital event record having a digital ID of a user that initiated the respective digital event;
at the computer, obtaining at least one list of professional registry numbers of professionals in a profession;
by the computer, classifying at least some portion of the digital event records and at least some internet web pages based on a standard taxonomical index; and
by the computer, identifying correlated identification data points among the digital event records and the professional registry records, and based on the taxonomic classification of pages and digital events, to infer a correlation between digital IDs from digital event records and actual physical identities of physical persons, and computing a parameter reflecting a degree of certainty of the inference.
8. The method of claim 7 , wherein:
the identifying and inferring of correlation consider at least three of a cookie value from a user's browser that initiated a one of the digital event records, IP address of a visitor for a one of the digital event records, user ID assigned by an onboarder, mobile device ID of a visitor for a one of the digital event records, mobile phone number of a visitor for a one of the digital event records, and email address of a visitor for a one of the digital event records.
9. The method of claim 8 , wherein:
the identifying and inferring of correlation consider at least four of a cookie value from a user's browser that initiated a one of the digital event records, IP address of a visitor for a one of the digital event records, user ID assigned by an onboarder, mobile device ID of a visitor for a one of the digital event records, mobile phone number of a visitor for a one of the digital event records, and email address of a visitor for a one of the digital event records.
10. The method of claim 7 , wherein:
the identifying and inferring of correlation include identifying multiple digital IDs assigned by multiple sources that correspond, to high probability, to a single, identifiable individual.
11. The method of claim 7 ,
wherein the list of professional registry numbers includes the NPI (National Provider ID) assigned by CMS (the Center for Medicare & Medicaid Services).
12. The method of claim 7 ,
wherein the web pages and digital events are taxonomically classified under at least two of SNOMED CT, the Medical Subject Headings (MeSH), the Unified Medical Language System (UMLS), and International Classification of Diseases (ICD).
13. A apparatus, comprising:
one or more processors;
a machine readable, nontransitory memory, having stored therein instructions programmed to cause the one or more processors to:
obtain records of multiple digital events from multiple vendors of digital event records, each digital event record having a digital ID of a user that initiated the respective digital event;
obtain at least one list of professional registry numbers of professionals in a profession;
classify at least some portion of the digital event records and at least some internet web pages based on a standard taxonomical index; and
identify correlated identification data points among the digital event records and the professional registry records, and based on the taxonomic classification of pages and digital events, to infer a correlation between digital IDs from digital event records and actual physical identities of physical persons, and computing a parameter reflecting a degree of certainty of the inference.
14. The apparatus of claim 13 , wherein:
the identifying and inferring of correlation consider considers at least three of a cookie value from a user's browser that initiated a one of the digital event records, IP address of a visitor for a one of the digital event records, user ID assigned by an onboarder, mobile device ID of a visitor for a one of the digital event records, mobile phone number of a visitor for a one of the digital event records, and email address of a visitor for a one of the digital event records.
15. The apparatus of claim 14 , wherein:
the identifying and inferring of correlation consider at least four of a cookie value from a user's browser that initiated a one of the digital event records, IP address of a visitor for a one of the digital event records, user ID assigned by an onboarder, mobile device ID of a visitor for a one of the digital event records, mobile phone number of a visitor for a one of the digital event records, and email address of a visitor for a one of the digital event records.
16. The apparatus of claim 13 , wherein:
the identifying and inferring of correlation consider includes identifying multiple digital IDs assigned by multiple sources that correspond, to high probability, to a single, identifiable individual.
17. The apparatus of claim 13 ,
wherein the list of professional registry numbers includes the NPI (National Provider ID) assigned by CMS (the Center for Medicare & Medicaid Services).
18. The apparatus of claim 13 ,
wherein the web pages and digital events are taxonomically classified under at least two of SNOMED CT, the Medical Subject Headings (MeSH), the Unified Medical Language System (UMLS), and International Classification of Diseases (ICD).