Using user-attribute ontologies to calculate user-anonymity degrees
First Claim
1. One or more computer hardware storage media having computer-executable instructions embodied thereon for performing a method in a clinical computing environment for using user-attribute ontologies to calculate user-anonymity degrees, the method comprising:
- receiving an indication that a user desires to join a medical social network group having a plurality of members;
receiving a plurality of attribute values, each attribute value being associated with a user-attribute, wherein the plurality of attribute values comprises attribute values associated with user submitted data and attribute values extracted from the user'"'"'s electronic health records, wherein a first user-attribute value of the plurality of attribute values is a medical condition, wherein the first user-attribute value includes a multi-level user-attribute ontology related thereto;
receiving group-member attribute values for the plurality of members of the medical social network group;
calculating a degree of user-anonymity for the user conditioned on exposure of at least one subset of the plurality of attribute values to the medical social network group, wherein the calculated degree of user-anonymity is based at least in part on the group-member attribute values; and
presenting an indication of the calculated degree of user-anonymity and an identity of each of the plurality of attribute values included in the at least one subset.
1 Assignment
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Accused Products
Abstract
Computerized methods and systems for using user-attribute ontologies to calculate anonymity levels are provided. A semi-automated mechanism permits selective and optionally progressive exposure of demographic and clinical information to other members of a medical social network group that a member has joined. When a user decides to join a medical social network group (which may be based upon system suggestion or initiated of the user'"'"'s own accord), he or she selects or creates a profile that has a statistically validated degree of anonymity, ranging from fully anonymous to fully transparent. Based upon a user'"'"'s elected level of exposure, only certain data is exposed to the rest of the group'"'"'s membership. Thus, the user is permitted to personally balance the tension between exposing a level of information that may render him or her personally identifiable and exposing enough information to obtain meaningful advice and/or camaraderie.
4 Citations
18 Claims
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1. One or more computer hardware storage media having computer-executable instructions embodied thereon for performing a method in a clinical computing environment for using user-attribute ontologies to calculate user-anonymity degrees, the method comprising:
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receiving an indication that a user desires to join a medical social network group having a plurality of members; receiving a plurality of attribute values, each attribute value being associated with a user-attribute, wherein the plurality of attribute values comprises attribute values associated with user submitted data and attribute values extracted from the user'"'"'s electronic health records, wherein a first user-attribute value of the plurality of attribute values is a medical condition, wherein the first user-attribute value includes a multi-level user-attribute ontology related thereto; receiving group-member attribute values for the plurality of members of the medical social network group; calculating a degree of user-anonymity for the user conditioned on exposure of at least one subset of the plurality of attribute values to the medical social network group, wherein the calculated degree of user-anonymity is based at least in part on the group-member attribute values; and presenting an indication of the calculated degree of user-anonymity and an identity of each of the plurality of attribute values included in the at least one subset. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8)
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9. A method in a clinical computing environment for providing medical social network group suggestions having anonymity degrees calculated, at least in part, using user-attribute ontologies, the method comprising the following computer-implemented steps:
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extracting a plurality of attribute values from a health record of a user, each attribute value being associated with a user-attribute, wherein a first user-attribute value of the plurality of attribute values is a medical condition, wherein the first user-attribute value includes a multi-level user-attribute ontology related thereto; receiving attribute values associated with user submitted data; receiving group-member attribute values for a plurality of members of a medical social network group, the group-member attribute values being associated with a common user-attribute associated with the plurality of attribute values; calculating a degree of user-anonymity for the user as it relates to the received group-member attribute values, the degree of user-anonymity being conditioned on exposure of at least one subset of the plurality of attribute values and at least a portion of the attribute values associated with user submitted data; and presenting a suggestion that the user join the medical social network group and the calculated degree of user-anonymity upon determining that the calculated degree of user-anonymity meets or exceeds a threshold degree of user-anonymity, wherein the threshold degree of user-anonymity is based on the group-member attribute values of the plurality of members in the medical social network group. - View Dependent Claims (10, 11, 12, 13, 14, 15)
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16. One or more computer hardware storage media having computer-executable instructions embodied thereon for performing a method in a clinical computing environment for using user-attribute ontologies to calculate user-anonymity degrees, the method comprising:
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receiving an indication that a user desires to join a medical social network group having a plurality of members; receiving a plurality of attribute values, each attribute value being associated with a user-attribute, wherein a first and a second of the plurality of attribute values are associated with a first common user-attribute, wherein the first common user-attribute is a medical condition, wherein the first common user-attribute includes a first multi-level user-attribute ontology related thereto, and wherein each of the first and second of the plurality of attribute values is associated with a different level of the first multi-level user-attribute ontology, wherein a third and a fourth of the plurality of attribute values are associated with a second common user-attribute, wherein the second common user-attribute includes a second multi-level user-attribute ontology related thereto, and wherein each of the third and fourth of the plurality of attribute values is associated with a different level of the second multi-level user-attribute ontology, calculating a plurality of degrees of user-anonymity conditioned on exposure of different subsets of the plurality of attribute values, a first subset containing at least one of the first and second of the plurality of attribute values and one of the third and fourth of the plurality of attribute values; and presenting an indication of the calculated degrees of user-anonymity and an identity of each of the plurality of attribute values included in the associated subset. - View Dependent Claims (17, 18)
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Specification