Unified data interface and system

Abstract

Various systems and methods are provided that aggregate, analyze, and display health data for users. The system aggregates data stored in various databases. For example, the system retrieves data from these databases, maps the data to a set of common terms based on an ontology, and displays such information to an entity accessing the system. Rather than converting the data stored in the databases into a standardized format, the system includes a set of ontologies that provide a correlation between a first set of fields and a second set of fields. The system determines a correlation between a first field in the first set of fields and a second field in the second set of fields using the ontology, stores data retrieved from the database in a second database in association with the second field, and displays the data associated with the first field under the second field.

What is claimed is: 
     
         1 . A computing system comprising:
 one or more computer processors;   a database that organizes data in a plurality of first columns;   a computer readable storage medium storing program instructions configured for execution by the one or more computer processor in order to cause the computing system to:
 for a second database,
 access a dataset stored in the second database, wherein the accessed dataset comprises data for a plurality of users organized in a plurality of second columns; 
 determine a mapping between a name of a second column in the plurality of second columns and a name of a first column in the plurality of first columns; and 
 cause display of an unmodified version of the data in the accessed dataset corresponding to the name of the second column in a user interface under the name of the first column; 
 
 receive a request to access the computing system; 
 determine an identity of a user associated with the request to access the computing system; 
 retrieve, from the first database, user health data that is associated with the determined user; 
 retrieve, from a third database, health claims data associated with the determined user; 
 categorize the determined user into a first group based on the health claims data; 
 train one or more models using the health claims data and health claims data associated with one or more other users to produce a set of feature weights associated with the determined user, wherein each of the one or more models corresponds to a state transition from the first group to another group in one or more groups; 
 determine a likelihood that the determined user will transition from the first group into one of the one or more other groups within a threshold time period using the set of feature weights; 
 translate the likelihood into a risk score; and 
 generate user interface data for rendering the user interface on a computing device, wherein the user interface comprises an indication of the risk score. 
   
     
     
         2 . The computing system of  claim 1 , wherein the user interface includes a first container that comprises an identification of at least one third column in the plurality of first columns, wherein the first container further comprises the retrieved user health data that corresponds with the at least one third column. 
     
     
         3 . The computing system of  claim 1 , wherein the retrieved health claims data comprises medical claims submitted on behalf of the determined user, and wherein the computer readable storage medium further stores program instructions that cause the computing system to generate a summary of a health history of the determined user based on the medical claims. 
     
     
         4 . The computing system of  claim 1 , wherein the retrieved user health data comprises prescription data. 
     
     
         5 . The computing system of  claim 1 , wherein the risk score is based on at least one of a number of missing services associated with the user, a priority of each missing service associated with the user, a likelihood that the user seeks medical services without intervention, or a number of times the user does not comply with a recommended care plan. 
     
     
         6 . The computing system of  claim 1 , wherein the mapping between the name of the second column and the name of the first column is determined based on an ontology. 
     
     
         7 . The computing system of  claim 1 , wherein the user interface further includes a first container that comprises a first alert associated with a team member and a second alert associated with the team member, wherein the first alert corresponds with the user, and wherein the second alert corresponds with a second user. 
     
     
         8 . The computing system of  claim 1 , wherein the computer readable storage medium further stores program instructions that cause the computing system to:
 receive text and a selection of a second team member from a first team member; and   transmit a message to an account associated with the second team member, wherein the message comprises the text, and wherein the second team member can view the message when accessing the computing system.   
     
     
         9 . The computing system of  claim 8 , wherein the first team member is one of a primary care physician, a pharmacist, a government agency employee, a guardian, or the user. 
     
     
         10 . A computer-implemented method comprising:
 as implemented by one or more computer systems comprising computer hardware and memory, the one or more computer systems configured with specific executable instructions,   retrieving a dataset stored in a first database, wherein the retrieved dataset comprises data for a plurality of users organized in a plurality of second columns;   determining a mapping between a name of a second column in the plurality of second columns and a name of a first column in a plurality of first columns;   causing display of an unmodified version of the data in the retrieved dataset corresponding to the name of the second column in a user interface under the name of the first column;   receiving a request to access the one or more computer systems;   determining an identity of a user associated with the request to access the one or more computer systems;   retrieving, from the first database, user health data that is associated with the determined user;   retrieving, from a second database, health claims data associated with the determined user;   categorizing the determined user into a first group based on the health claims data;   training one or more models using the health claims data and health claims data associated with one or more other users to produce a set of feature weights associated with the determined user, wherein each of the one or more models corresponds to a state transition from the first group to another group in one or more groups;   determining a likelihood that the determined user will transition from the first group into one of the one or more other groups within a threshold time period using the set of feature weights;   translating the likelihood into a risk score; and   generating user interface data for rendering the user interface on a computing device, wherein the user interface comprises an indication of the risk score.   
     
     
         11 . The computer-implemented method of  claim 10 , wherein the user interface includes a first container that comprises an identification of at least one third column in the plurality of first columns, wherein the first container further comprises the retrieved user health data that corresponds with the at least one third column. 
     
     
         12 . The computer-implemented method of  claim 11 , further comprising generating a summary of a health history of the determined user based on the retrieved user health data, wherein the first container further comprises the generated summary of the health history of the determined user. 
     
     
         13 . The computer-implemented method of  claim 12 , wherein the retrieved health claims data comprises medical claims submitted on behalf of the determined user, and wherein the computer-implemented method further comprises generating the summary of the health history of the determined user based on the medical claims. 
     
     
         14 . The computer-implemented method of  claim 10 , wherein the retrieved health claims data comprises prescription data. 
     
     
         15 . The computer-implemented method of  claim 10 , further comprising:
 receiving text and a selection of a second team member from a first team member; and   transmitting a message to an account associated with the second team member, wherein the message comprises the text, and wherein the second team member can view the message when accessing the computing system.   
     
     
         16 . The computer-implemented method of  claim 15 , wherein the first team member is one of a primary care physician, a pharmacist, a government agency employee, a guardian, or the user. 
     
     
         17 . A non-transitory computer-readable storage medium including computer-executable instructions that, when executed by a processor, configure the processor to:
 retrieve a dataset stored in a first database, wherein the retrieved dataset comprises data for a plurality of users organized in a plurality of second columns;   determine a mapping between a name of a second column in the plurality of second columns and a name of a first column in a plurality of first columns;   cause display of an unmodified version of the data in the retrieved dataset corresponding to the name of the second column in a user interface under the name of the first column;   receive a request to access one or more computer systems;   determine an identity of a user associated with the request to access the one or more computer systems;   retrieve, from the first database, user health data that is associated with the determined user;   retrieve, from a second database, health claims data associated with the determined user;   categorize the determined user into a first group based on the health claims data;   train one or more models using the health claims data and health claims data associated with one or more other users to produce a set of feature weights associated with the determined user, wherein each of the one or more models corresponds to a state transition from the first group to another group in one or more groups;   determine a likelihood that the determined user will transition from the first group into one of the one or more other groups within a threshold time period using the set of feature weights;   translate the likelihood into a risk score; and   generate user interface data for rendering the user interface on a computing device, wherein the user interface comprises an indication of the risk score.