Network based intervention

Abstract

Methods and systems for network-based intervention are disclosed. The methods can include receiving a user response and analyzing the user response and other user data to determine a user typology. The user typology can be compared with risk data that indicates the user's risk of failing to achieve a target outcome based on the identified user typology. If the user's risk of failing to achieve the target outcome exceeds a desired level, a mitigation plan can be generated and provided to the user to thereby facilitate in the attainment of the target outcome.

What is claimed is: 
     
         1 . A system, comprising:
 a database coupled to a computer network and storing:
 a user data comprising at least one user attribute; 
 a plurality of question prompts; 
 a threshold; and 
 a plurality of intervention recommendations; 
   a server comprising a server computing device coupled to the computer network and including at least one processor executing instructions within memory which, when executed, cause the system to:
 receive, from a user interface on a user device, a target outcome; 
 select a question prompt, in the plurality of question prompts, associated in the database with the target outcome; 
 transmit the question prompt through the network to a user device; 
 receive, from the user device, a response to the question prompt; 
 analyze the response to identify at least one response attribute; 
 input the at least one response attribute and the at least one user attribute into a predictive model; 
 receive, as an output from the predictive model:
 an identified classification; and 
 a risk score comprising a likelihood of the target outcome being achieved; 
 
 responsive to the risk score being below the threshold, select, from the plurality of intervention recommendations, at least one intervention recommendation associated in the database with the identified classification; and 
 transmit a notification including the intervention recommendation through the computer network to the user device. 
   
     
     
         2 . The system of  claim 1 , further comprising a plurality of user devices, wherein the instructions further cause the server, prior to receiving the target outcome, to:
 transmit a previous question prompt, associated with the target outcome, through the network to the plurality of user devices;   receive, from the plurality of user devices, a plurality of responses; and   define a plurality of classifications, including the classification, according to the plurality of responses.   
     
     
         3 . The system of  claim 2 , wherein the predictive model is trained by:
 receiving the plurality of responses;   identifying, within each of the plurality of responses, at least one response attribute;   determining a resulting outcome associated with each of the plurality of responses, the resulting outcome comprising a determination of whether at least one target outcome was achieved; and   associating a classification with the resulting outcome.   
     
     
         4 . The system of  claim 3 , further comprising a text mining software running on the server and configured to identify the at least one response attribute, comprising a common content, style, or tone of each of the plurality of responses, by identifying a commonality of terms within each of the plurality of responses. 
     
     
         5 . The system of  claim 3 , further comprising an outcome software engine running on the server and configured to:
 identify the resulting outcome associated with each of the plurality of responses;   store, in association in the database, the resulting outcome and the at least one response attribute for each of the plurality of responses.   
     
     
         6 . The system of  claim 5  further comprising a typology classification software engine running on the server and configured to:
 select a plurality of resulting outcomes and the at least one response characteristic associated with each of the plurality of resulting outcomes from the database; 
 determine a degree to which the plurality of resulting outcomes resulted in at least one target outcome being achieved; 
 assign a typology categorization to a subset of the plurality of responses sharing a common degree of success for achieving the at least one target outcome. 
 
     
     
         7 . A method, comprising:
 receiving, from a user interface on a user device, by a server comprising a server computing device coupled to a computer network and including at least one processor executing instructions within memory, a target outcome;   selecting, by the server, from a plurality of question prompts stored in a database coupled to the computer network, a question prompt associated in the database with the target outcome;   transmitting, by the server, the question prompt through the computer network to a user device;   receiving, by the server from the user device, a response to the question prompt;   analyzing, by the server, the response to identify at least one response attribute;   inputting, by the server, the at least one response attribute and at least one user attribute stored in the database, into a predictive model;   receiving, by the server, as an output from the predictive model:
 an identified classification; and 
 a risk score comprising a likelihood of the target outcome being achieved; 
   responsive to the risk score being below a threshold stored in the database, selecting, by the server, from a plurality of intervention recommendations stored in the database, at least one intervention recommendation associated in the database with the identified classification; and   transmitting, by the server, a notification including the intervention recommendation through the computer network to the user device.   
     
     
         8 . The method of  claim 7 , further comprising the steps, prior to receiving the target outcome, of:
 transmitting, by the server, a previous question prompt, associated with the target outcome, through the network to a plurality of user devices;   receiving, by the server, from the plurality of user devices, a plurality of responses; and   defining, by the server, a plurality of classifications, including the identified classification, according to the plurality of responses.   
     
     
         9 . The method of  claim 8 , further comprising the step of training the predictive model by:
 receiving the plurality of responses;   identifying, within each of the plurality of responses, by a text mining software running on the server, at least one response attribute;   determining a resulting outcome associated with each of the plurality of responses, the resulting outcome comprising a determination of whether at least one target outcome was achieved; and   associating a classification with the resulting outcome.   
     
     
         10 . The method of  claim 9 , wherein the text mining software is configured to identify the at least one response attribute, comprising a common content, style, or tone of each of the plurality of responses, by identifying a commonality of terms within each of the plurality of responses. 
     
     
         11 . The method of  claim 9 , further comprising the steps of:
 selecting, by the server from the database:
 a plurality of resulting outcomes; and 
 the at least one response characteristic associated with each of the plurality of resulting outcomes; 
   determining, by the server, a degree to which the plurality of resulting outcomes resulted in at least one achieved target outcome; and   assigning, by the server, a typology categorization to each of a plurality of subsets of the plurality of responses sharing a common degree of success for achieving the at least one target outcome.   
     
     
         12 . The method of  claim 7  wherein the identified classification indicates:
 the characteristics of an exhibited typology associated with the response; or 
 a degree to which the response exhibits at least one response characteristic associated with the exhibited typology. 
 
     
     
         13 . The method of  claim 7 , wherein the risk score represents a likelihood that the target outcome will be achieved, or a risk of the target outcome not being achieved. 
     
     
         14 . The method of  claim 7 , wherein intervention recommendation comprises at least one action to be taken to mitigate the risk of a predicted adverse outcome or at least one action to be taken to increase the likelihood of a predicted positive outcome. 
     
     
         15 . A system, comprising:
 a server comprising a server computing device coupled to the computer network and including at least one processor executing instructions within memory which, when executed, cause the server to:
 receive, from a user interface on a user device, a target outcome; 
 select, from a plurality of question prompts stored in a database coupled to the computer network, a question prompt associated in the database with the target outcome; 
 transmit the question prompt through the computer network to a user device; 
 receive, from the user device, a response to the question prompt; 
 analyze the response to identify at least one response attribute; 
 input the at least one response attribute and at least one user attribute stored in the database, into a predictive model; 
 receive, as an output from the predictive model:
 an identified classification; and 
 a risk score comprising a likelihood of the target outcome being achieved; 
 
 responsive to the risk score being below a threshold stored in the database, select, from a plurality of intervention recommendations stored in the database, at least one intervention recommendation associated in the database with the identified classification; and 
 transmit a notification including the intervention recommendation through the computer network to the user device. 
   
     
     
         16 . The system of  claim 15 , wherein the server is further configured to, prior to receiving the target outcome:
 transmit a previous question prompt, associated with the target outcome, through the network to a plurality of user devices;   receive, from the plurality of user devices, a plurality of responses; and   define a plurality of classifications, including the identified classification, according to the plurality of responses.   
     
     
         17 . The system of  claim 16 , wherein the predictive model is trained by:
 receiving the plurality of responses;   identifying, within each of the plurality of responses, by a text mining software running on the server, at least one response attribute;   determining a resulting outcome associated with each of the plurality of responses, the resulting outcome comprising a determination of whether at least one target outcome was achieved; and   associating a classification with the resulting outcome.   
     
     
         18 . The system of  claim 17 , wherein the server is further configured to:
 select, from the database:
 a plurality of resulting outcomes; and 
 the at least one response characteristic associated with each of the plurality of resulting outcomes; 
   determine a degree to which the plurality of resulting outcomes resulted in at least one achieved target outcome; and   assign a typology categorization to each of a plurality of subsets of the plurality of responses sharing a common degree of success for achieving the at least one target outcome.