Evidence-Based Medicine Supercharger

Abstract

Apparatuses, computer media, and methods for supporting health needs of a consumer by processing input data. An integrated health management platform supports the management of healthcare by obtaining multi-dimensional input data for a consumer, determining a health-trajectory predictor from the multi-dimensional input data, identifying a target of opportunity for the consumer in accordance with the health-trajectory predictor, and offering the target of opportunity for the consumer. An outcome study for a medical treatment from a medical publication is detected. The medical treatment is mapped to a diagnostic and procedural code and a database for health data is accessed using the diagnostic and procedural code. An outcome metric for the medical treatment with a consumer group is associated, and a utility function is generated from the plurality of outcome metrics, where the utility function gauges an efficacy of at least one intervention channel for a consumer.

1 . An apparatus for processing medical literature comprising:
 a text mining module detecting an outcome study for a medical treatment from a medical publication;   a rule induction module mapping the medical treatment to a diagnostic and procedural code;   a data analyzer configured to perform:
 (a) accessing a database for health data using the diagnostic and procedural code, the health data spanning previous treatment for a population of consumers; 
 (b) associating an outcome metric for the medical treatment with a consumer group; and 
 (c) repeating (a) and (b) to determine another outcome metric for another consumer group; and 
   a utility generator generating a utility function from the plurality of outcome metrics, the utility function gauging an efficacy of at least one intervention channel for a consumer.   
     
     
         2 . The apparatus of  claim 1 , the text mining module detecting another outcome study for another medical treatment. 
     
     
         3 . The apparatus of  claim 1 , the data analyzer determining the consumer group by clustering a subset of the population from at least one attribute of the population to form a cluster. 
     
     
         4 . The apparatus of  claim 3 , the utility generator determining the utility function that relates a utility score for a selected intervention channel as applied to the cluster. 
     
     
         5 . The apparatus of  claim 4 , the utility generator determining another utility score for another intervention channel as applied to another cluster. 
     
     
         6 . The apparatus of  claim 1 , further comprising:
 a confirmation interface presenting an abstract of the medical publication to a user and receiving, from the user, a notification that includes a confirmation of the abstract.   
     
     
         7 . The apparatus of  claim 6 , the confirmation interface editing the abstract that is presented to the user. 
     
     
         8 . The apparatus of  claim 3 , the data analyzer comparing a cluster dispersion measure of the cluster to a overall dispersion measure of the population and accepting the cluster from a ratio of the overall dispersion measure to the cluster dispersion measure. 
     
     
         9 . The apparatus of  claim 8 , the data analyzer comparing the cluster dispersion measure and overall dispersion measure for each outcome distribution. 
     
     
         10 . A method for processing medical literature comprising:
 (a) detecting an outcome study for a medical treatment from a medical publication;   (b) mapping the medical treatment to a diagnostic and procedural code;   (c) accessing a database for health data using the diagnostic and procedural code, the health data spanning previous treatment for a population of consumers;   (d) associating an outcome metric for the medical treatment with a consumer group; and   (e) repeating (c) and (d) to determine another outcome metric for another consumer group; and   (f) generating a utility function from the plurality of outcome metrics, the utility function gauging an efficacy of at least one intervention channel for a consumer.   
     
     
         11 . The method of  claim 10 , further comprising:
 (g) detecting another outcome study for another medical treatment.   
     
     
         12 . The method of  claim 10 , further comprising:
 (g) determining the consumer group by clustering a subset of the population from at least one attribute of the population to form a cluster.   
     
     
         13 . The method of  claim 12 , further comprising:
 (h) determining the utility function that relates a utility score for a selected intervention channel as applied to the cluster.   
     
     
         14 . The method of  claim 13 , further comprising:
 (i) determining another utility score for another intervention channel as applied to another cluster.   
     
     
         15 . The method of  claim 10 , further comprising:
 (g) presenting an abstract of the medical publication to a user receiving, from the user, a notification that includes a confirmation of the abstract.   
     
     
         16 . The method of  claim 15 , further comprising:
 (h) editing the abstract that is presented to the user.   
     
     
         17 . The method of  claim 12 , further comprising:
 (h) comparing a cluster dispersion measure of the cluster to a overall dispersion measure of the population; and   (i) accepting the cluster from a ratio of the overall dispersion measure to the cluster dispersion measure.   
     
     
         18 . The method of  claim 17 , further comprising:
 (j) comparing the cluster dispersion measure and overall dispersion measure for each outcome distribution.   
     
     
         19 . A computer-readable medium having computer-executable instructions to perform:
 (a) detecting an outcome study for a medical treatment from a medical publication;   (b) mapping the medical treatment to a diagnostic and procedural code;   (c) accessing a database for health data using the diagnostic and procedural code, the health data spanning previous treatment for a population of consumers;   (d) associating an outcome metric for the medical treatment with a consumer group; and   (e) repeating (c) and (d) to determine another outcome metric for another consumer group; and   (f) generating a utility function from the plurality of outcome metrics, the utility function gauging an efficacy of at least one intervention channel for a consumer.   
     
     
         20 . The computer-readable medium of  claim 19 , further configured to perform:
 (g) determining the consumer group by clustering a subset of the population from at least one attribute of the population to form a cluster.   
     
     
         21 . The computer-readable medium of  claim 20 , further configured to perform:
 (h) determining the utility function that relates a utility score for a selected intervention channel as applied to the cluster.   
     
     
         22 . The computer-readable medium of  claim 20 , further configured to perform:
 (h) comparing a cluster dispersion measure of the cluster to a overall dispersion measure of the population; and   (i) accepting the cluster from a ratio of the overall dispersion measure to the cluster dispersion measure.