Natural language processing of electronic records

Abstract

Electronic records are accessed from computer storage for a given subject, wherein the electronic records include natural language notes about the subject. Tokens are identified in the natural language notes. For each token, a corresponding intensity score is generated representing an intensity of match between the token and a particular dimension, wherein the intensity scores are each values on a first scale, wherein each dimension is one of a plurality of dimensions of a category out of a plurality of categories; generating rescaled-intensity scores from the intensity scores by rescaling the intensity scores from the first scale to a second scale different from the first scale. For each dimension of each category, a dimension-score is compiled based on the intensity scores; and categorizing the subject into at least one category based on the dimension scores. The subject is categorized into at least one category based on the dimension scores.

What is claimed is: 
     
         1 . A method comprising:
 accessing, from computer storage, clinical records for a patient prepared by a clinician treating the patient, the clinical records comprising natural language clinical-notes about the subject;   accessing, from computer storage, journals records prepared from journaling by the patient, the journal records comprising natural language entries;   combining the clinical records with the journal records to produce a plurality of clinical-journal tokens from at least one of the clinical records and the journal records, each of the clinical-journal tokens having an associated time based on the at least one of the clinical records and the journal records; and   creating a categorizing time-series for the subject based on the clinical journal tokens, the categorizing time-series showing intensity of a clinically-diagnostic category for the subject over a time period in which the clinical records were prepared and the journal records were prepared.   
     
     
         2 . The method of  claim 1 , wherein the clinical records are electronic medical records (EMRs) stored in a patient-management system that manages EMRs for many patients and wherein the journal records are stored in an electronic journal for a single one of the many patients. 
     
     
         3 . (canceled) 
     
     
         4 . (canceled) 
     
     
         5 . (canceled) 
     
     
         6 . (canceled) 
     
     
         7 . (canceled) 
     
     
         8 . The method of  claim 1 , wherein the clinical-journal tokens comprise words, strings, and portions of words. 
     
     
         9 . (canceled) 
     
     
         10 . (canceled) 
     
     
         11 . The method of  claim 1 , wherein:
 the clinical records and the journal records include timestamps;   identifying, for each clinical-journal token, a timestamp from the clinical records or the journal records; and   the method further comprises associating the associated time for each clinical-journal token based on one of the timestamps.   
     
     
         12 . A system comprising:
 one or more computers and one or more storage devices on which are stored instructions that are operable, when executed by the one or more computers, to cause the one or more computers to perform operations comprising:
 accessing, from computer storage, clinical records for a patient prepared by a clinician treating the patient, the clinical records comprising natural language clinical-notes about the subject; 
 accessing, from computer storage, journals records prepared from journaling by the patient, the journal records comprising natural language entries; 
 combining the clinical records with the journal records to produce a plurality of clinical-journal tokens from at least one of the clinical records and the journal records, each of the clinical journal tokens having an associated time based on the at least one of the clinical records and the journal records; and 
 creating a categorizing time-series for the subject based on the clinical journal tokens, the categorizing time-series showing intensity of a clinically-diagnostic category for the subject over a time period in which the clinical records were prepared and the journal records were prepared. 
   
     
     
         13 . The system of  claim 12 , wherein the clinical records are electronic medical records (EMRs) stored in a patient-management system that manages EMRs for many patients and wherein the journal records are stored in an electronic journal for a single one of the many patients. 
     
     
         14 . (canceled) 
     
     
         15 . (canceled) 
     
     
         16 . (canceled) 
     
     
         17 . (canceled) 
     
     
         18 . (canceled) 
     
     
         19 . (canceled) 
     
     
         20 . One or more non-transitory computer-readable storage media encoded with instructions that, when executed by one or more computers, cause the one or more computers to perform operations comprising:
 accessing, from computer storage, clinical records for a patient prepared by a clinician treating the patient, the clinical records comprising natural language clinical-notes about the subject;   accessing, from computer storage, journals records prepared from journaling by the patient, the journal records comprising natural language entries;   combining the clinical records with the journal records to produce a plurality of clinical-journal tokens from at least one of the clinical records and the journal records, each of the clinical journal tokens having an associated time based on the at least one of the clinical records and the journal records; and   creating a categorizing time-series for the subject based on the clinical journal tokens, the categorizing time-series showing intensity of a clinically-diagnostic category for the subject over a time period in which the clinical records were prepared and the journal records were prepared.   
     
     
         21 . The method of  claim 1 , wherein combining the clinical records with the journal records to produce a plurality of clinical journal tokens comprises:
 generating, for each clinical-journal token, a plurality of intensity scores, each intensity score being a numeric-value on a single scale such that none of the intensity values are greater than a maximum for the single scale and such that none of the intensity values are less a minimum for the single scale; and   translating the intensity scores to translated-scores in category-specific scales, at least some of the category-specific scales having a maximum for the category-specific scale different than the maximum for the single scale.   
     
     
         22 . The method of  claim 1 , wherein generating a time-series icon by:
 for at least a part of the time period, generating an element with a geometric parameter reflective of the intensity of the clinically-diagnostic category, such that changes in the intensity correspond to changes in the geometric parameter; and   causing the element to be rendered in a graphical user interface (GUI) as a time-series icon to show to a user the changes in the intensity by way of the geometric parameter.   
     
     
         23 . The method of  claim 22 , wherein the element is a line chart and wherein the geometric parameter is a y-value in the line chart reflective of the intensity of the clinically-diagnosed category. 
     
     
         24 . The method of  claim 22 , wherein causing the element to be rendered comprises serving to a client device a webpage with instructions to instruct the client device to render the element in a web browser. 
     
     
         25 . The system of  claim 12 , wherein the clinical journal tokens comprise words, strings, and portions of words. 
     
     
         26 . The system of  claim 12 , wherein:
 the clinical records and the journal records include timestamps;   identifying, for each clinical-journal token, a timestamp from the clinical records or the journal records; and   the operations further comprises associating the associated time for each clinical journal token based on one of the timestamps.   
     
     
         27 . The system of  claim 12 , wherein combining the clinical records with the journal records to produce a plurality of clinical journal tokens comprises:
 generating, for each clinical-journal token, a plurality of intensity scores, each intensity score being a numeric-value on a single scale such that none of the intensity values are greater than a maximum for the single scale and such that none of the intensity values are less a minimum for the single scale; and   translating the intensity scores to translated-scores in category-specific scales, at least some of the category-specific scales having a maximum for the category-specific scale different than the maximum for the single scale.   
     
     
         28 . The system of  claim 12 , wherein generating a time-series icon by:
 for at least a part of the time period, generating an element with a geometric parameter reflective of the intensity of the clinically-diagnostic category, such that changes in the intensity correspond to changes in the geometric parameter; and   causing the element to be rendered in a graphical user interface (GUI) as a time-series icon to show to a user the changes in the intensity by way of the geometric parameter.   
     
     
         29 . The system of  claim 28 , wherein the element is a line chart and wherein the geometric parameter is a y-value in the line chart reflective of the intensity of the clinically-diagnosed category. 
     
     
         30 . The system of  claim 28 , wherein causing the element to be rendered comprises serving to a client device a webpage with instructions to instruct the client device to render the element in a web browser. 
     
     
         31 . The media of  claim 20 , wherein the clinical records are electronic medical records (EMRs) stored in a patient-management system that manages EMRs for many patients and wherein the journal records are stored in an electronic journal for a single one of the many patients. 
     
     
         32 . The media of  claim 20 , wherein the clinical journal tokens comprise words, strings, and portions of words. 
     
     
         33 . The media of  claim 20 , wherein:
 the clinical records and the journal records include timestamps;   identifying, for each clinical-journal token, a timestamp from the clinical records or the journal records; and   the operations further comprises associating the associated time for each clinical journal token based on one of the timestamps.   
     
     
         34 . The media of  claim 20 , wherein combining the clinical records with the journal records to produce a plurality of clinical journal tokens comprises:
 generating, for each clinical-journal token, a plurality of intensity scores, each intensity score being a numeric-value on a single scale such that none of the intensity values are greater than a maximum for the single scale and such that none of the intensity values are less a minimum for the single scale; and   translating the intensity scores to translated-scores in category-specific scales, at least some of the category-specific scales having a maximum for the category-specific scale different than the maximum for the single scale.   
     
     
         35 . The media of  claim 20 , wherein generating a time-series icon by:
 for at least a part of the time period, generating an element with a geometric parameter reflective of the intensity of the clinically-diagnostic category, such that changes in the intensity correspond to changes in the geometric parameter; and   causing the element to be rendered in a graphical user interface (GUI) as a time-series icon to show to a user the changes in the intensity by way of the geometric parameter.   
     
     
         36 . The media of  claim 35 , wherein the element is a line chart and wherein the geometric parameter is a y-value in the line chart reflective of the intensity of the clinically-diagnosed category. 
     
     
         37 . The media of  claim 35 , wherein causing the element to be rendered comprises serving to a client device a webpage with instructions to instruct the client device to render the element in a web browser. 
     
     
         38 . The method of  claim 1 , wherein at least one of accessing the clinical records and accessing the journal records comprises performing optical character recognition (OCR) on one or more scanned documents. 
     
     
         39 . The method of  claim 1 , wherein combining the clinical records with the journal records comprises weighing the clinical records and journal records by their type. 
     
     
         40 . The system of  claim 12 , wherein at least one of accessing the clinical records and accessing the journal records comprises performing optical character recognition (OCR) on one or more scanned documents. 
     
     
         41 . The system of  claim 12 , wherein combining the clinical records with the journal records comprises weighing the clinical records and journal records by their type. 
     
     
         42 . The media of  claim 20 , wherein combining the clinical records with the journal records comprises weighing the clinical records and journal records by their type 
     
     
         43 . The media of  claim 20 , wherein at least one of accessing the clinical records and accessing the journal records comprises performing optical character recognition (OCR) on one or more scanned documents.