PREDICTIVE MODELING
First Claim
Patent Images
1. A computer implemented method, comprising:
- extracting patient data from a database, the patient data comprising final coded data for each of a plurality of patients and encounter patient data for at least a subset of the plurality of patients;
assigning a value to each code in a set of possible codes for each respective patient based on comparing data for each patient in the final coded data relative to the set of possible codes to provide model data;
storing the model data in memory;
assigning a value to each code of the set of possible codes for each respective patient in the subset of patients based on comparing data for each patient in the encounter patient data relative to the set of possible codes to provide testing data;
storing the testing data in the memory;
generating a model for predicting a selected patient event or outcome, the model having a plurality of predictor variables, corresponding to a selected set of the possible codes, derived from the model data, each of the predictor variables having coefficients calculated from the testing data based on a concordance index of the respective predictor variable to the patient event or outcome; and
storing the model in the memory.
1 Assignment
0 Petitions
Accused Products
Abstract
This disclosure relates to predictive modeling. Systems and methods can be utilized extract data from a plurality of data sources to provide a set of predictor variables. The predictor variables can be analyzed to generate a model having a portion of the predictor variables with weighted coefficients according to an event or outcome for which the model is generated. A prediction tool can employ the model to predict the even or outcome for one or more patients.
-
Citations
25 Claims
-
1. A computer implemented method, comprising:
-
extracting patient data from a database, the patient data comprising final coded data for each of a plurality of patients and encounter patient data for at least a subset of the plurality of patients; assigning a value to each code in a set of possible codes for each respective patient based on comparing data for each patient in the final coded data relative to the set of possible codes to provide model data; storing the model data in memory; assigning a value to each code of the set of possible codes for each respective patient in the subset of patients based on comparing data for each patient in the encounter patient data relative to the set of possible codes to provide testing data; storing the testing data in the memory; generating a model for predicting a selected patient event or outcome, the model having a plurality of predictor variables, corresponding to a selected set of the possible codes, derived from the model data, each of the predictor variables having coefficients calculated from the testing data based on a concordance index of the respective predictor variable to the patient event or outcome; and storing the model in the memory. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18)
-
-
19. A system comprising:
-
memory to store computer readable instructions and data; a processing unit to access the memory and execute the computer readable instructions, the computer readable instructions comprising; an extractor programmed to extract patient data from at least one data source, the patient data comprising a final coded data set for each of a plurality of patients and a patient encounter data set for at least a subset of the plurality of patients; data inspection logic programmed to assign a value to each code of a set of possible codes for each patient based on comparing data for each respective patient in the final coded data set relative to the set of possible codes to provide a modeling data set, the data inspection logic also being programmed to assign a value to each code of the set of possible codes based on comparing data for each patient in the patient encounter data set relative to the set of possible codes to provide a testing data set; and a model generator programmed to generate a model having a plurality of predictor variables, corresponding to a selected set of the possible codes, each of the predictor variables having coefficients calculated based on a concordance index of each respective variable to a selected patient event or outcome for which the model is generated. - View Dependent Claims (20, 21, 22, 23, 24, 25)
-
Specification