Method for generating healthcare-related validated prediction models from multiple sources
First Claim
1. A system for generating a prediction model for a health outcome of interest comprising:
- (a) a plurality of electronic storage media, each comprising a Model Deconstruction and Transfer platform (MDT), wherein each electronic storage media configured for receiving data from only one of a plurality of healthcare centers, wherein the MDT is comprised of a variable library (VL) comprised of variables relevant to a health outcome of interest, wherein upon completion of data entry by a healthcare center, the MDT generates a first prediction model (PM0) for the health outcome of interest, wherein the PM0 represents a statistical relationship among the variables that are predictive of the health outcome of interest, and further wherein upon generation of the PM0, the MDT automatically destroys the data entered into the electronic storage media; and
(b) a server configured to receive the MDT and deconstruct the PM0 from the electronic storage media received from each of the plurality of healthcare centers, wherein the server is configured to perform the following functions,(i) combine the PM0 from the plurality of healthcare centers;
(ii) generate a Model Component Library, MCL from each PM0, wherein the MCL comprises components that result from deconstruction of each PM0,(iii) generate at least one second prediction model, PM1, from the MCL based upon differential weighting of the MCL components relevant to the health outcome of interest, wherein the at least one PM1 provides a prediction of the health outcome of interest for individuals in a broad population, wherein the broad population is represented by the data entered into the MDT by the plurality of healthcare centers;
wherein the system expands predictive scope of a healthcare center that does not have sufficient data to develop its own predictions for a health outcome of interest.
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Abstract
Provided is a method for generating prediction models from multiple healthcare centers. The method allows a third party to use data sets from multiple sources to build prediction models. By entering the data sets in a Model Deconstruction and Transfer (MDT) platform, a healthcare center may provide data to a third party without the need to de-identify data or to physically transfer any identifying or de-identified data from the healthcare center. The MDT platform includes a variable library, which allows the healthcare center to select variables that will be used to generate and validate the prediction model. Also provided is a method for compensating sources that contribute data sets based upon the percentage of clinical data that is used to generate a prediction model.
61 Citations
36 Claims
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1. A system for generating a prediction model for a health outcome of interest comprising:
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(a) a plurality of electronic storage media, each comprising a Model Deconstruction and Transfer platform (MDT), wherein each electronic storage media configured for receiving data from only one of a plurality of healthcare centers, wherein the MDT is comprised of a variable library (VL) comprised of variables relevant to a health outcome of interest, wherein upon completion of data entry by a healthcare center, the MDT generates a first prediction model (PM0) for the health outcome of interest, wherein the PM0 represents a statistical relationship among the variables that are predictive of the health outcome of interest, and further wherein upon generation of the PM0, the MDT automatically destroys the data entered into the electronic storage media; and (b) a server configured to receive the MDT and deconstruct the PM0 from the electronic storage media received from each of the plurality of healthcare centers, wherein the server is configured to perform the following functions, (i) combine the PM0 from the plurality of healthcare centers; (ii) generate a Model Component Library, MCL from each PM0, wherein the MCL comprises components that result from deconstruction of each PM0, (iii) generate at least one second prediction model, PM1, from the MCL based upon differential weighting of the MCL components relevant to the health outcome of interest, wherein the at least one PM1 provides a prediction of the health outcome of interest for individuals in a broad population, wherein the broad population is represented by the data entered into the MDT by the plurality of healthcare centers; wherein the system expands predictive scope of a healthcare center that does not have sufficient data to develop its own predictions for a health outcome of interest. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36)
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Specification