Integrated health management platform
First Claim
1. A method for managing healthcare, comprising:
- obtaining multi-dimensional input data for each of a plurality of consumers, the multi-dimensional data including, for each consumer, claim data, self-reported data, and consumer behavior marketing data for the consumer, the consumer behavior marketing data further including behavior, lifestyle, and attitudinal information about the consumer;
a computer using the multi-dimensional input data to iteratively generate a set of clusters for each of a plurality of outcome variables, wherein the clusters for each outcome variable are generated to maximize an output dispersion compression by comparing a ratio of a dispersion of each cluster and an overall dispersion of a population to a predetermined dispersion-compression threshold;
a computer assigning a first consumer to at least one cluster according to multi-dimensional input data for the consumer;
a computer determining for the first consumer at least one health-trajectory prediction from a model associated with the at least one cluster for the first consumer and the multi- dimensional input data for the first consumer;
the computer identifying a target of opportunity for the consumer in accordance with the at least one health-trajectory prediction; and
the computer offering the target of opportunity for the first consumer.
2 Assignments
0 Petitions
Accused Products
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. Multi-dimensional input data may include claim data, consumer behavior marketing data, self-reported data, and biometric data. A consumer may be assigned to a cluster based on the multi-dimensional input data and a characteristic of the consumer may be inferred. A cluster may be associated with a disease progression, and a target of opportunity is determined from the cluster and the disease progression. An impact of the target of opportunity may be assessed by delivering treatment to a consumer at an appropriate time.
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Citations
24 Claims
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1. A method for managing healthcare, comprising:
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obtaining multi-dimensional input data for each of a plurality of consumers, the multi-dimensional data including, for each consumer, claim data, self-reported data, and consumer behavior marketing data for the consumer, the consumer behavior marketing data further including behavior, lifestyle, and attitudinal information about the consumer; a computer using the multi-dimensional input data to iteratively generate a set of clusters for each of a plurality of outcome variables, wherein the clusters for each outcome variable are generated to maximize an output dispersion compression by comparing a ratio of a dispersion of each cluster and an overall dispersion of a population to a predetermined dispersion-compression threshold; a computer assigning a first consumer to at least one cluster according to multi-dimensional input data for the consumer; a computer determining for the first consumer at least one health-trajectory prediction from a model associated with the at least one cluster for the first consumer and the multi- dimensional input data for the first consumer; the computer identifying a target of opportunity for the consumer in accordance with the at least one health-trajectory prediction; and the computer offering the target of opportunity for the first consumer. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14)
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15. An apparatus that manages healthcare, comprising:
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a memory; and a processor accessing the memory to obtain computer-executable instructions, and the processor executing the computer-executable instructions to perform the following operations; obtaining multi-dimensional input data for each of a plurality of consumers, the multi-dimensional data including, for each consumer, claim data and consumer behavior marketing data for the consumer; using the multi-dimensional input data to iteratively generate a set of clusters for each of a plurality of outcome variables, wherein the clusters for each outcome variable are generated to maximize an output dispersion compression by comparing a ratio of a dispersion of each cluster and an overall dispersion of a population to a predetermined dispersion-compression threshold; assigning a first consumer to at least one cluster according to multi-dimensional input data for the consumer; determining, for the first consumer, at least one health-trajectory predictor from a model associated with the at least one cluster for the first consumer and the multi-dimensional input data for the first consumer; identifying a target of opportunity for the consumer in accordance with the at least one health-trajectory predictor; and offering the target of opportunity to the consumer. - View Dependent Claims (16, 17, 18)
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19. A non-transitory computer-readable medium having computer-executable instructions that, when executed by a computer, cause the computer to perform operations comprising:
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obtaining multi-dimensional input data for each of a plurality of consumers, the multi-dimensional data including, for each consumer, claim data and consumer behavior marketing data for the consumer; a computer using the multi-dimensional input data to iteratively generate a set of clusters for each of a plurality of outcome variables, wherein the clusters for each outcome variable are generated to maximize an output dispersion compression by comparing a ratio of a dispersion of each cluster and an overall dispersion of a population to a predetermined dispersion-compression threshold; a computer assigning a first consumer to at least one cluster according to multi-dimensional input data for the consumer; determining, for the first consumer, at least one health-trajectory predictor from a model associated with the at least one cluster for the first consumer and the multi-dimensional input data for the first consumer; identifying a target of opportunity for the consumer in accordance with the at least one health-trajectory predictor; and offering the target of opportunity to the first consumer. - View Dependent Claims (20)
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21. A computer-implemented method, comprising:
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obtaining multi-dimensional input data for a consumer, the multi-dimensional input data including claim data, self-reported data, and consumer behavior marketing data; using the multi-dimensional input data to iteratively generate a set of clusters for each of a plurality of outcome variables, wherein the clusters for each outcome variable are generated to maximize an output dispersion compression by comparing a ratio of a dispersion of each cluster and an overall dispersion of a population to a predetermined dispersion-compression threshold; assigning the consumer to a particular cluster in the set of clusters, wherein the clusters are defined according to an impact of treatment on consumers in each cluster; determining a health trajectory prediction for the consumer according to the multi-dimensional input data and a model specific to the particular cluster, wherein the health trajectory prediction predicts a future status of a health of the consumer according to disease progression, engagement, and impact; identifying a target of opportunity from the health trajectory prediction, wherein the target of opportunity comprises a treatment for a disease of the consumer; and presenting the target of opportunity to the consumer; wherein the obtaining, using, assigning, determining, identifying, and presenting are performed by one or more computers. - View Dependent Claims (22, 23, 24)
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Specification