System and method for predicting financial data about health care expenses
First Claim
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1. A system for predicting financial data about health care expenses for members of a defined subject population, comprising:
- benchmark data containing derived cost weights for evaluative data items including any actual diagnostic information reported, and any concurrent health status information reported near the time when a diagnosis is made and before the corresponding actual diagnostic information is reported, the benchmark data being created by subjecting evaluative data item information about a pre-defined benchmark population to an analytical technique to derive cost weights and storing the derived cost weights for each evaluative data item in a database;
interaction term data stored in the database, for identifying specified combinations of evaluative data items having incremental cost weights;
timing term data stored in the database, for identifying timing information about evaluative data items having incremental cost weights;
a grouper function for applying the applicable cost weights to each defined subject population member'"'"'s associated evaluative data items using cost weights from the corresponding evaluative data items in the benchmark data, the grouper function also grouping the evaluative data items into pre-determined classifications; and
a modeler function for performing any further grouping into any other classifications, the modeler function applying interaction terms as appropriate to create any aggregated classifications and applying timing terms as appropriate to the classifications to calculate predicted health care expenses.
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Abstract
A system for predicting financial data about health care expenses for members of a defined subject population is disclosed.
44 Citations
30 Claims
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1. A system for predicting financial data about health care expenses for members of a defined subject population, comprising:
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benchmark data containing derived cost weights for evaluative data items including any actual diagnostic information reported, and any concurrent health status information reported near the time when a diagnosis is made and before the corresponding actual diagnostic information is reported, the benchmark data being created by subjecting evaluative data item information about a pre-defined benchmark population to an analytical technique to derive cost weights and storing the derived cost weights for each evaluative data item in a database;
interaction term data stored in the database, for identifying specified combinations of evaluative data items having incremental cost weights;
timing term data stored in the database, for identifying timing information about evaluative data items having incremental cost weights;
a grouper function for applying the applicable cost weights to each defined subject population member'"'"'s associated evaluative data items using cost weights from the corresponding evaluative data items in the benchmark data, the grouper function also grouping the evaluative data items into pre-determined classifications; and
a modeler function for performing any further grouping into any other classifications, the modeler function applying interaction terms as appropriate to create any aggregated classifications and applying timing terms as appropriate to the classifications to calculate predicted health care expenses. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15)
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16. A method for predicting financial data about health care expenses for members of a defined subject population, comprising the steps of:
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creating benchmark data containing derived cost weights for evaluative data items including any actual diagnostic information reported, and any concurrent health status information reported near the time when a diagnosis is made and before the corresponding actual diagnostic information is reported, the benchmark data being created by subjecting evaluative data item information about a pre-defined benchmark population to an analytical technique to derive cost weights and storing the derived cost weights for each evaluative data item in a database;
using interaction term data stored in the database, for identifying specified combinations of evaluative data items having incremental cost weights;
using timing term data stored in the database, for identifying timing information about evaluative data items having incremental cost weights;
applying the applicable cost weights to each defined subject population member'"'"'s associated evaluative data items using cost weights from the corresponding evaluative data items in the benchmark data, the grouper function also grouping the evaluative data items into pre-determined classifications; and
modeling by performing any further grouping into any other classifications, the modeler function applying interaction terms as appropriate to create any aggregated classifications and applying timing terms as appropriate to the classifications to calculate predicted health care expenses. - View Dependent Claims (17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30)
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Specification
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Current AssigneeDXCG, Inc.
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Original AssigneeDXCG, Inc.
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InventorsHaughton, John F., Kramer, Marilyn Schlein, Yi, Rong, McMillan, Benjamin
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Application NumberUS10/226,653Publication NumberTime in Patent OfficeDaysField of SearchUS Class Current705/2CPC Class CodesG06Q 10/10 Office automation; Time man...G06Q 40/08 Insurance
