Methods and systems for evaluating interaction of medical products and dependence on demographic variables
First Claim
1. A computer implemented method of evaluating interaction of two or more medical products or conditions, in the context of a reference condition, based on a dataset of patient records, comprising:
- developing a reference contingency lattice of reference lattice subsets from a subset of the patient records containing the reference condition, wherein each reference lattice subset corresponds to the patient records that contain the reference condition and that contain a respective medical product or condition, or combination of medical products or conditions, of the two or more medical products or conditions;
developing a plurality of comparison contingency lattices, each of the comparison contingency lattices developed from a respective random subset of the patient records not containing the reference condition, wherein each of the respective random subsets is of a same size as the subset of patient records containing the reference condition, and wherein each of the comparison contingency lattices includes comparison lattice subsets, wherein each comparison lattice subset is associated with a respective reference lattice subset and corresponds to the patient records containing the respective medical product or condition, or combination of medical products or conditions, of the associated reference lattice subset; and
comparing, via a processor, the reference lattice subsets of the reference contingency lattice to the associated comparison lattice subsets of the comparison contingency lattices to determine a difference in one of the reference lattice subsets of the reference contingency lattice from the associated comparison lattice subsets of the comparison contingency lattices, wherein the difference is indicative of an interaction between the medical products or conditions with respect to the reference condition.
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Abstract
A computer implemented method of evaluating interaction two or more medical products or conditions, in the context of a reference condition, based on a dataset of patient records includes developing a reference contingency lattice of lattice subsets from a subset of the patient records containing the reference condition, wherein the lattice subsets correspond to the number of patient records that contain each of the two or more medical products or conditions and combinations thereof. A plurality of comparison contingency lattices are developed, each of the comparison contingency lattices developed from a respective random subset of patient records not containing the reference condition, where each of the comparison contingency lattices include lattice subsets that correspond to the number of patient records that contain each of the two or more medical products or conditions and combinations thereof. The lattice subsets of the reference contingency lattice are compared to the corresponding lattice subsets of the comparison contingency lattices to determine whether a lattice subset is indicative of an interaction between the medical products or conditions with respect to the reference condition.
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Citations
29 Claims
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1. A computer implemented method of evaluating interaction of two or more medical products or conditions, in the context of a reference condition, based on a dataset of patient records, comprising:
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developing a reference contingency lattice of reference lattice subsets from a subset of the patient records containing the reference condition, wherein each reference lattice subset corresponds to the patient records that contain the reference condition and that contain a respective medical product or condition, or combination of medical products or conditions, of the two or more medical products or conditions; developing a plurality of comparison contingency lattices, each of the comparison contingency lattices developed from a respective random subset of the patient records not containing the reference condition, wherein each of the respective random subsets is of a same size as the subset of patient records containing the reference condition, and wherein each of the comparison contingency lattices includes comparison lattice subsets, wherein each comparison lattice subset is associated with a respective reference lattice subset and corresponds to the patient records containing the respective medical product or condition, or combination of medical products or conditions, of the associated reference lattice subset; and comparing, via a processor, the reference lattice subsets of the reference contingency lattice to the associated comparison lattice subsets of the comparison contingency lattices to determine a difference in one of the reference lattice subsets of the reference contingency lattice from the associated comparison lattice subsets of the comparison contingency lattices, wherein the difference is indicative of an interaction between the medical products or conditions with respect to the reference condition. - View Dependent Claims (2, 3, 4, 5, 6, 7)
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8. A computer implemented method of evaluating interaction of two or more medical products or conditions, in the context of a reference condition, based on a dataset of patient records, comprising:
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developing a reference orthogonal contingency lattice of reference lattice subsets from a subset of the patient records containing the reference condition, wherein each reference lattice subset corresponds to the patient records that contain the reference condition and that contain a respective medical product or condition, or combination of medical products or conditions, of the two or more medical products or conditions, and wherein each reference lattice subset excludes the medical products or conditions, or combination of medical products or conditions, that correspond to other reference lattice subsets; developing a plurality of comparison contingency lattices, each of the comparison contingency lattices developed from a respective random subset of the patient records not containing the reference condition, wherein each of the respective random subsets is of a same size as the subset of patient records containing the references condition, and wherein each of the comparison contingency lattices includes comparison lattice subsets, wherein each comparison lattice subset is associated with a respective reference lattice subset and corresponds to the patient records containing the respective medical product or condition, or the combination of medical products or conditions, of the associated reference lattice subset, and wherein each comparison lattice subset excludes the medical products or conditions, or combination of medical products or conditions, that correspond to the reference subsets with which the comparison lattice subset is not associated; and comparing, via a processor, the reference lattice subsets of the reference orthogonal contingency lattice to the associated comparison lattice subsets of the comparison contingency lattices to determine a difference in one of the reference lattice subsets of the reference orthogonal contingency lattice from the associated comparison lattice subsets of the comparison contingency lattices, wherein the difference is indicative of an interaction between the medical products or conditions with reference to the reference condition. - View Dependent Claims (9, 10, 11, 12, 13, 14, 15, 16)
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17. A computer implemented method of evaluating interaction of two or more medical products, in the context of a reference condition, based on a dataset of patient records, comprising:
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determining a number, N, of patient records in the dataset containing indications of a medical product A and a medical product B; of patient records in the dataset containing indications of the medical product A and the medical product B, determining a number, Nx, of patient records containing indications of the reference condition; among patient records of a first random sample of size N of patient records of the dataset, the patient records of the first random sample containing the medical product A and not the medical product B, determining a number of the patient records of the first random sample containing the reference condition; among patient records of a second random sample of size N of patient records of the dataset, the patient records of the second random sample containing the medical product B and not the medical product A, determining a number of the patient records of the second random sample containing the reference condition; among patient records of a third random sample of size N of patient records of the dataset, the patient records of the third random sample containing neither the medical product A nor the medical product B, determining a number of the patient records of the third random sample containing the reference condition; and determining, via a processor, whether a second-order bystander effect exists between the reference condition and either of the medical product A or the medical product B based on a comparison of Nx to the number of the patient records of the first random sample containing the reference condition, the number of the patient records of the second random sample containing the reference condition, and the number of the patient records of the third random sample containing the reference condition. - View Dependent Claims (18, 19, 20, 21)
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22. A computer implemented method of evaluating dependence on demographic variables, in the context of a medical product and a reference condition, based on a dataset of patient records, comprising:
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determining a number, N, of patient records in the dataset containing indications of both the medical product and the reference condition; determining an average demographic variable of the patient records in the dataset containing indications of both the medical product and the reference condition; for a continuous demographic variable, determining an average of the demographic variable of patient records in a first random sample of size N, the patient records of the first random sample containing an indication of the medical product and not containing an indication of the reference condition; for the continuous demographic variable, determining an average of the demographic variable of patient records in a second random sample of size N, the patient records of the second random sample containing an indication of the reference condition and not containing an indication of the medical product; for the continuous demographic variable, determining an average of the demographic variable of patient records in a third random sample of size N, the patient records of the third random sample containing neither an indication of the medical product nor an indication of the reference condition; and determining, via a processor, whether the continuous demographic variable, affects an association between the reference condition and the medical product, wherein the determining step is based on a comparison of the average demographic variable of the patient records in the dataset containing indications of both the medical product and the reference condition, the average of the demographic variable of patient records in a first random sample, the average of the demographic variable of patient records in a second random sample, and the average of the demographic variable of patient records in a third random sample. - View Dependent Claims (23, 24)
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25. A computer readable data storage means, the computer readable data storage means not being a transitory signal, and the computer readable data storage means containing program code recorded thereon for implementing the following steps:
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developing a reference contingency lattice of reference lattice subsets from a subset of the patient records containing the reference condition, wherein each reference lattice subset corresponds to the patient records that contain the reference condition and that contain a respective medical product or condition, or combination of medical products or conditions, of the two or more medical products or conditions; developing a plurality of comparison contingency lattices, each of the comparison contingency lattices developed from a respective random subset of the patient records not containing the reference condition, wherein each of the respective random subsets is of a same size as the subset of patient records containing the reference condition, and wherein each of the comparison contingency lattices includes comparison lattice subsets, wherein each comparison lattice subset is associated with a respective reference lattice subset and corresponds to the patient records containing the respective medical product or condition, or combination of medical products or conditions, of the associated reference lattice subset; and comparing, via a processor, the reference lattice subsets of the reference contingency lattice to the associated comparison lattice subsets of the comparison contingency lattices to determine a difference in one of the reference lattice subsets of the reference contingency lattice from the associated comparison lattice subsets of the comparison contingency lattices, wherein the difference is indicative of an interaction between the medical products or conditions with respect to the reference condition.
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26. A computing system comprising:
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a processor; and a system memory containing program code recorded thereon that when executed by the processor performs the following steps; developing a reference contingency lattice of reference lattice subsets from a subset of the patient records containing the reference condition, wherein each reference lattice subset corresponds to the patient records that contain the reference condition and that contain a respective medical product or condition, or combination of medical products or conditions, of the two or more medical products or conditions; developing a plurality of comparison contingency lattices, each of the comparison contingency lattices developed from a respective random subset of the patient records not containing the reference condition, wherein each of the respective random subsets is of a same size as the subset of patient records containing the reference condition, and wherein each of the comparison contingency lattices includes comparison lattice subsets, wherein each comparison lattice subset is associated with a respective reference lattice subset and corresponds to the patient records containing the respective medical product or condition, or combination of medical products or conditions, of the associated reference lattice subset; and comparing, via a processor, the reference lattice subsets of the reference contingency lattice to the associated comparison lattice subsets of the comparison contingency lattices to determine a difference in one of the reference lattice subsets of the reference contingency lattice from the associated comparison lattice subsets of the comparison contingency lattices, wherein the difference is indicative of an interaction between the medical products or conditions with respect to the reference condition.
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27. A computer implemented method of evaluating dependence on demographic variables, in the context of a medical product and a reference condition, based on a dataset of patient records, comprising:
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determining a number, N, of patient records in the dataset containing indications of both the medical product and the reference condition; determining a fraction of the patient records in the dataset containing indications of both the medical product and the reference condition; for a categorical demographic variable, among patient records in a first random sample of size N, determining a fraction of patient records for which the categorical demographic variable has a specified value, the patient records of the first random sample containing an indication of the medical product and not containing an indication of the reference condition; for the categorical demographic variable, among patient records in a second random sample of size N, determining a fraction of patient records for which the categorical demographic variable has a specified value, the patient records of the second random sample containing an indication of the reference condition and not containing an indication of the medical product; for the categorical demographic variable, among patient records in a third random sample of size N, determining a fraction of patient records for which the categorical demographic variable has a specified value, the patient records of the third random sample containing neither an indication of the medical product or an indication of the reference condition; and determining, via a processor, whether the categorical demographic variable affects an association between the reference condition and the medical product, wherein the determining step is based on a comparison of the fraction of the patient records in the dataset containing indications of both the medical product and the reference condition, the fraction of patient records for which the categorical demographic variable has the specified value. - View Dependent Claims (28, 29)
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Specification