System and method for weighting manageable patient attributes during criteria evaluations for treatment
First Claim
1. A system for evaluating attribute values to determine eligibility for a first treatment, the system comprising:
- one or more computer processors; and
a memory containing a program which, when executed by the one or more computer processors performs an operation comprising;
responsive to receiving input regarding a first patient, determining a topic based on parsing the received input using natural language processing, the topic comprising a request to identify treatment protocols for which the first patient can be eligible, wherein the topic is determined by a question classifier component of an application and stored in a feature store;
determining, based on a corpus and by a pipeline execution component of the application, a set of required attributes associated with a treatment protocol associated with the first treatment, wherein the pipeline execution component reduces processing of sources in the corpus that do not pertain to the stored topic;
responsive to receiving a case, wherein the case includes a patient history containing patient attribute values for the first patient, identifying, by an attribute verification component of the application, a first patient attribute value that does not satisfy a first attribute specified by the treatment protocol as a required attribute;
determining that the first patient is not currently eligible to receive the first treatment, based on determining that the first patient attribute value does not satisfy the first attribute specified by the treatment protocol;
upon determining that the first patient is not currently eligible to receive the first treatment, determining, based on evaluating the patient history using one or more machine learning models, a likelihood that the patient will meet the first attribute in the future due to a change in the first patient attribute value, thereby determining potential eligibility of the first patient for the treatment protocol with a greater measure of accuracy than absent determining the likelihood, wherein the likelihood is determined based on an upward or downward trend of the first patient attribute value and based further on an extent by which the first patient attribute value differs from the required attribute; and
causing approval, based on the determined likelihood, of the first patient for receiving the treatment protocol, whereafter the treatment protocol is applied to the first patient, wherein absent determining the likelihood, the first patient would have been denied from receiving the treatment protocol.
1 Assignment
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Accused Products
Abstract
System, method, and computer program product for evaluating attribute values to determine treatment eligibility, the method by receiving a set of required attributes associated with a treatment protocol, receiving a case, wherein the case includes a patient history containing patient attribute values, identifying a patient attribute value that does not satisfy a required attribute specified by the treatment protocol, determining a likelihood that the patient could meet the required attribute based upon the patient history, and providing an indication of the likelihood that the patient could satisfy the required attribute specified by the treatment protocol.
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Citations
21 Claims
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1. A system for evaluating attribute values to determine eligibility for a first treatment, the system comprising:
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one or more computer processors; and a memory containing a program which, when executed by the one or more computer processors performs an operation comprising; responsive to receiving input regarding a first patient, determining a topic based on parsing the received input using natural language processing, the topic comprising a request to identify treatment protocols for which the first patient can be eligible, wherein the topic is determined by a question classifier component of an application and stored in a feature store; determining, based on a corpus and by a pipeline execution component of the application, a set of required attributes associated with a treatment protocol associated with the first treatment, wherein the pipeline execution component reduces processing of sources in the corpus that do not pertain to the stored topic; responsive to receiving a case, wherein the case includes a patient history containing patient attribute values for the first patient, identifying, by an attribute verification component of the application, a first patient attribute value that does not satisfy a first attribute specified by the treatment protocol as a required attribute; determining that the first patient is not currently eligible to receive the first treatment, based on determining that the first patient attribute value does not satisfy the first attribute specified by the treatment protocol; upon determining that the first patient is not currently eligible to receive the first treatment, determining, based on evaluating the patient history using one or more machine learning models, a likelihood that the patient will meet the first attribute in the future due to a change in the first patient attribute value, thereby determining potential eligibility of the first patient for the treatment protocol with a greater measure of accuracy than absent determining the likelihood, wherein the likelihood is determined based on an upward or downward trend of the first patient attribute value and based further on an extent by which the first patient attribute value differs from the required attribute; and causing approval, based on the determined likelihood, of the first patient for receiving the treatment protocol, whereafter the treatment protocol is applied to the first patient, wherein absent determining the likelihood, the first patient would have been denied from receiving the treatment protocol. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13)
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14. A computer program product to evaluate attribute values to determine eligibility for a first treatment, the computer program product comprising:
a computer-readable storage medium having computer-readable program code embodied therewith, the computer-readable program code executable by one or more computer processors to perform an operation comprising; responsive to receiving input regarding a first patient, determining a topic based on parsing the received input using natural language processing, the topic comprising a request to identify treatment protocols for which the first patient can be eligible, wherein the topic is determined by a question classifier component of an application and stored in a feature store; determining, based on a corpus and by a pipeline execution component of the application, a set of required attributes associated with a treatment protocol associated with the first treatment, wherein the pipeline execution component reduces processing of sources in the corpus that do not pertain to the stored topic; responsive to receiving a case, wherein the case includes a patient history containing patient attribute values for a first patient, identifying, by an attribute verification component of the application, a first patient attribute value that does not satisfy a first attribute specified by the treatment protocol as a required attribute; determining that the first patient is not currently eligible to receive the first treatment, based on determining that the first patient attribute value does not satisfy the first attribute specified by the treatment protocol; upon determining that the first patient is not currently eligible to receive the first treatment, determining, based on evaluating the patient history using one or more machine learning models, a likelihood that the patient will meet the first attribute in the future due to a change in the first patient attribute value, thereby determining potential eligibility of the first patient for the treatment protocol with a greater measure of accuracy than absent determining the likelihood, wherein the likelihood is determined based on an upward or downward trend of the first patient attribute value and based further on an extent by which the first patient attribute value differs from the required attribute; and causing approval, based on the determined likelihood, of the first patient for receiving the treatment protocol, whereafter the treatment protocol is applied to the first patient, wherein absent determining the likelihood, the first patient would have been denied from receiving the treatment protocol. - View Dependent Claims (15, 16, 17, 18, 19, 20, 21)
Specification