Patents by Inventor Pritesh J. Shah

Pritesh J. Shah has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).

  • Publication number: 20250132005
    Abstract: A method includes receiving a prescription benefit request and identifying one or more covered alternative drugs. The method also includes identifying one or more additional alternative drugs based on at least one of the requested drug and determining whether the one or more additional alternative drugs includes at least one covered additional alternative drug. The method also includes determining, for each of the at least one covered additional alternative drug and the one or more covered alternative drugs, an alternative drug value. The method also includes identifying the at least one covered additional alternative drug and the one or more covered alternative drugs having a lowest alternative drug value and generating a request response indicating at least the alternative drug of the at least one covered additional alternative drug and the one or more covered alternative drugs having the lowest alternative drug value.
    Type: Application
    Filed: December 31, 2024
    Publication date: April 24, 2025
    Inventors: Amit K. Bothra, Aanal Patel, Daniel C. Casper, Pritesh J. Shah, Jonelle Lofton, John J. Felo, II, Gaspar Reyes
  • Patent number: 12249414
    Abstract: Systems and methods herein describe a mental health management system. The mental health management system accesses patient data associated with a patient from a database, determines that the patient is associated with a trigger event, identifies a category associated with the trigger event, generates a notification based on the trigger event and the identified category, validates the notification based on a notification history and transmits the notification to a computing device.
    Type: Grant
    Filed: November 17, 2021
    Date of Patent: March 11, 2025
    Assignee: Evernorth Strategic Development, Inc.
    Inventors: Gang Wu, Christopher G. Lehmuth, Amit K. Bothra, Pritesh J. Shah, Zachary A. Goodman, Kelcey A. Blair, Callie S. Carter, Jackie L. Ahlstrom, Amy C. Gross, Jeremy A. Rower, Rochelle R. Henderson, Snezana Mahon
  • Patent number: 12248660
    Abstract: A system includes memory hardware storing processor-executable instructions, a persona, and a data structure associated with the persona. Processor hardware executes the processor-executable instructions. The instructions include generating a graphical user interface and, in response to a first condition, inputting a first set of explanatory variables to a first trained machine learning model to generate a first metric and transforming the graphical user interface according to the persona and the first metric. The instructions include, in response to a second condition, inputting a second set of explanatory variables to a second trained machine learning model to generate a second metric and transforming the graphical user interface according to the persona and the second metric. The first trained machine learning model is different from the second trained machine learning model.
    Type: Grant
    Filed: August 7, 2023
    Date of Patent: March 11, 2025
    Assignee: Evernorth Strategic Development, Inc.
    Inventors: Adithya Chowdary Boppana, Christopher R. Markson, Pritesh J. Shah, Jiawei Kuang, Keith L. Widmer
  • Patent number: 12243630
    Abstract: A method includes receiving a prescription benefit request and identifying one or more covered alternative drugs. The method also includes identifying one or more additional alternative drugs based on at least one of the requested drug and determining whether the one or more additional alternative drugs includes at least one covered additional alternative drug. The method also includes determining, for each of the at least one covered additional alternative drug and the one or more covered alternative drugs, an alternative drug value. The method also includes identifying the at least one covered additional alternative drug and the one or more covered alternative drugs having a lowest alternative drug value and generating a request response indicating at least the alternative drug of the at least one covered additional alternative drug and the one or more covered alternative drugs having the lowest alternative drug value.
    Type: Grant
    Filed: February 22, 2022
    Date of Patent: March 4, 2025
    Assignee: Evernorth Strategic Development, Inc.
    Inventors: Amit K. Bothra, Aanal Patel, Daniel C. Casper, Pritesh J. Shah, Jonelle Lofton, John J. Felo, II, Gaspar Reyes
  • Patent number: 12243645
    Abstract: A computer-implemented method includes defining model attributes including a training iteration value that defines a set of training iterations to be used in machine learning to associate portions of feedback data with a set of topic groups based on similarities in concepts conveyed in the feedback data. The method includes removing at least some of the confidential information from the feedback data. The method includes receiving a topic model number selection that indicates a subset of the set of topic groups. The method includes using machine learning to train a machine model based on the model attributes and the topic model number selection. The method includes generating a display showing at least one of a topic cluster graph or a word cloud based on the machine model.
    Type: Grant
    Filed: December 18, 2023
    Date of Patent: March 4, 2025
    Assignee: Express Scripts Strategic Development, Inc.
    Inventors: Pritesh J. Shah, Christopher R. Markson, Logan R. Meltabarger
  • Publication number: 20240282452
    Abstract: A computer-implemented method for generating one or more summarizations of a large volume of feedback data includes obtaining the feedback data. The feedback data is provided from disparate sources. The method includes separating the feedback data into a set of sentences, generating feedback embeddings of the set of sentences by providing the set of sentences to a set of machine models, providing topic input data to the set of machine models, computing sentence similarity of the feedback embeddings, calculating an importance score for each sentence of the set of sentences, ranking the set of sentences according to their respective importance scores, selecting one or more subsets of the set of sentences to generate the one or more summarizations, generating a visual representation of the one or more summarizations, and displaying the visual representation in an interactive user interface.
    Type: Application
    Filed: May 2, 2024
    Publication date: August 22, 2024
    Inventors: Swati Tyagi, Rahul Rajendran, Christopher R. Markson, Pritesh J. Shah
  • Patent number: 12039347
    Abstract: A method includes storing a parameter related to a user, storing descriptive data for multiple identifiers, and indexing multiple events. Each event corresponds to a physical object supplied to a user on behalf of an entity. The method includes identifying a first set of identifiers based on commonality among the descriptive data. The method includes training a machine learning model for the first set of identifiers based on event data from within a predetermined epoch. The method includes receiving an indication of a selected identifier and determining a first intake metric of the selected identifiers using the machine learning model. The method includes determining a second intake metric of the selected identifier and the parameter and transforming the user interface according to the first and second intake metrics. The first intake metric represents an amount of resources expected to be received during a second epoch subsequent to the predetermined epoch.
    Type: Grant
    Filed: March 30, 2023
    Date of Patent: July 16, 2024
    Assignee: Express Scripts Strategic Development, Inc.
    Inventors: Christopher R. Markson, Pritesh J. Shah, Christopher G. Lehmuth
  • Patent number: 12033731
    Abstract: A content analysis system includes a processor executing instructions from memory. The instructions include, in response to receiving a request signal from a user device, obtaining feedback items, each having a source indicator; identifying unique source indicators; and, for each source indicator, aggregating corresponding ones of the feedback items. A set of filtered feedback items is generated according to either first or second access levels associated with a user of the user device. A subset of filtered feedback items is selected according to a date range specified by the request signal, a set of automated rules is applied, and natural language processing is performed based on frequency of presence of salient terms to identify themes. A control signal is transmitted to a user interface of the user device instructing display of a representation that indicates a change in the frequency of the identified themes over the specified date range.
    Type: Grant
    Filed: February 5, 2021
    Date of Patent: July 9, 2024
    Assignee: Express Scripts Strategic Development, Inc.
    Inventors: Logan R. Meltabarger, Pritesh J. Shah, Amit K. Bothra, David A. Tomala, Christopher R. Markson, Bose S. Daggubati, Christopher G. Lehmuth
  • Publication number: 20240193231
    Abstract: A computer system includes memory hardware configured to store a transcription database, a call database, and instructions. The transcription database includes multiple call transcription data entries. The call database includes multiple agent call log data entries. The computer system executes instructions including joining the call transcription data entries with the agent call log data entries according to associated timestamps. The instructions include, for at least one of the set of joined call data entries, generating an input vector for an unsupervised machine learning model. The instructions include supplying the input vector to the model to assign an output topic classification of the model to the joined call data entry associated with the input vector, and supplying the input vector to at least one sub-topic model associated with the output topic classification to assign one or more sub-topic output classifications to the joined call data entry associated with the input vector.
    Type: Application
    Filed: February 21, 2024
    Publication date: June 13, 2024
    Inventors: Akash Dwivedi, Christopher R. Markson, Pritesh J. Shah
  • Patent number: 12009087
    Abstract: Systems and methods in this document describe a mental health management system. The mental health management system accesses patient data associated with a patient from a database, determines that the patient is associated with a trigger event, generates a prediction, using a predictive modeling system trained to analyze the patient data, the prediction corresponding to a probability that the patient's current medication data will be modified, stores the prediction in association with the patient data, and transmits the prediction to a computing device.
    Type: Grant
    Filed: July 27, 2021
    Date of Patent: June 11, 2024
    Assignee: Evernorth Strategic Development, Inc.
    Inventors: Gang Wu, Christopher G. Lehmuth, Amit K. Bothra, Pritesh J. Shah
  • Patent number: 11977903
    Abstract: A method includes receiving a first set of identifiers selected based on commonality among descriptive data corresponding to the identifiers of the first set. Each identifier corresponds to a user who has been supplied a physical object. The method includes identifying event data for the first set within a specified epoch. The method includes training a machine learning model for the first set using the identified event data. The machine learning model is trained using parallel processing of records from a storage structure storing the event data. The parallel processing includes assigning analysis of the event data of each of a subset of the first set to respective processor threads for parallel execution on processing hardware. The trained machine learning model is configured to receive a selected identifier and generate an output representing an amount of resources expected to be used by the selected identifier for a subsequent epoch.
    Type: Grant
    Filed: November 28, 2022
    Date of Patent: May 7, 2024
    Assignee: Express Scripts Strategic Development, Inc.
    Inventors: Christopher R. Markson, Pritesh J. Shah, Christopher G. Lehmuth
  • Publication number: 20240120103
    Abstract: A computer-implemented method includes defining model attributes including a training iteration value that defines a set of training iterations to be used in machine learning to associate portions of feedback data with a set of topic groups based on similarities in concepts conveyed in the feedback data. The method includes removing at least some of the confidential information from the feedback data. The method includes receiving a topic model number selection that indicates a subset of the set of topic groups. The method includes using machine learning to train a machine model based on the model attributes and the topic model number selection. The method includes generating a display showing at least one of a topic cluster graph or a word cloud based on the machine model.
    Type: Application
    Filed: December 18, 2023
    Publication date: April 11, 2024
    Inventors: Pritesh J. Shah, Christopher R. Markson, Logan R. Meltabarger
  • Patent number: 11947629
    Abstract: A computer system includes processor hardware configured to execute instructions that include joining at least a portion of multiple call transcription data entries with at least a portion of multiple agent call log data entries according to timestamps associated with the entries to generate a set of joined call data entries, and validating the joined call data entry by determining whether a transcribed entity name matches with entity identifier information associated with the agent call log data entry. The instructions include preprocessing the joined call data entry according to word confidence score data entries associated with the call transcription data entry to generate preprocessed text, performing natural language processing vectorization on the preprocessed text to generate an input vector, and supplying the input vector to an unsupervised machine learning model to assign an output topic classification of the model to the joined call data entry associated with the input vector.
    Type: Grant
    Filed: September 1, 2021
    Date of Patent: April 2, 2024
    Assignee: Evernorth Strategic Development, Inc.
    Inventors: Akash Dwivedi, Christopher R. Markson, Pritesh J. Shah
  • Patent number: 11848101
    Abstract: A method includes defining model attributes of a machine model that organizes feedback data into topic groups based on similarities in concepts in the feedback data. The model attributes include a topic model number that defines how many topic groups are to be created, a hyperparameter optimization alpha value, and/or a hyperparameter optimization beta value. The method also includes generating the machine model using the model attributes that are defined and the feedback data, and applying the machine model to the feedback data to divide different portions of the feedback data into the different topic groups based on contents of the feedback data, the topic model number, the hyperparameter optimization alpha value, and/or the hyperparameter optimization beta value.
    Type: Grant
    Filed: June 30, 2021
    Date of Patent: December 19, 2023
    Assignee: Express Scripts Strategic Development, Inc.
    Inventors: Pritesh J. Shah, Christopher R. Markson, Logan R. Meltabarger
  • Patent number: 11830629
    Abstract: A method includes generating an intervention model by determining principal components for features of a training set, associating each feature of the training set with one of the principal components, selecting features of the training set most closely correlated with the principal components, performing a regression analysis on the selected features to determine a subset of the selected features that are most closely correlated with a model target, training a machine learning model with the subset, verifying the trained machine learning model with a verification set, and saving the verified trained machine learning model as the intervention model. The method includes determining an intervention expectation indicating a likelihood that the user will take action in response to an intervention being execute, determining a likelihood of a gap in care for the user, selecting and scheduling an intervention for execution based on the care gap likelihood and the intervention expectation.
    Type: Grant
    Filed: January 9, 2023
    Date of Patent: November 28, 2023
    Assignee: Express Scripts Strategic Development, Inc.
    Inventors: Amit K. Bothra, Pritesh J. Shah, Christopher G. Lehmuth, Bradley D. Flynn
  • Patent number: 11830610
    Abstract: A method includes generating an intervention model by determining principal components for features of a training set, associating each feature of the training set with a principal component, selecting features of the training set most highly correlated with principal components, training a machine learning model with at least some of the selected features, and saving the verified trained machine learning model as the intervention model. The method includes determining multiple channel-specific intervention expectations. Each channel-specific intervention expectation indicates a likelihood that the user will take action in response to an intervention being executed using the engagement channel corresponding to the channel-specific intervention expectation. The method includes selecting an intervention and scheduling the selected intervention for execution.
    Type: Grant
    Filed: December 31, 2022
    Date of Patent: November 28, 2023
    Assignee: Express Scripts Strategic Development, Inc.
    Inventors: Amit K. Bothra, Pritesh J. Shah, Christopher G. Lehmuth, Bradley D. Flynn, Varun Tandra
  • Publication number: 20230376173
    Abstract: A system includes memory hardware storing processor-executable instructions, a persona, and a data structure associated with the persona. Processor hardware executes the processor-executable instructions. The instructions include generating a graphical user interface and, in response to a first condition, inputting a first set of explanatory variables to a first trained machine learning model to generate a first metric and transforming the graphical user interface according to the persona and the first metric. The instructions include, in response to a second condition, inputting a second set of explanatory variables to a second trained machine learning model to generate a second metric and transforming the graphical user interface according to the persona and the second metric. The first trained machine learning model is different from the second trained machine learning model.
    Type: Application
    Filed: August 7, 2023
    Publication date: November 23, 2023
    Inventors: Adithya Chowdary Boppana, Christopher R. Markson, Pritesh J. Shah, Jiawei Kuang, Keith L. Widmer
  • Publication number: 20230268044
    Abstract: A method includes receiving a prescription benefit request and identifying one or more covered alternative drugs. The method also includes identifying one or more additional alternative drugs based on at least one of the requested drug and determining whether the one or more additional alternative drugs includes at least one covered additional alternative drug. The method also includes determining, for each of the at least one covered additional alternative drug and the one or more covered alternative drugs, an alternative drug value. The method also includes identifying the at least one covered additional alternative drug and the one or more covered alternative drugs having a lowest alternative drug value and generating a request response indicating at least the alternative drug of the at least one covered additional alternative drug and the one or more covered alternative drugs having the lowest alternative drug value.
    Type: Application
    Filed: February 22, 2022
    Publication date: August 24, 2023
    Inventors: Amit K. Bothra, Aanal Patel, Daniel C. Casper, Pritesh J. Shah, Jonelle Lofton, John J. Felo, II, Gaspar Reyes
  • Patent number: 11720228
    Abstract: A computerized method for transforming an interactive graphical user interface according to machine learning includes selecting a persona, loading a data structure associated with the selected persona, and generating the interactive graphical user interface. The method includes, in response to a user selecting a first selectable element, inputting a first set of explanatory variables to a first trained machine learning model to generate a first metric, and transforming the user interface according to the selected persona and the first metric. The method includes, in response to the user selecting a second selectable element, inputting a second set of explanatory variables to a second trained machine learning model to generate a second metric, and transforming the user interface according to the selected persona and the second metric. In various implementations, first metric is a first probability of the persona being approved for a first prior authorization prescription.
    Type: Grant
    Filed: August 5, 2021
    Date of Patent: August 8, 2023
    Assignee: Evernorth Strategic Development, Inc.
    Inventors: Adithya Chowdary Boppana, Christopher R. Markson, Pritesh J. Shah, Jiawei Kuang, Keith L. Widmer
  • Publication number: 20230236850
    Abstract: A method includes storing a parameter related to a user, storing descriptive data for multiple identifiers, and indexing multiple events. Each event corresponds to a physical object supplied to a user on behalf of an entity. The method includes identifying a first set of identifiers based on commonality among the descriptive data. The method includes training a machine learning model for the first set of identifiers based on event data from within a predetermined epoch. The method includes receiving an indication of a selected identifier and determining a first intake metric of the selected identifiers using the machine learning model. The method includes determining a second intake metric of the selected identifier and the parameter and transforming the user interface according to the first and second intake metrics. The first intake metric represents an amount of resources expected to be received during a second epoch subsequent to the predetermined epoch.
    Type: Application
    Filed: March 30, 2023
    Publication date: July 27, 2023
    Inventors: Christopher R. Markson, Pritesh J. Shah, Christopher G. Lehmuth